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In the evolving landscape of the Internet of Things (IoT), Mobile Wireless Sensor Networks (MWSN) play a pivotal role, particularly in dynamic environments requiring mobile sensing capabilities. A primary challenge in MWSNs is achieving accurate node positioning with minimal energy consumption, as these networks often consist of battery-powered, mobile sensors where energy replenishment is difficult. This paper addresses the critical problem of energy-efficient node localization in MWSNs. We propose a novel positioning approach leveraging Cooperative Virtual Array (CVA) technology, which strategically utilizes the mobility of nodes to enhance positioning accuracy while conservatively using energy resources. The methodology revolves around optimizing the number of transceiver nodes, considering factors such as node moving speed, total energy consumption, and positioning errors. Central to our approach is the Signal Arrival and Interaction (SAI) algorithm, an innovative technique devised for efficient and precise mobile node localization, replacing traditional Time of Arrival (ToA) methods. Our simulations, conducted under various scenarios, demonstrate the significant advantages of the CVA-based positioning algorithm. Results show a marked reduction in energy consumption and robust performance in mobile node scenarios. Key findings include substantial improvements in localization accuracy and energy efficiency, highlighting the potential of our approach in enhancing the operational sustainability of MWSNs. The implications of this research are far-reaching for IoT applications, particularly those involving mobile sensors, such as in smart cities, industrial monitoring, and disaster management. By introducing a novel, energy-efficient positioning method, our work contributes to the advancement of MWSN technology, offering a sustainable solution to the challenge of mobile node localization. [ABSTRACT FROM AUTHOR]

In the evolving landscape of the Internet of Things (IoT), Mobile Wireless Sensor Networks (MWSN) play a pivotal role, particularly in dynamic environments requiring mobile sensing capabilities. A primary challenge in MWSNs is achieving accurate node positioning with minimal energy consumption, as these networks often consist of battery-powered, mobile sensors where energy replenishment is difficult. This paper addresses the critical problem of energy-efficient node localization in MWSNs. We propose a novel positioning approach leveraging Cooperative Virtual Array (CVA) technology, which strategically utilizes the mobility of nodes to enhance positioning accuracy while conservatively using energy resources. The methodology revolves around optimizing the number of transceiver nodes, considering factors such as node moving speed, total energy consumption, and positioning errors. Central to our approach is the Signal Arrival and Interaction (SAI) algorithm, an innovative technique devised for efficient and precise mobile node localization, replacing traditional Time of Arrival (ToA) methods. Our simulations, conducted under various scenarios, demonstrate the significant advantages of the CVA-based positioning algorithm. Results show a marked reduction in energy consumption and robust performance in mobile node scenarios. Key findings include substantial improvements in localization accuracy and energy efficiency, highlighting the potential of our approach in enhancing the operational sustainability of MWSNs. The implications of this research are far-reaching for IoT applications, particularly those involving mobile sensors, such as in smart cities, industrial monitoring, and disaster management. By introducing a novel, energy-efficient positioning method, our work contributes to the advancement of MWSN technology, offering a sustainable solution to the challenge of mobile node localization.

The Mobile Wireless Sensor Network (MWSN) is a new technology that has a variety of applications, such as traffic monitoring, wildlife monitoring, military surveillance, and so on. It enables sensor nodes to move freely and communicate with one another without the need for a fixed infrastructure. Energy conservation is one of the major concerns in mobile WSN because of the high packet delivery ratio, high computing power, short battery life, low throughput, high packet dropping ratio, high routing packet overhead, and high energy consumption. Congestion is also a serious issue for communication networks. It faces difficulties due to node buffer overflow, packet collision, transmission channel contention, a transmission channel with dynamic time variation, and transmission rate. Therefore, this review analyzes energy conservation and congestion control techniques in mobile WSN based on various categories. Initially, the energy conservation-based techniques are classified based on their network structure, clustering, and routing techniques, whereas the congestion control techniques are classified as queue-based, supervised learning-based, resource-based, and priority-based techniques. The nature of these techniques and their advantages and disadvantages are discussed. Furthermore, the software tools and evaluation metrics used in the existing techniques are also identified. Finally, the open challenges that need to be considered in future work are discussed. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) have emerged as a pivotal technology interlinked with numerous burgeoning sectors. Myriad sensor nodes, diverse in nature, constitute these networks, which are dispersed within a given environment to collect and relay pertinent data to a central station. Given the typical deployment of sensor nodes--bearing limited energy reserves and often stationed at extensive distances for prolonged periods--energy conservation becomes a paramount concern for enhancing the network's lifespan. One avenue explored to address this challenge involves the clustering of sensor nodes within the network. This study introduces a dynamic approach for clustering nodes in WSNs, designed to accommodate mobile nodes. The approach leverages an enhanced version of the k-means algorithm in tandem with a novel cluster head selection method, capable of clustering even moving nodes. This strategy proposes an innovative solution to select cluster heads, aiming to reduce the energy consumption of nodes and augment reliability during data transmission within sensor networks. [ABSTRACT FROM AUTHOR]

