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A wireless body area network (WBAN) is a type of wireless sensor network that plays a crucial role in monitoring patient healthcare. In this network, sensor nodes are typically placed inside or outside the patient's body. These nodes are capable of transmitting data to the sink node when any functional changes in the patient are detected. The routing and energy efficiency of the network nodes are challenging tasks in WBAN, as each sensor node operates on a battery. Therefore, in multi-hop routing designing a robust routing protocol has a significant impact on reducing energy consumption during the selection of the next hop. In this paper, a simple novel routing protocol named simple energy-aware and reliable (SEAR) routing protocol is proposed to transmit reliable data packets in a WBAN. The proposed routing scheme considers the remaining energy of sensor nodes, priority data, and hop count to the sink node as significant metrics for dynamically selecting the best forwarder node. Furthermore, the proposed protocol utilizes the route reliability factor (RRF) to select the optimal route among all possible routes between the source sensor node and the sink node. RRF selects the route with the maximum route residual energy and minimum hop count. As a result, SEAR has the ability to provide effective single-hop and multi-hop routing data transmission to improve the reliability of data transmission, decrease the energy consumption of the sensor nodes, and prolong the lifetime of the network. The simulation results show that the performance of the SEAR routing protocol outperforms the existing routing protocols for the metrics: packet loss ratio, throughput, end-to-end delay, normalized routing load, energy consumption, and network lifetime. The results indicate that the proposed protocol improves total energy consumption by 18.76% and 10.89% when compared to EERR-RLFL and AMCRP respectively. Meanwhile, SEAR reduces the average end-to-end delay by 17% and 9%, packet loss ratio by 29.48% and 17.69%, and normalized routing load by 31.17% and 20.91%. Additionally, SEAR achieves up to 16% and 9.71% higher throughput compared to EERR-RLFL and AMCRP routing protocols respectively. Overall, the results obtained indicate that the proposed SEAR routing scheme significantly enhances the overall performance of the network. [ABSTRACT FROM AUTHOR]

The extensive utilization of IoT applications leads to the aggregation of a substantial volume of data, presenting a crucial challenge in terms of data routing within these networks. RPL intentionally surpasses the limitations sometimes observed in low-power and lossy networks, which are particularly prevalent in IoT networks. The RPL protocol is designed specifically for static networks that do not involve mobility or topological changes. The RPL protocol guarantees continuous connectivity between nodes and mitigates the risk of data loss in stationary IoT applications that do not involve mobility or alterations in network configuration. The article utilizes a mobility aid technology known as network performance stability using the intelligent routing protocol (nPSIR), which expands upon RPL. The Mobility Support Entity (nPSIR) facilitates the displacement of all nodes, with the exception of the root node, and ensures uninterrupted connection during mobility. Moreover, it deals with the situation where there is a physical barrier between two interconnected nodes in a changing environment. In order to achieve this objective, it employs a dynamic trickle timer that operates within two distinct ranges. Furthermore, it utilizes a neighbor link quality table, a mechanism for selecting the most beneficial parent node in the event of migration, a measure of confidence, the identification of crucial regions, and a blacklist. Multiple simulations validate that nPSIR effectively decreases hand-off delay and improves packet delivery, despite the minor drawbacks of increased signaling costs and power consumption. The delivery ratio decreases the quantity of lost data packets and surpasses both RPL as a responsive protocol and mRPL as a proactive protocol in relation to mobility. [ABSTRACT FROM AUTHOR]

In the world of connected devices with enormous application market, wireless sensor network comes with inherent challenges. Energy consumption balancing among the sensors affects its lifetime and connectivity. A hybrid approach for the randomly deployed sensor network is proposed in this paper with better consumption energy balance through the lifetime of the sensor network. An optimized threshold probability is analyzed for the improvement of network lifetime in comparison with stable election protocol. Simulation results provide improved consumption energy distribution and prolonged network lifetime of heterogeneous wireless sensor network. The proposed protocol is reactive to the change in the network, making it suitable for the Internet of Things applications. [ABSTRACT FROM AUTHOR]

With the widespread use of wireless sensor networks, one of the most pressing concerns is extending the lifetime of the sensors. By deploying directional antenna arrays, millimeter wave (mmWave) is a possible candidate for wireless energy transfer (WPT). This paper investigates a beneficial combination of WPT and data transmission in a typical mmWave sensor network with Rayleigh channels, where a transmission interval can be divided into two sub-intervals. During the first sub-interval, one hybrid access point (HAP) employs beamforming techniques to transfer energy for serving multiple sensors within the service sector. The sensors then transmit their individual signal in turn to the HAP based on time division multiple address (TDMA) strategy by using the whole harvested energy. According to stochastic geometry, the exact and approximate expressions of beam outage probability for the considered system are determined, respectively. The optimal time allocation of energy harvesting and data transmission for sensors is examined in order to maximize the energy efficiency of the system. The optimization problem can be translated into corresponding parametric form, and the resulting optimization problem can be solved using the Lagrange dual method with Karush–Kuhn–Tucker (KKT) conditions. The numerical results show the variation trend of the beam outage probability under various parameters and verify the accuracy of the theoretical analyses. Furthermore, the simulation results illustrate that the proposed optimal time allocation strategy can significantly enhance the overall energy efficiency of the system compared with a similar scheme. [ABSTRACT FROM AUTHOR]

The design of underwater wireless sensor networks (UWSNs) faces many challenges, including power consumption, storage, battery life, and transmission bandwidth. UWSNs usually either use node clustering or multi-hop routing as their energy-efficient optimization algorithms. The cluster optimization technique will organize the sensor nodes into a cluster network, with each cluster led by a cluster head (CH). In contrast, the multi-hop optimization algorithm will create a multi-hop network by sending data to the base station (BS) while switching between different sensor nodes. However, the overburdens of CH nodes impact the performance of the cluster optimization method, whereas the overburdens of nodes close to the BS impact the performance of the multi-hop optimization algorithm. Therefore, clustering and routing procedures can be considered as a simultaneous NP-hard problem that metaheuristic algorithms can address. With this motivation, this paper proposes an energy-efficient clustering and multi-hop routing protocol using the metaheuristic-based algorithm to increase energy efficiency in UWSNs and lengthen the network life. However, the existing metaheuristic-based methods use two separate algorithms for clustering and multi-hop routing, increasing computational complexity, different initialization, and difficulty in hyperparameters' tuning. In order to address the mentioned shortcomings, this paper proposes a novel hierarchical structure called hierarchical chimp optimization (HChOA) for both clustering and multi-hop routing processes. The proposed HChOA is validated using various metrics after being simulated using an extended set of experiments. Results are compared to those from LEACH, TEEN, MPSO, PSO, and IPSO-GWO to validate the impact of the HChOA. According to the findings, the HChOA performed better than other lifespan and energy usage benchmarks. [ABSTRACT FROM AUTHOR]