The target tracking algorithm of mobile wireless sensor networks involves target motion trend prediction and subsequent node guidance. This study aims to solve the problems of global consistency of node information and significant errors in forecasting fast-moving targets’ trajectories through traditional distributed tracking methods in sensor networks. Initially, the average consistency algorithm is used to average the local measurements of each node to achieve global consistency. Then, semantic moving computing of the Internet of Things calculates and analyzes the node movement to support the subsequent movement guidance of nodes and target movement prediction. Finally, the simulation experiment is carried out to evaluate the commonly used target trajectory prediction model. The simulation results show that the node movement algorithm by average consistency can effectively improve the positioning accuracy of the network for moving targets. Besides, the positioning error decreases with the increase of the sensing radius R, the number of moving nodes nm, and the total number of nodes ns deployed in a particular range in a two-dimensional (2D) space. The positioning error after node movement in 2D space is about 20%–30%R lower than that in a static state. After node movement in a three-dimensional (3D) space, the positioning error is about 40%–50%R lower than in a dormant state. When the target moves at a speed greater than 7m/s, the consistency-based moving computing algorithm’s target loss rate and tracking errors are about 0~10% and 1.5%~2% lower than the target tracking algorithm via Kalman Filter. Therefore, the algorithm reported here can precisely track the high-speed moving target. The existing research on point target tracking has problems of insufficient accuracy and robustness. The algorithm proposed here has stronger robustness, reduced data error in multi-node, and more flexible node movements, providing a reference for the subsequent research on distributed point target tracking.

The security of mobile wireless sensor networks has captivated extensive attention of researchers because of their wide range of applications and vulnerability to attacks caused by malware. In this paper, we investigate a delayed malware propagation model on mobile wireless sensor network incorporating nonlinear incidence rate, logistic growth rate and recovery rate. Local asymptotic stability of the endemic equilibrium and existence of Hopf bifurcation at crucial value of the time delay are analyzed. Then, properties of Hopf bifurcation are explored. Specifically, global exponential stability is investigated via linear matrix inequality. An example is presented finally to underline the effectiveness of findings in our paper numerically and graphically. [ABSTRACT FROM AUTHOR]

In recent years, Wireless Sensor Network (WSN) has been used for several applications and various roles like information gathering, monitoring data, transmitting data, etc. However, the key drawback behind this WSN is energy consumption. In WSN, some nodes have been consumed more energy because of malicious events like replication nodes. So, the replication node must be predicted in the initial stage to avoid packet drop and minimize energy consumption. So, this current research proposed a novel Whale-based Node Identity Verification (WbNIV) for detecting replication nodes in the Mobile Wireless Sensor Network. Moreover, the fitness function of the whale is used to identify each node's energy level and for exact replication node detection. Initially, the required numbers of nodes are designed then the details of a node are stored in WbNIV memory. During the monitoring and prediction process, the replication node in the WSN is identified by analyzing the details and behavior of the node. Finally, the proposed WbNIV has gained 98.89% replication node prediction accuracy, recorded the maximum packet drop as 12.8%, and reduced communication delay to 3 s, which is relatively better than the existing models. Thus, it has reduced power consumption up to 30% compared to the existing models. It has also improved the detection accuracy up to 5% than the compared models and has reduced the packet drop up to 10% compared to conventional approaches. [ABSTRACT FROM AUTHOR]

Formation control is an important part of any system that utilizes multiple mobile agents to achieve its particular goals. One of those applications is the mobile wireless network sensor. This field has become increasingly more popular in recent times due to the advancement of technology, especially in the fields of miniaturization and telecommunications. The main problem of this research is the relatively untested sensing capability of a mobile wireless sensor network in an operating area that has distributed and/or multiple locations of high interest. The purpose of this research is to discover the compatibility of a multiple-agent coverage control system with several examples of interest functions that have multiple and/or distributed points of global maximum value in order to explore more thoroughly the performance of a given system in a varying environments. [ABSTRACT FROM AUTHOR]

The reliable distributed monitoring system provides the real-time video observation from the power cable tunnels when the preinstalled communication system is disabled in an emergency. The spherical robotic prototypes are designed as the sensor node based on the analysis of the robot dynamic model. A novel self-constructed mobile wireless sensor network (MWSN) is proposed to realize the communication and positioning functions through the fusion of the Ad-Hoc and ultra-wideband (UWB) approaches. The Ad-Hoc network consists of multiple robot nodes as sensor carriers and relay stations to transmit large amounts of data from the accident scene to the monitoring terminal. The UWB network consists of UWB tags and bases on each node and implements the leader-follower (LF) strategy to create the robot formation. In order to maximize the monitoring area and maintain the reliability of the network, the traditional LF strategy is optimized based on the N-X algorithm subjected to the constraints of node number, Ad-Hoc communication and UWB positioning range, and the power tunnel boundaries. A self-constructed MWSN consisting of five robotic nodes ( $N=5$ ) is capable of covering 40 m of power cable tunnel, when the value of $X$ is selected as 3. The network failure probability reduces from 73.5% ( $X=0$ ) to 0.2% ( $X=3$ ) when the malfunction probability of sensor node is 23.3% due to the accident condition in the tunnel. Finally, the simulation and experimental results show that the optimized LF algorithm increases 20.2% coverage of the network in the curve formation. The network transmits a monitoring video streaming with a $320\times240$ pixel resolution and a delay less than 150 ms. The real-time video observation from the accident scene is significant to formulate the emergency countermeasure and investigate the direct cause of the accident.

Wireless sensor networks have played an important role in many applications, where sensors in the network can automatically collect and transmit information in an environment without much human maintenance. To enhance the adaptability of sensors, people produce mobile wireless sensors through fixing wireless sensors on mobile vehicles or robots. The same as static wireless sensors, since the energy of mobile wireless sensors is still supplied by the battery, their energy management has a great impact on their lifetime. Different with static wireless sensors, the mobility of mobile wireless sensors gives us a new perspective to achieve the efficient energy management. In this paper, a decentralized self-adaptive approach is proposed for mobile wireless sensors, which enables sensors in a mobile wireless sensor network to adapt their locations according to the information transmission regularity in the network so as to reduce their energy consumption for the information transmission. The experimental results indicate that after employed the proposed approach to adapt locations, the energy consumption for the information transmission of sensors in a mobile wireless sensor network can be greatly reduced and their lifetime is extended.

Mobile Wireless Sensor Network (MWSN) typically created with no major infrastructure. Thus, they are moderately defenseless to various mischievous attacks; as a result, attack detection is a significant problem in MWSN. The cryptographic technique can avoid several attacks. A mischievous node can simply disrupt a route in the communication path. However, an attacker captures sensor nodes, evokes their cryptanalytic key, and modifies their code to behave mischievously. Hence, the mischievous node detection is a significant problem in the network. To solve these problems, in this paper, Swarm Intellect Optimization Technique based mischievous detection and improve Authentication in MWSN. In this approach, the minimum distance nodes are formed the clusters. Then cluster Heads (CHs) are selected based on the node weight. Observing forwarding behavior, Observing Great energy Communication and Observing fake route ads parameters are decided the MWSN Mischievous nodes. The presented approach is validated by a network simulator. Simulation results shows the SIOT approach detect the mischievous nodes efficiently. [ABSTRACT FROM AUTHOR]

In this work, we study the problem of jamming avoidance for ensuring quality-of-service (QoS) in terms of the network lifetime and overhead in wireless sensor networks (WSNs). We propose a mobility model using Single-Leader-Multiple-Followers Stackelberg game theory to avoid the jamming affected region. In the proposed model, the centralized unit (CU) identifies the jamming affected region based on the locations of the affected nodes and acts as the leader. On the other hand, the jamming affected nodes act as followers and decide the mobility pattern, including the angle of movement, while minimizing the energy consumption and delay in packet delivery. A scheme, named M-JAW, for ensuring QoS, while avoiding jammers in WSNs, is proposed using the stated game-theoretic mobility model. Using M-JAW, the energy consumption of the overall network reduces by up to $\text{20.36}\%$ , and the network overload reduces by 44.13– $\text{50.12}\%$ , which, in turn, increases the lifetime of WSNs. [ABSTRACT FROM AUTHOR]