In optical networks, increasing longevity is of critical importance. This article describes a cutting-edge routing protocol based on Q-learning techniques that have been meticulously constructed to extend the lifetime of optical networks by enhancing energy effectiveness and throughput. The protocol dynamically manages energy usage using Q-learning, a reinforcement learning approach. The primary objective is to choose routing algorithms that optimize long-term revenues for individual nodes while increasing energy efficiency. In a detailed study, the protocol's performance is compared to that of well-known rivals such as Low-Energy Adaptive Clustering Hierarchy (LEACH), Multi-Hop Low-Energy Adaptive Clustering Hierarchy (M-LEACH), and Balanced Low-Energy Adaptive Clustering Hierarchy (B-LEACH) (B-LEACH). The evaluation considers several factors, including network durability as measured by active/inactive node ratios, energy efficiency as measured by per-round energy consumption, quality of service as measured by throughput per round, and scalability as measured over networks with 40, 70, and 100 nodes. The complete examination for each network configuration spans over 5,000 cycles. M-LEACH outperforms LEACH and B-LEACH in all performance measures in the simulation results test, establishing a new benchmark. It is fascinating to compare the performance of the unique Q-learning-based protocol to that of LEACH, M-LEACH, and B-LEACH. Regarding network durability, energy efficiency, quality of service, and scalability, the proposed protocol outperforms. [ABSTRACT FROM AUTHOR]

One of the network performance challenges of Vehicular Ad Hoc Networks (VANET) is the Black Hole attack. This destructive attack severely damages the network performance if succeeded. By replying to a route request with the minimum routing cost and the maximum sequence number (SN) value, the malicious vehicle can fool the source vehicle that it has the "freshest" and best cost-effective route to the destination vehicle. As a result, all data packets intended to a legitimate destination are caught and destroyed by the malicious vehicle. This may also cause a serious risk for autonomous vehicle control system or traffic warning applications. Previous published malicious detection algorithms suffer high error rates when the malicious node uses a "close-to-legitimate" SN value to attack or actively change the information in the route reply packet. This paper proposes a Black Hole Attack Detection Algorithm (BADA) based on a machine learning approach. In VANETs, it is a challenge to differentiate the behavior of malicious vehicles as they try to avoid detection by imitating that of the normal vehicles. The BADA classification algorithm outperforms existing solutions because it relies on the history of each vehicle's route request and response behavior, and it deploys the k-Nearest Neighbors machine learning algorithm to identify malicious vehicles. The paper also proposes a Black hole Attack Detection Routing Protocol which utilizes the proposed BADA solution to realize a more secured and improved AODV-based protocol. Using the NS2 simulation system, the paper evaluates the performance of the proposed protocol and compares it with related solutions on the traffic network model in Ho Chi Minh city, Vietnam under black hole attacks using minimum SN values. Simulation results have shown that the proposed algorithm can correctly detect the malicious node higher than 99.0%, outperforming previously published algorithms. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) comprises the interconnection of things or objects that are embedded with both hardware and software. The WSN is a tiny sensor with end device sensors that are connected to the Internet. To perform effective routing in the WSN efficient and reliable data collection, schemes are deployed with the routing protocol for low power and lossy networks (RPL) routing scheme for the low power and lossy network. The RPL routing scheme of the low and lossy routing protocol design for the network with the objective function. The objective function in RPL routing involved network construction and maintenance through hop count. The RPL scheme uses the destination-oriented directed acyclic graph (DODAG) with the greedy election for estimation of instability in the network. The routers in the WSN are enabled with the software-defined network (SDN) server node. The process of routing comprises detection of routes between the source and the destination. This paper focused on secure routing and monitoring schemes in WSN. To improve the secure routing process in WSN, this paper developed a deep RPL-software-defined network (DRPL_SDN). The DRPL_SDN concentrated on the parent selection through RPL based on the predicted energy level of the parent node. The prediction is performed with the DRPL_SDN-based reinforcement learning method with the estimation of child count through a partial stability routing mechanism. The secure prediction is performed through the deep reinforcement learning method in DRPL_SDN for the succeeded node count for the routing stability. The security model is evaluated with the utilization of the knowledge discovery in database (KDD) dataset. With the KDD dataset, the different attacks are evaluated in the proposed DRPL_SDN model. Additionally, the proposed DRPL_SDN exhibits better load balancing with the uncontrolled node in the network. The DRPL_SDN focused on the establishment of a link in the available network path through a dynamic controlled environment. The simulation analysis expressed that DRPL_SDN achieves the minimal packet loss of 236 and the energy consumption is minimal for 6%. The simulation examination expressed that the DRPL_SDN model exhibits the ~ 13% higher performance than the RPL and ELDR. [ABSTRACT FROM AUTHOR]

Sensor nodes are expected to remain autonomous for a long period of time and communication must be successfully maintained. Therefore, energy efficiency and communication reliability are the main challenges in wireless sensor networks (WSNs). Clustering-based routing protocols are the main solution to energy constraints in this kind of network. Channel coding is required in a lossy milieu to guarantee reliable and efficient transmission. However, this reliability is compromised by the added energy of encoding and decoding in the network. In this context, to explore the trade-off between energy efficiency and reliability, we proposed two approaches: ACC-LDPC (Adaptive Coding Clustered protocol with LDPC decoding) and ACC-RS/LDPC (Adaptive Coding Clustered protocol with RS and LDPC decoding) for clustered multi-hop WSNs. The proposed approaches are based on intra and inter-cluster distances to enhance the transmission reliability, extend the network lifetime and minimize the energy consumption in the WSN. Simulation results show that ACC-RS/LDPC scheme enhances both energy consumption and transmission reliability compared to the ACC-LDPC scheme in clustered multi-hop WSNs. ACC-RS/LDPC improves the reliability of the uncoded system by 90%, while ACC-LDPC enhances it by 82%. Thus, the ACC-RS/LDPC outperforms the ACC-LDPC by increasing the network lifetime by 33%. [ABSTRACT FROM AUTHOR]

The internet of things (IoT) is a collection of systems connected to an online network consisting of things. Routing Protocol for Low-Power and Lossy Networks (RPL) is a proactive routing protocol for wireless networks based on distance vectors. Several methods have been proposed for improving RPL protocol security, suffering from lack of accuracy, the authenticity of intrusion detection, and lack of scalability. Therefore, in this research, an intrusion detection system based on deep cellular learning automata and semantic hierarchy is developed to increase RPL protocol security. Semantic hierarchy is used to transform attack features into significant values, and deep cellular learning automata are employed to increase the security of the RPL protocol. Here five datasets related to attacks, including Darknet, "Version Number", "NSL-KDD", "Botnet", and Distributed Denial of Service (DDoS), have been used. Comparing the proposed results on five datasets indicates that the proposed method outperforms its counterparts. Also, the proposed model has been tested on Blackhole, NID, and BoT-IoT datasets based on ANN and CNN's Deep Neural Network. The results of penetration detection accuracy of the proposed method on Blackhole datasets, NID, and BoT-IoT were 99.65%, 99.71%, and 93.75%, respectively, which improved by averages of 0.42% compared to ANN and 0.55% compared to CNN methods. [ABSTRACT FROM AUTHOR]

In wireless sensor network projects, it is generally desired to cover the area to be monitored at a given cost and to achieve the maximum useful network lifetime. In the deployment of the wireless sensors, it is necessary to know in advance how many sensor nodes will be required, how much the distance between the nodes should be, etc., or what the transmit power level should be, etc. depending on the channel parameters of the area. This necessitates accurate calculation of variables such as maximum network lifetime, communication channel parameters, number of nodes to be used, and distance between nodes. As numbers reach to the order of hundreds, calculation tends to a NP hard problem to solve. At this point, we employed both single-based and stacked ensemble-based machine learning models to speed up the parameter estimations with highly accurate outcomes. Adaboost was superior over other models (Elastic Net, SVR) in single-based models. Stacked ensemble models achieved best results for the WSN parameter prediction compared to single-based models. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are used in many different fields. One of the most recent and rapidly expanding applications is the Internet of Things (IoT), which enables the connectivity of numerous objects or devices over the Internet. However, WSNs have a bigger concern about battery power than mobile ad hoc networks, which shortens the network's lifetime. As a result, extensive research has been done on lowering WSNs' energy usage. Designing a hierarchical clustering algorithm is one of many methods for lowering the energy consumption of WSNs. Given the restricted hardware capabilities of the sensor nodes, modeling and building energy-efficient routing solutions to enhance the overall network lifetime has emerged as one of the most crucial approaches in wireless sensor networks. Cluster-based heterogeneous routing protocols, a typical feature of routing technology, have demonstrated efficacy in managing topology, energy consumption, data collection or fusion, dependability, or stability in distributed sensor networks. The existing Distributed Energy-Efficient Clustering (DEEC) clustering protocol is changed in this study by switching the power level between the nodes and adding a threshold limit for cluster head selection. The number of packets sent to a base station increases by 843% when comparing the proposed improved DEEC protocol to the existing DEEC protocol, increasing the number of living nodes to more than 10,000 rounds, or over 30,000 rounds, which can be used to extend the WSN lifetime. The suggested algorithm outperforms alternative energy-efficient protocols in terms of stability period and network lifetime under various scenarios of area, energy, and node density. [ABSTRACT FROM AUTHOR]

Wireless body area network (WBAN) is a wireless communication technology which facilitates the medical staff to remotely monitor and provide accurate treatment to patients. Wireless body sensors are resource constrained, and consequently, an efficient routing protocol is vital in the design of these networks. Although many protocols have been presented for the routing in WBANs, sufficient features have not been adequately addressed in these techniques. Moreover, parameters of these protocols are manually set and remain constant in all applications, i.e., no automatic tuning procedure is applied to tune the protocol based on the application requirements. To overcome these drawbacks, we introduce a swarm intelligence multi-objective fuzzy protocol (named SIMOF), as a tunable routing protocol in WBANs. The SIMOF comprises two phases, namely fuzzy inference system (FIS) and automatic rule tuning using whale optimization algorithm (WOA). The FIS utilizes a multi-objective fuzzy inference system based on residual energy, distance, reliability, bandwidth, temperature, path loss, and estimated energy consumption, to select proper relay nodes, considering IEEE 802.15.6 standard. To achieve the best performance in the SIMOF, Mamdani rules of the FIS are automatically tuned using WOA. Simulations over three WBANs demonstrate the superiority of the proposed SIMOF routing protocol against the existing techniques in terms of the stability period, path loss, reliability, and hotspot temperature. [ABSTRACT FROM AUTHOR]

Developing clustering algorithms for energy optimization, for the Internet of Things (IoT) applications based mainly on wireless sensors networks services, is a major research challenge. The large amount of data generated by this type of networks, requires a huge quantity of energy and a large number of Internet connections to support communication between different devices via the Internet. Therefore, clustering protocols for data routing in IoT, also referred to as hierarchical routing protocols, need to take into account energy efficiency, the number of individual connections and scalability. In this paper, we propose a novel distributed clustering protocol based on the objects' performances aggregation for hierarchical communications in IoT applications focused on Wireless Sensors Networks (WSNs) for the self election of Cluster Heads (CHs) and the clusters construction. Each node calculates a threshold T(i) considered as a competition timer to become a CH. A node can be a CH only once among a fixed number of rounds. An optimum number of clusters is computed based on the network parameters. Simulation results show that our proposed solution is better with energy management performance parameters compared to the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and two other developed energy-efficient protocols namely LEACH-MAC and TB-LEACH. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is becoming a crucial requirement for linking numerous physical devices or gadgets to the web. Due to large volume of data exchanged, security in IoT still remains a key challenge. Additionally, maintaining security in routing protocols like Routing Protocol for Low-power and Lossy networks (RPL) is becoming more difficult because IoT devices are heterogeneous and resource-constrained. RPL builds a tree topology using control packets. Since more control packets are exchanged, modification in the content of control packets gives rise to a number of attacks including rank attacks, version attacks, flood attacks and so forth. Rank attack is a major attack that causes loop creation, energy depletion, decreased packet delivery, increased packet delivery latency and other problems. Since rank attacks have a significant adverse effect on the network, an effort has been made to enhance the default mechanism of RPL and so that the rank attackers can be quickly identified and isolated. The proposed E-RAD (Enhanced-Rank Attack Detection) algorithm deploys rate limiting technique to control the generation of DIO (DODAG Information Object) packet and also uses DIS (DODAG Information Solicitation) message solicitation to isolate the rank attackers. If an attacker is missed using above mechanism, it can be detected from the consistency check of hash value in DAO (Destination Advertisement Object) message. An alarm is set off against the rank attackers as soon as it is found. An alarm is an attachment to the control message itself and is not a standalone packet. E-RAD algorithm resulted in 1356 J of energy usage, 775 ms of packet delivery delay, 95.53% of delivery ratio, 97.23% of accuracy and 1023 packets of overhead in control packet generation. [ABSTRACT FROM AUTHOR]

Wireless sensor nodes come with small-sized batteries that provide the energy required to do all kinds of activities. Unnecessary usage of the radio, especially during idle listening, drains a lot of energy in Wireless Sensor Networks (WSNs). The proposed model, Energy-Efficient Clustering Algorithm (EECA), prolongs the WSN lifetime by minimizing energy consumption in sensor nodes. In EECA, the target area is considered to be a collection of small regions. The proposed model uses Artificial Neural Network (ANN) to select one node in each region as the cluster head (CH). The sensor nodes with a predefined minimum energy level qualify for the CH selection process. ANN calculates the scores of these nodes based on four parameters – residual energy, number of events detected, distance to the base station, and number of neighbours. The sensor node with the highest score is selected as the CH in its region. A limit called maximum cluster size is also defined to avoid the formation of huge clusters. Only the sensor nodes located close to an event inform the CH about the event. This rule ensures that redundant data is not transmitted to CHs. In the proposed model, a CH checks the medium for a very short duration at the beginning of a slot for incoming transmissions. If the CH does not receive any signal within this duration, it turns its radio OFF. This rule minimizes idle listening in CHs. EECA is compared with some existing medium access control protocols to find out its efficiency. The experimental results show that EECA saves more energy in sensor nodes than in other models. [ABSTRACT FROM AUTHOR]