Node replication attack is one of the well-known and dangerous attacks against Wireless Sensor Networks (WSNs) in which adversary enters the network, searches randomly and captures one or multiple normal nodes. Adversary extracts data and keying materials of the captured node and generates several copies of that node and deploys them in the network. In this paper, a novel algorithm using watchdog nodes is proposed to detect replica nodes in mobile WSNs. The main idea of the proposed algorithm is inspired by maximum predefined speed for sensor nodes and using time-location tags by the watchdog nodes to detect replica nodes. Watchdog nodes collaborate to measure sensor nodes' speed in the environment and if they find that a node moves faster than a predefined threshold, they mark it as a malicious node, because such replica node in different regions of the network is moving faster than usual in different regions of the network. The proposed algorithm is implemented by J-SIM simulator and its performance is evaluated in terms of false detection and true detection rates through some experiments. Experiment results show that the proposed algorithm is able to detect 100% of replica nodes, while the false detection rate is less than 0.5%. [ABSTRACT FROM AUTHOR]

We study the feasibility of extending the lifetime of a wireless sensor network by exploiting mobility. In our system, a small percentage of network nodes are autonomously mobile, allowing them to move in search of energy, recharge, and delivery energy to immobile, energy-depleted nodes. We term this approach energy harvesting. We characterize the problem of uneven energy consumption, suggest energy harvesting as a possible solution, and provide a simple analytical framework to evaluate energy consumption and our scheme. Data from initial feasibility experiments using energy harvesting show promising results.

Abstract Controlling the transmission power level in a mobile wireless sensor network is an essential process to improve the energy efficiency and quality of service (QoS) at each wireless node. To achieve this goal, we propose to evaluate the QoS by an estimation of the signal-to-interference noise ratio (SINR) according to the IEEE 802.15.4 standard. For this purpose, the received signal strength indicator per packet (RSSIp), and general received signal strength indicator (RSSIg) metrics are considered in this research work followed by a filtering stage to reduce the variability in the SINR estimation. In addition, this research work aims to evaluate different dynamic power control algorithms through an experimental test-bed, where the wireless nodes are in motion. A comparative analysis is presented of five distributed power control algorithms: fixed-step, Foschini-Miljanic, proportional-integral-derivative control, variable structure control, and water-filling control. Moreover, a new distributed power control technique is proposed for mobile wireless sensor networks: modified fixed-step (MFS). All the power allocation algorithms use the tracking error between the estimated and objective SINRs as the driving mechanism to adjust the transmission power. In general, the results show that a dynamic power allocation scheme not only enables the efficient use of the battery, extending its lifetime, but also it is able to achieve the desired QoS despite multiple interference and mobility of the nodes in the network. Furthermore, the results of the experimental evaluation indicate that the modified fixed-step algorithm has the best performance as a function of the reference tracking of the QoS and power consumption. [ABSTRACT FROM AUTHOR]

To avoid premature failure due to excessive energy consumption of some nodes in the network, the node energy consumption problem was considered. Network life was maximized. For the problem of node energy consumption, multiple methods such as the shortest path method, optimization method, and power control method were used to solve the problem of optimization of the survival time of the wireless sensor network in different scenarios and improve the network lifetime. The results showed that the subgradient algorithm could balance the node energy consumption and the number of neighbor nodes and extend the maximum network lifetime. Therefore, under certain conditions, the algorithm is better than the algorithm using fixed transmission power. [ABSTRACT FROM AUTHOR]