The location of nodes is critical in underwater wireless sensor networks (UWSNs), which is an ocean monitoring platform. UWSNs are motivated by the popular usage of localization and play a major role in several technologies that depend primarily on innovations and localization of these nodes. Underwater node localization is a critical technology that enables the deployment of a variety of underwater applications. In this study, the underwater nodes are divided into two levels. Firstly, a clock asynchronous localization system (LS-AC) for base layer's node localization is presented. In order to eradicate the original ranging strategy's dependence on active nodes and address the problem of energy consumption, LS-AC performs in-network situation-based monitoring by relying on asynchronous clocks. Secondly, we propose a backtracking search algorithm (OTKL-BSA) based on optimal topology and knowledge learning. It is used to address the issues associated with traditional algorithms' lack of diversity and the imbalance between exploration and exploitation. Thirdly, to solve the problems that the traditional gray wolf optimizer (GWO) is prone to falling into local optimal values and has a low search efficiency, this paper proposes a GWO scheme based on hunting step size (GWO-HSS). Finally, simulation results show that the proposed algorithm outperforms SLMP, MCL-MP, MP-PSO, and MGP in aspects of localization performance. [ABSTRACT FROM AUTHOR]

A crucial research problem in the field of wireless sensor network is to maximize its lifetime. One approach to solve this problem is to group the nodes in clusters or chains. One of the nodes in a cluster or chain takes the responsibility of collecting data from the other sensors in its group and sends the data to the base station or sink. As the energy spent per round is comparatively higher for a cluster head(CH)/chain leader (CL), the lifetime of the network can increase if we rotate the role of CH/CL among the nodes in the cluster/chain. In this paper, we have proposed several algorithms to select CH/CL at different rounds to maximize the lifetime of the WSN. We have shown that maximizing lifetime measured as first node die, can be solved optimally using an integer linear program. Then we have given a polynomial-time algorithm to solve this problem by relaxing to a linear programming problem. We have also given algorithms to maximize the lifetimes measured as half of the nodes die and last node dies. Simulation results indicate significant improvement in the performance of our proposed algorithms compared to BP-DCA, NEECP and naive Bayesian-based algorithm. [ABSTRACT FROM AUTHOR]

Ocean acidification is one of the parameters that affect underwater wireless sensor network routing protocols. The underlying network-level metrics of sensor nodes correspond to depth-dependent interactions. The spatial relevancy of sensor nodes varies drastically due to the mobility of the ocean column. In this work, complexity of the underwater environment and its characteristics are fed along with the sensor node capabilities of internetworking and its communication void. The wireless sensor node embeds medium access control layer timing of sensor packet transmission associated with its communication range and underwater characteristics of transmission and absorption losses. Underwater routing protocol for void avoidance transmission probability (UWRPVA-TP) is proposed, and sensors are deployed across diverse depths. Multi-hop communications as a function of depth-dependent attenuation across the ocean columns and their transmission probabilities have been calculated under mobility scenarios. The simulation result of UWRPVA-TP has been validated for the protocol using different attenuation models for energy consumption and number of alive nodes. Finally, the packet reliability ratio and deadline miss ratio has been calculated to understand the application of the time complexity associated with packet transfer. [ABSTRACT FROM AUTHOR]

Wireless multimedia sensor networks (WMSNs) can gather multi-media events such as road traffic accidents, object monitoring, and scalar data. Additionally, multimedia applications have the potential to generate substantial bandwidth congestion leading to greater energy usage. Researchers in WMSNs are constantly interested in designing and developing energy-efficient routing protocols. Numerous clustering routing protocols have been developed in recent years to overcome the limitation of consuming less energy and prolonging the lifetime of sensor nodes in homogeneous and heterogeneous WMSNs. Existing approaches depend on single-hop communication, in which sensor nodes consume more energy and die faster. Inter-communication nodes can play a more important role in reducing energy by transmitting sensing data in a multi-hop fashion to the base station. In this paper, an Energy-Efficient Multipath Clustering with Load balancing routing protocol for WMSNs (EEMCL) was proposed to minimize the energy consumption and prolong the network lifetime. Clustering-based routing with multi-hop would be used to implement the proposed protocol. To analyze and investigate the performance of the proposed protocol, a simulation model utilizing the MATLAB program is used. The simulation results show that the improvement rate for the proposed protocol is 75% when compared with modified-low energy adaptive clustering hierarchy (MODLEACH), and 65% when compared with energy-efficient multistage routing protocol (EE-MRP) in terms of the number of alive nodes and in terms of residual energy of normal sensor nodes, the improvement rate for the proposed protocol is 86% when compared with MODLEACH, and 67% when compared with EE-MRP. [ABSTRACT FROM AUTHOR]

At present, underwater wireless ad hoc networks (UWAN) are widely used in enormous applications. At the same time, UWAN faced many security issues, like energy leaks. The energy hole will make the network lifetime end soon. However, most existing underwater research has not taken security as serious threat. This article aims to provide a new secure data transmission scheme in UWAN, in which the management and deployment of UWAN is typically done by a trusted authority. The proposed Cluster Tree Enhanced Dempster Shafer based Bidirectional Butterfly Optimization algorithm (CT-EDS-BBO) will be divided into three phases. Initially, the cluster-based tree routing protocol designed for cluster formation, CH selection process, and routing process establishment. In the second phase, the Enhanced Dempster Shafer Evidence Theory uses the fusion rule to evaluate the trust value for each node, which is used to determine the security of each node and to detect the Malicious Node. Finally, the Bidirectional Butterfly Optimization algorithm model is designed to avoid the energy hole issue and to allocate a routing channel for secure data transmission over UWAN. The results obtained from simulation analysis demonstrate that the proposed CT-EDS-BBO has observable benefits over the conventional methods with a Packet Delivery Ratio of 90%, energy consumption of 0.14 J, a network lifetime of 732 s for 200 rounds, and an end-to-end delay of 0.12 s. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) provides a common platform to connect the heterogeneous devices over the internet. Hence, the number of devices connected via the internet and consequently congestion is exponentially increased. Congestion reduces the network performance and negatively affects QoS. RPL (routing protocol for low-power and lossy networks) significantly has responded to IoT routing needs, but controlling congestion and QoS needs have been failed to be considered. Therefore, this paper improved the RPL protocol based on the congestion control and QoS requirements and proposed a protocol called Congestion and QoS-Aware RPL for IoT applications (CQARPL). This protocol selects parents based on multi-metric evaluation, considering the conditions of routes to the root. In addition, it somehow controls the parent selection and the children's acceptance that a balanced DODAG graph is formed. Furthermore, it provides the ability to predict congestion and prevents it from occurring as much as possible. The proposed protocol is implemented by the Cooja simulator and evaluated with different scenarios compared to CLRPL and RPL. The simulation results showed that CQARPL maintains the quality of transmissions and controls congestion in IoT. [ABSTRACT FROM AUTHOR]

In this work, energy efficient routing protocol variants considering different sink mobility in hierarchical cluster based wireless sensor network have been designed and implemented. WSN is a resource hungry network, especially the sensor nodes have limited energy source besides memory, computation power etc. Sensor generated huge traffic in terms of data generation and forwarding to nearest cluster head for further forwarding to base station also cause energy drainage in large extent. Here two energy efficient routing algorithm Brownian motion sink mobility (EERBM) and fixed trajectory mobile sink (EERFT) have been designed and simulated using MATLAB. Performance evaluation of proposed algorithms is done based on several parameters such as path loss, throughput, alive nodes, dead nodes, message received at Sink, average remaining energy and energy consumption over time. Comparison with algorithms having static sink, LEACH, RRPBLC, and EAMMH of both the proposed protocols is done to find that EERBM and EERFT outperform over other existing algorithms in term of above performance metrics. Also, comparison of EERBM and EERFT with EERAMS having mobile sink shows that EERBM and EERFT outperform the earlier one in terms of average residual energy, total energy consumption, no. of dead nodes and alive nodes over rounds. Less energy consumption enhances network lifetime and data received at nodes with increased network stability thus making WSN suitable for real time applications such as health monitoring, surveillance, ambient sensing etc. EERFT is 88.8%, 88.56% and 86% better with respect to dead nodes whereas for alive node 97%, 93.74% and 96%while for total energy consumption 83.65%, 61.52%, and 54.81% lesser than LEACH, EMMAH and EERAMS respectively and for average residual energy 89.99%, 63.13%, 45.49% and 65.94% lesser than LEACH, EMMAH, RRPBLC and EERAMS respectively. For Throughput, EERFT is 57.47% and 92.34% better than LEACH and EAMMH respectively. [ABSTRACT FROM AUTHOR]

Aiming at solving the effective data delivery and energy hole problem in multi-hop cognitive radio sensor networks (CRSNs), a weighted energy consumption minimization-based uneven clustering (ECMUC) routing protocol is proposed in this paper. For the first time, the impact of control overhead on the network performance is taken into consideration, to be specific, the energy consumption of control overhead is integrated with that of data communication to model the network energy consumption. Through effective transformation and theoretical analysis, cluster radius of each ring is derived by minimizing the network energy consumption and balancing the residual energy among nodes in different rings. Distributed cluster heads (CHs) selection and cluster formation are carried out within this range to control the cluster size and the corresponding energy cost. Expected times for being CHs metric is defined to measure nodes' energy and spectral potential and help select powerful CHs. Simulation results show that ECMUC protocol is superior to most clustering protocols designed for CRSNs in terms of network surveillance capability and network lifetime, and it is also demonstrated that taking control overhead into consideration is beneficial for improving the network performance. [ABSTRACT FROM AUTHOR]

Organizing nodes into clusters and forwarding data to the base station (BS) in clustering routing protocols have been widely utilized to improve the energy efficiency, scalability and stability of wireless sensor networks. Making decisions on how many clusters are formed, which nodes are selected as cluster heads (CHs) and who become the relay nodes significantly impact the network performance. Therefore, a distributed clustering routing protocol combined affinity propagation (AP) with fuzzy logic called DAPFL is proposed in this paper, which considers not only energy efficiency but also energy balance to extend the network lifetime. In DAPFL, AP is firstly used to determine the number of clusters and select the best CHs simultaneously based on residual energy, distance between nodes. Then, the optimal next-hop CHs are chosen by using fuzzy logic system with residual energy, data length and distance to BS as descriptors. Simulations in different scenarios are carried out to verify the effectiveness of DAPFL, and the results show that DAPFL exhibits the promising performance in terms of network energy consumption, standard deviation of residual energy, network throughput and lifetime, compared with the up-to-date distributed clustering routing protocols EEFUC, EEFRP, LEACH-AP and APSA. [ABSTRACT FROM AUTHOR]

Wireless sensor network is a group of nodes combined with tiny sensors equipped with transceiver parts used for sensing, monitoring, and data collecting in various environments. It is not possible to support the battery support to the sensors while placed in an unmanned area. Hence, the sensor's energy should be vital, and it is very crucial. Combining the techniques of clustering and proper routing is one of the efficient schemes to save the energy of the sensor nodes. During the clustering process, cluster heads can be chosen with utmost care for load balancing. Along with cluster head selection, this proposed work also focussed on two major things. First, the appropriate relay node can be selected using the fuzzy inference system with sensor energy level as one input and the distance between the relay node and the cluster head node as another input. Secondly, the mobile sink collects the aggregated data from the relay node and sends it to the base station. On combining these two schemes, mobile sink and fuzzy based relay node routing Protocol is proposed. Simulation result shows that the proposed protocol has an improved number of alive nodes and a better network lifetime in terms of energy consumption compared with the existing schemes. [ABSTRACT FROM AUTHOR]

The network-on-chip is a subsystem based on simplified public data network communication protocols for routing using routers. Providing an efficient solution is not a trivial issue due to communication problems caused by network element failure on the chip. The purpose is to maintain the performance of the router in the presence of failure. Therefore, in this paper, by combining path length and an adaptive congestion-aware approach using multi-criteria decision-making technique, a reliable method is introduced that, in case of failure, replaces a reliable path with similar quality of service features. The throughput increase is confirmed in the simulation results of the proposed solution, up to 54.05% and 8.05% with a two-criteria and a single-criteria router, respectively. The hardware overhead of the algorithm is relatively low cost, which maintains scalability for implementation in large network-on-chips. [ABSTRACT FROM AUTHOR]

Despite that IoT technology provides a promising future for human life, some significant challenges such as routing, security, low-cost equipment, energy consumption, privacy, and reliability can considerably affect its performance. In recent studies, routing has been considered as one of the most critical challenges in IoT due to many existing IoT devices in a network. Selecting a non-optimal path increases collision probability and packet latency which sharply reduces the network performance. Hence, a novel flexible, scalable, and efficient routing protocol named LOADng-AT has been introduced in this study to overcome this challenge. Using LOADng-AT, firstly, taking advantage of the hello message, information about link quality parameters up to two hops is exchanged among nodes. This information includes various parameters such as bi-/unidirectional links, ETX, number of neighbors, link stability, received and residual energy, and SINR, gathered by hello message. Secondly, considering those parameters simultaneously, LOADng-AT efficiently chooses the best possible route based on the hybrid AHP-TOPSIS algorithm. The proposed protocol considerably decreases the RREQ broadcast storm. Moreover, it supports an error recovery path without rerunning a new routing process that noticeably decreases the network routing delay. LOADng-AT can be easily adapted to any QoS parameter with very low complexity which is very important for a delay-sensitive IoT-based network. Finally, in case of noisy condition, the proposed protocol can be efficiently used in low-quality links. Simulation results based on several scenarios in the OMNET ++ simulator show that end-to-end delay (EED) and packet delivery ratio (PDR) parameters significantly improved in the proposed method compared to other similar methods. In other words, using LOADng-AT, the mean values of PDR parameter were 98.64 and 82 percent for network sizes 400 × 200 and 800 × 400 m2, respectively, while the mean values of EED were 0.001 and 0.018 for network sizes 400 × 200 and 800 × 400 m2, respectively. The overall improvement for PDR and EED parameters in all 60 considered scenarios compared to similar methods were 82.26 and 16.6 percent, respectively. [ABSTRACT FROM AUTHOR]

With the development of the internet of things, people pay more and more attention to wireless sensor networks. Designing the energy efficient routing is an essential objective for wireless sensor networks. Cluster routing is one of the most popular routing protocols to enhance the network lifetime. However, hotspot problem always exists in cluster-based routing protocol. The task of this study is designing a cluster routing protocol with mobile base station which aims at balancing the energy consumption and prolonging the network lifetime. In this article, we design a particle swarm optimization and artificial bee colony algorithm for clustering and mobile based software-defined wireless sensor networks. The software defined network architecture is used to reduce the energy overhead and computation overhead in sensor nodes. Particle swarm optimization-based cluster routing algorithm is used to calculate the cluster heads and the sojourn locations of base station. Artificial bee colony algorithm-based traversal path algorithm is used to design the move path of the base station. Comparing with relevant protocols, the proposed protocol reduces the energy consumption, enhances the network lifetime and reduces the control overhead. [ABSTRACT FROM AUTHOR]

Mobile Ad-hoc Networks (MANETs) consist of mobile nodes that usually have limited energy resources. MANET routing protocols should consider the dynamics and energy constraints of the network, and this makes them an optimization problem. Various optimization-based MANET routing protocols have been proposed in literature and each of them consider different metrics and try to cope with specific problems. In this paper, a novel heterogeneous MANET routing protocol called "learning Automata and Genetic based Ad hoc On-Demand Distance Vector" (AGEN-AODV) is proposed, in which routes are rated based on energy, stability, traffic, and hop-count criteria. The Genetic Algorithm (GA) in conjunction with Learning Automata (LA) is used to select the optimal route. The LA runs concurrent to the GA and initializes, adjusts and optimizes its coefficients based on the network feedback, preventing the GA from divergence or sub-optimal convergence. Compared with related works, the throughput, packet delivery ratio (PDR), delay, network lifetime, and energy consumption are improved by at least 4%, 8%, 8%, 13%, and 30% respectively. [ABSTRACT FROM AUTHOR]

Acoustic signals are used for communication in underwater sensor networks (UWSNs) because radio signals attenuate heavily when propagating in water, while optical signals have large scattering in water. Data transmission in UWSNs faces great challenges due to the characteristics of underwater acoustic channels. Moreover, high energy consumption and long latency bring about increased challenges for the designs of routing protocols in UWSNs. In this paper, we propose a routing protocol called Layer-based Energy-Efficient Routing (LEER) protocol to address the route failure problem with greedy routing, as well as the long end-to-end delay and high energy consumption problems. In LEER, each node extracts the layer field information from hello packets received and updates its own layer to avoid the problem of routing a packet to a void area. All nodes with the LEER protocol forward packets to a sink node without the need for any location information. Simulation results show that the LEER protocol outperforms the depth-based routing (DBR) protocol in terms of the delivery rate and end-to-end delay. [ABSTRACT FROM AUTHOR]

Energy efficient routing protocol selection for Cluster based Underwater Wireless Sensor Network (CUWSN) is aimed to support monitoring and controlling underwater scenarios in the field of Internet of Underwater Things. The crucial requirement of Underwater Wireless Sensor Network (UWSN) is to prolong network lifespan. The aim of this article is to build energy-efficient UWSN that will trim energy expenditure as well as improve performance in the underwater scenario. In the proposed CUWSN, a UWSN architecture is designed, which uses the benefits of cluster head and multi-hop transmission. The proposed CUWSN extends the network lifetime by using multi-hop transmission. The proposed CUWSN model is simulated using QualNet 7.1 simulation tool. In this article, energy consumption, throughput, packet delivery ratio, transmission delay, error signals, and packet loss parameter indicators are considered to investigate the performance of proposed CUWSN. The outcomes of proposed CUWSN exhibit that the AODV routing protocol surpasses the DYMO routing protocol by 80%, the IERP routing protocol by 75%, STAR routing protocol by 47% and ZRP routing protocol by 81% in perspective of energy efficiency. In references to other performance indicators like average path loss and average interference the IERP routing protocol and in case of throughput the ZRP routing protocol performs well among the five routing protocols. Finally, the AODV routing protocol is energy conservative in the proposed CUWSN. [ABSTRACT FROM AUTHOR]

Underwater wireless sensor network (UWSN) is a new technolog that can be used for various purposes, including ocean tracking and underwater exploration, military surveillance, disaster management, industrial applications, and scientific research. These applications require the sensed data to be routed to the destination, and this results in making the data routing one of the essential parts in designing such applications. High propagation delay, restricted bandwidth, 3D deployment, and energy constraints are some of the challenges that UWSN faces when developing routing protocols. Therefore, to mitigate these challenges, efficient routing protocols are proposed according to the specific application. This paper surveys recently routing protocols for UWSN. Furthermore, each routing protocol's main idea and essential operation are presented and its merits and demerits. There are two types of routing protocols surveyed: location-based and location-free routing protocols. Each type is divided into two sub-categories: those that take into account node mobility and those that do not. The surveyed protocols are evaluated through the analytical method in which these protocols are compared through a wide range of parameters like packet delivery ratio, end-to-end delay, energy efficiency, and reliability. Some of the surveyed protocols are evaluated through the numerical simulation method by using Aqua-Sim with NS2.30 and are compared through packet delivery ratio, end-to-end delay, and energy consumption. This survey's core goal is to encourage more research into improving UWSN routing protocols for better underwater exploration and monitoring. [ABSTRACT FROM AUTHOR]

Advanced metering infrastructure (AMI) is the core component of the smart grid. As the wireless connection between smart meters in AMI is featured with high packet loss and low transmission rate, AMI is considered as a representative of the low power and lossy networks (LLNs). In such communication environment, the routing protocol in AMI network is essential to ensure the reliability and real-time of data transmission. The IPv6 routing protocol for low-power and lossy networks (RPL), proposed by IETF ROLL working group, is considered to be the best routing solution for the AMI communication environment. However, the performance of RPL can be seriously degraded due to jamming attack. In this paper, we analyze the performance degradation problem of RPL protocol under jamming attack. We propose a backup node selection mechanism based on the standard RPL protocol. The proposed mechanism chooses a predefined number of backup nodes that maximize the probability of successful transmission. We evaluation the proposed mechanism through MATLAB simulations, results show the proposed mechanism improves the performance of RPL under jamming attack prominently. [ABSTRACT FROM AUTHOR]

As a key enabling technology of underwater acoustic sensor networks, underwater routing feature a variety of unique characteristics, including limited energy supply, high end-to-end delay and low delivery ratio. All these problems pose challenges in the design of efficient and effective routing protocols. To address such challenges, we propose an adaptive multi-zone geographic routing protocol(AMGR). First, AMGR dynamically adjusts the neighbor information acquisition interval according to the topology change speed, which not only reduces the excessive energy consumption of updating information, but also improves the performance of routing in high dynamic underwater environment. Second, according to the characteristics of different forwarding zones, the multi-region cooperative forwarding mechanism is adaptive used to improve the end-to-end delay and increase delivery ratio under the premise of reducing energy consumption as much as possible. Third, in priority calculation, we consider both the impact of packet transmission advancement and energy consumption, which can ensure less hops and avoid some high advancement nodes running out of energy in advance. Simulation results show that the proposed protocol outperforms AHH-VBF, PCR and restrictive flooding in delivery ratio, end-to-end delay and energy tax. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) consist of sensor nodes, which can sense, process, and then transfer different types of data into the base station. The major role of sensor nodes is to gather data at regular intervals and then send it into the base station. Designing energy-efficient routing protocols is one of the major challenges in WSNs. In this paper, an energy efficient layered routing protocol (EELRP) is proposed. The proposed method divides the network into some concentric circles of different radii. The circles are divided into eight equal sectors. Sections are created through a crossover between layers and sectors. Each section contains some nodes, and the most appropriate one is selected as the agent. The nodes of each section send the sensed data to their agent. Next, the agent aggregates the data, provides error detection and correction according to the redundant residue number system, and then sends information to the agent of the lower section of the same sector. The procedure continues until the information reaches the base station. On comparing the performance of EELRP with that of conventional methods, one can see that EELRP provides an improvement in the network lifetime, energy consumption, packet delivery rate, and the number of path hops. [ABSTRACT FROM AUTHOR]

Internet of things (IoT) is renowned for being a massive revolution led by business leaders and researchers. Routing protocol for low-power and lossy network (RPL) is a standardized protocol that serves the routing need of the IPv6-based low-power and lossy networks, which are the significant enablers of the IoT technology. Despite its many outstanding features, RPL offers very low protection against different routing attacks. In this respect, we mainly emphasize on the sybil attack. Specifically, we focus on three different types of sybil attack on a realistic smart home network topology. Considering the involvement of resource-constraint devices, we propose and evaluate a novel decentralized countermeasure against these attacks. The proposed countermeasure is based on a hybrid approach that involves the use of the geographical location of the nodes and a trust value-based parent selection procedure. Along with this, we use specially configured monitoring nodes that are responsible for the detection of the malicious attacker node(s). Further, we use RPL's multi-instance property to integrate the proposed decentralized architecture into the exiting RPL protocol. We implement the proposed countermeasure in Cooja, the Contiki operating system-based network simulator. The results obtained through our experiments validate the practicality of the proposed countermeasure. [ABSTRACT FROM AUTHOR]

Edge computing perfectly integrates cloud computing centers and edge-end devices together, but there are not many related researches on how the edge-end node devices work to form an edge network and what the protocols used to implement the communication among nodes in the edge network. Aiming at the problem of coordinated communication among edge nodes in the current edge computing network architecture, this paper proposes an edge network routing and forwarding protocol based on target tracking scenarios. This protocol can meet the dynamic changes of node locations, and the elastic expansion of node scale. Individual node failures will not affect the overall network, and the network ensures efficient real-time with less communication overhead. The experimental results display that the protocol can effectively reduce the communications volume of the edge network, improve the overall efficiency of the network, and set the optimal sampling period, so as to ensure that the network delay is minimized. [ABSTRACT FROM AUTHOR]

Flying ad hoc network (FANET) provides portable and flexible communication for many applications and possesses several unique design challenges; a key one is the successful delivery of messages to the destination, reliably. For reliable communication, routing plays an important role, which establishes a path between source and destination on the basis of certain criteria. Conventional routing protocols of FANET generally use a minimum hop count criterion to find the best route between source and destination, which results in lower latency with the consideration that there is single source/destination network environment. However, in a network with multiple sources, the minimum hop count routing criterion along with the 1-Hop HELLO messages broadcasted by each node in the network may deteriorate the network performance in terms of high End-to-End (ETE) delay and decrease in the lifetime of the network. This research work proposes a Reliable link-adaptive position-based routing protocol (RLPR) for FANET. It uses relative speed, signal strength, and energy of the nodes along with the geographic distance towards the destination using a forwarding angle. This angle is used to determine the forwarding zone that decreases the undesirable control messages in the network in order to discover the route. RLPR enhances the network performance by selecting those relay nodes which are in the forwarding zone and whose geographic movement is towards the destination. Additionally, RLPR selects the next hop with better energy level and uses signal strength and relative speed of the nodes to achieve high connectivity-level. Based on the performance evaluation performed in the Network simulator (ns-2.35), it has been analysed that RLPR outperforms the Robust and reliable predictive based routing (RARP) and Ad hoc on-demand distance vector (AODV) protocols in different scenarios. The results show that RLPR achieves a 33% reduction in control messages overhead as compared to RARP and 45% reduction as compared to AODV. Additionally, RLPR shows a 55% improvement in the lifetime of the network as compared to RARP and 65% as compared to AODV. Moreover, the search success rate in RLPR is 16% better as compared to RARP and 28% as compared to AODV. [ABSTRACT FROM AUTHOR]

Anycast is a special operation in ad hoc networks, where source communicates with one suitable destination in anycast zone. AAODV or anycast ad hoc on demand distance vector is an anycast routing protocol designed as an extension of AODV protocol to enable any cast operation in ad hoc networks. However, requirement of stability comes to existence where a huge number of data packets are to be transmitted from anycast source to anycast zone. If source elects one particular peripheral node of the anycast zone and the peripheral anycast destination goes out of the specified zone after receiving only a few number of packets , then source has to again broadcast route requests leading to huge message cost in the network. In our present work, we predict the presence of selected peripheral destination in anycast zone based on its history of location and velocity in earlier time stamps, which is used during route selection in AAODV. Also flooding of route request is directional based on coordinates of anycast zone supplied to the source. This helps to restrain flooding of route request within a limited portion of network. [ABSTRACT FROM AUTHOR]

In the vehicular ad hoc network (VANET), due to the particularity of high-speed movement of vehicle nodes, there are higher challenges in link stability and network topology control overhead. In this paper, a new algorithm of clustering AODV based on edge computing strategy is proposed. Considering the vehicle node energy and speed, the AODV routing protocol based on the minimum hop number is optimized, which divided the communication mode into vehicle to vehicle (V2V) and vehicle to road (V2R) mode. Adding edge server in the road side unit (RSU) and using the idea of clustering, that is, the nodes in the cluster use V2V communication mode, and the nodes between clusters use V2V and V2R combined communication mode to select routes. The algorithm improves the routing efficiency in the high-speed mobile. Experiments show that the algorithm is feasible, reducing the network topology control overhead, lowering the end-to-end delay and improving the packet delivery rate comparing with others in different environment. [ABSTRACT FROM AUTHOR]

ZigBee is one of the latest technologies developed by the ZigBee Alliance to enable Wireless Personal Area works. ZigBee technology has better characteristics when compared with other wireless standards such as WI-FI, Bluetooth and WiMAX, and so on. Though the transmission range in ZigBee ranges up to a few meters, the network has several layers, designed to enable interpersonal communication within the network, appropriate routing technique can lead the data to be reached to a longer distance, leading to an increase in the transmission range. Present research emphases on the maximization of the transmission range in the ZigBee network. For the analysis, the Simulink based software called TRUETIME 2.0 in MATLAB tool is used. Energy Efficient ZigBee based AODV routing protocol with incorporated CSMA-CA MAC channel access (EE-ZAODVCSMA) is proposed for maximizing the transmission range in the ZigBee network. To maximize the transmission range, various soft computing techniques such as Fuzzy Logic, Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System, and one more technique which is an integration of ANN and Genetic Algorithm are applied to the network. A small ZigBee network is implemented with four nodes on LPC 2148 to show the data communication based on the proposed algorithm. [ABSTRACT FROM AUTHOR]

As one of the basic supporting technologies of 5G system, wireless sensor networks technology is facing a new challenge to improve its transmission energy efficiency. This paper considers combining simultaneous wireless information and power transfer (SWIPT) technique and routing technique, and applying them to multi-hop clustered wireless sensor networks (MCWSN), where each node can decode information and harvest energy from a received radio-frequency signal. And the relay nodes in MCWSN can utilize the harvest energy to forward data to their next hop nodes according to the routing scheme. First, we formulate an energy-efficient routing problem of MCWSN with SWIPT. Then, a heuristic energy efficient cooperative SWIPT routing algorithm (EECSR) is presented to find a transmission path with the maximum energy efficiency. Specifically, in EECSR, the resource allocation problem in each hop of the path is transformed to some equivalent convex optimization problems, which are resolved via dual decomposition. Moreover, a distributed routing protocol based on EECSR is proposed. As far as we know, this is the first solution that considers energy efficiency optimization based on routing and SWIPT in MCWSN. Simulation results show that our EECSR algorithm has high energy efficiency and good robustness. And our distributed routing protocol has better real-time performance than traditional protocols. [ABSTRACT FROM AUTHOR]

Wireless sensor network is extensively used for monitoring and surveillance systems. The primary challenges encountered in the area are energy minimization as well as superior quality of services. In this article, two tier complete binary tree based wireless sensor network (TTCBT) has been proposed. The performance analysis of the aforementioned TTCBT is simulated to study several performance metrics such as average end-to-end transmission delay, goodput, packet delivery ratio, residual energy, average jitter, path loss, total energy consumption, received error signals and throughput with the help of QualNet 7.1 simulation software. The simulation results depict that the LANMAR routing protocol is 3% more energy efficient than the FSR routing protocol in the proposed model. [ABSTRACT FROM AUTHOR]

This article presents the design, analyses and implementation of the novel routing protocol for energy optimization based on LEACH for WSN. Network Lifetime is the major problem in various routing protocols used in WSN. In order to overcome that problem, our proposed routing protocol is developed, which is a combination of Micro Genetic algorithm with LEACH protocol. Our proposed µGA-LEACH protocol, strengthen the cluster head (CH) selection and also reduce the energy consumption of the network when compared to existing protocols. This paper shows the improvement of network lifetime and energy consumption with the optimal CH selection based on a micro genetic algorithm and also compared the results with an existing hierarchical routing protocol like LEACH, LEACH-C, LEACH GA and GADA LEACH routing protocol with various packet sizes, and initial energy. [ABSTRACT FROM AUTHOR]

Network coding, as one of the foremost techniques boosting the performance of the wireless networks, has recently acquired notable popularity. As a result, a new category of routing approaches named as the coding-aware routing scheme, has been emerged. In such routing schemes, the possible coding opportunities are identified prior to the path establishment, and paths containing coding opportunities are prioritized to be established. Motivated by the appreciable efficiency of the coding-aware routing schemes, this paper leverages fuzzy logic and proposes a novel coding-aware routing approach alluded to as Fuzzy-logic-based Network Coding-aware Routing (FNCR) protocol. Notwithstanding a number of previously proposed coding-aware routing schemes which merely endeavor to establish paths including more coding opportunities, FNCR suggests embedding a purposefully designed fuzzy system in each node in order to calculate the overall desirability of the nodes in terms of some momentous factors such as the coding capability, the remaining energy, and the workload of the node. In addition to a new routing metric which utilizes the calculated overall desirability, the previously proposed coding conditions are modified such that more possible coding opportunities can now be identified. Simulation results demonstrate that FNCR outperforms the formerly proposed approaches employing network coding, in terms of throughput, end to end delay, packet delivery ratio, and lifetime of the network. [ABSTRACT FROM AUTHOR]

In this paper, we propose a framework for data delivery in nano-scale networks, where numerous wireless sensors are distributed on a human body, small object, tiny plant root, etc. Our framework caters for green energy-efficient applications in the Internet of Nano Things (IoNT) where data is relayed via nano-routers from a multifarious nanonodes towards a gateway connected to a large-scale network such as the Internet. We consider the entire network energy while choosing the next hop for our routed packets in the targeted wireless nanosensor network. Our delivery approach considers resource limitations in terms of hop count, and remaining energy levels. Moreover, extensive simulations are performed and the results confirm the effectiveness of the proposed approach in comparison to other baseline energy-aware routing protocols. [ABSTRACT FROM AUTHOR]

Networking is made out of remote mobile nodes; these nodes progressively structure a network with no centralized controller. Due to this dynamic nature, the nodes act as routers to keep up routing and sending data bundles. Be that as it may, the mobile nodes do not have changeless power supply and need to depend on batteries; in this way, they consume more energy and lessen network lifetime. The proposed work considers the issue of energy consumption in MANET, and it is overwhelmed by the optimization of energy constraint. At first, the mobile nodes in MANET are grouped by the proposed K-medoid clustering algorithm, which can lessen the cost of the routing of data in huge and dense networks. From each cluster, the limited energy consumption-based multipath routing is accomplished by utilizing the opposition genetic-based fish swarm optimization algorithm. The exhibition of the proposed system will be evaluated as far as data transmission, service cost, network lifetime, etc., are concerned. Simulation results revealed that the energy efficiency and network lifetime of our recommended work are improved than those of existing work. [ABSTRACT FROM AUTHOR]

Revenue generated by tourism is positively correlated with the development of any city. In recent years, tourism is getting peak focus among the government, local bodies, and researchers. This has led to increase in initiatives to grow tourism in and across the country. Being one of the most flourishing sectors, tourism in India shows bold signals of emerging as a strong participant in the world of tourism. In addition to safeguarding its culture and deep-rooted traditional values, tourism provides a way to increase employment opportunities as well as increase the foreign exchange within the country. There are many open research problems arising in the domain, which need the attention of researchers. City traffic management is one among the major concern for cities around the world. Scheduling dynamic travel plans for tourists with crowd and traffic awareness has high scope for research. In this paper, a system is proposed which connects the vehicles to a centralized sink for getting the optimal routes. Route scheduling is done based on a prediction model. Different parameters were collected from the environment that includes crowd, traffic, and schedule of other vehicles. The system has modules like static nodes, mobile nodes, host nodes, and sink node for the control and management. Selection of path and protocol is a primary strategy to design any VANET systems. Hence, performance analysis of routing protocols for the proposed system is done as a major step in selection of protocols. Packet delivery ratio, jitter, and throughput are common measures used for the comparison of protocols. [ABSTRACT FROM AUTHOR]

Wireless body area network (WBAN) routing protocols are primarily designed for improvement of network performance parameters such as network lifetime, throughput and latency. However, these designs do not take into account the health hazards posed due to WBAN radiation. The focus of implementing IEEE 802.15.6 standards is to develop an energy-efficient, reliable and health-conscious wireless communication system around human body. This paper presents the implementation of a clustering-based routing protocol for WBAN that targets in achieving overall optimization of WBAN performance parameters including network lifetime, throughput, latency, node signal power and specific absorption rate (SAR) of human body for emf radiation. The suggested protocol applies a multi-objective NSGA-II optimization heuristic for cluster formation while taking into account various IEEE 802.15.6 standard constraints. A unique chromosome structure has been proposed for NSGA-II population in which each chromosome represents a random network topology for determining the node clusters, cluster heads and node transmission power. Furthermore, three system-level models for conducting multi-objective fitness evaluation of each chromosome have been proposed. These models predict the global transmission energy consumption; the average received signal strength (RSSI) and end to end network latency respectively. The developed NSGA-II model evolves into a non-dominated set of Pareto-optimal network topologies that renders the desired objectives of minimization of network energy consumption and network latency besides maximization of average RSSI. Enhancement in RSSI further leads to a tremendous improvement in the throughput rate. The node transmission power specifications of Pareto-optimal network topologies meet the standard SAR constraints too. The performance results shows that the suggested protocol strictly meets IEEE 802.15.6 compliance. [ABSTRACT FROM AUTHOR]