Blockchain has proven in sensor networks as a distributed solution for transparent and secure storage, which allows its application in mobile wireless sensor networks (MWSNs). The consensus mechanism, an essential aspect of blockchain technology, must concern the high mobility, resource-constrained nature, and weak physical defenses of sensor nodes in MWSNs. To secure MWSN data storage in clustered communication, we design a proof-of-information (PoI) variant for fair miner campaigning via the amount of valid data generated from environmental information, including a dynamic adjustment of the data volume threshold to detect malicious nodes and prevent them from misreporting information. Additionally, we introduce a filtering mechanism through the dynamic integrated trust (DIt) of nodes, which integrates the trust evaluation of peer nodes across the network combining objective performance to prevent malicious nodes from infiltrating the final consensus group. The multi-level filtering technique improves the campaign fairness while isolating malicious nodes, ensuring complexity-sensitive PBFT algorithm efficiency in large-scale networks. Simulation results show that the scheme isolates 90% of the malicious nodes and screens 20% of members to produce a smaller final consensus group. Further analysis of impacts on the performance considering network topology and mobility patterns and comparisons of the relevant solutions are presented. • Design a consensus scheme for clustered MWSN application scenarios. • Joint PoI variants and dynamic integrated trust schemes to construct the final consensus group. • Dynamic valid data volume threshold mechanism isolates malicious nodes that inject false information. • The consensus group is smaller and selects more reputable miners. • Results demonstrate the security of the program and the fairness of the miners' campaign. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are often deployed in hostile environments, where an adversary can physically capture some of the sensor nodes. The adversary collects all the nodes’ important credentials and subsequently replicate the nodes, which may expose the network to a number of other security attacks, and eventually compromise the entire network. This harmful attack where a single or more nodes illegitimately claims an identity as replicas is known as the node replication attack. The problem of node replication attack can be further aggravated due to the mobile nature in WSN. In this paper, we propose an extended version of multi-level replica detection technique built on Danger Theory (DT), which utilizes a hybrid approach (centralized and distributed) to shield the mobile wireless sensor networks (MWSNs) from clone attacks. The danger theory concept depends on a multi-level of detections; first stage (highlights the danger zone (DZ) by checking the abnormal behavior of mobile nodes), second stage (battery check and random number) and third stage (inform about replica to other networks). The DT method performance is highlighted through security parameters such as false negative, energy, detection time, communication overhead and delay in detection. The proposed approach also demonstrates that the hybrid DT method is capable and successful in detecting and mitigating any malicious activities initiated by the replica. Nowadays, crimes are vastly increasing and it is crucial to modify the systems accordingly. Indeed, it is understood that the communication needs to be secured by keen observation at each level of detection. The simulation results show that the proposed approach overcomes the weaknesses of the previous and existing centralized and distributed approaches and enhances the performance of MWSN in terms of communication and memory overhead.

Thanks to the rapidly development of optimization algorithm, more energy can be saved in the communication system when executing an application. In recent years, allocating limited resources in a cooperative manner to maximize energy efficiency in emerging sensor networks has attracted a lot of attention. In this paper, a one-layer projection neural network subject to linear equalities and bound constraints is introduced and applied in mobile wireless sensor network to make it energy-efficient by reasonably allocating local and remote data sizes when processing an application within a certain period of time. Firstly, an optimal partition to minimize the total energy consumption of the local and helper sensor nodes is proposed. Then, the neural network model is described and the optimality and convergence of the proposed model are analyzed. Finally, some simulation results are given to show that the proposed algorithm is very effective to solve the energy efficient cooperative computing. [ABSTRACT FROM AUTHOR]

A mobile wireless sensor network (MWSN) consists of many sensor nodes, which can move from one position to another and gather data from the environment, and such nodes are coordinated with the support of a sink node. In recent years, the mobility behavior of sensor nodes present in wireless sensor networks is used to form effective clustering and to perform cluster-based routing. Virtual force is an important phenomenon in sensor nodes, which is used to model the mobility behavior. Production rules that use spatiotemporal constraints are able to make more accurate decisions on mobility speed, mobility area, and the required time. Routing in MWSNs under the mobility scenario will provide better performance if virtual force-based mobility modeling is used to form clusters. In this paper, an intelligent routing algorithm called virtual force-based intelligent clustering for energy-efficient routing in MWSNs has been proposed for effective and energy-efficient cluster-based routing of data packets collected by mobile sensor nodes in a MWSN. This algorithm uses attractive and repulsive forces for finding the cluster members. Moreover, spatiotemporal constraints are used in the form of rules for clustering, reclustering, and cluster head election and to perform routing through the cluster heads using intelligent rules. The main advantage of the proposed algorithm is that it increases the network lifetime and packet delivery ratio. Moreover, it reduces the delay and the energy consumption. [ABSTRACT FROM AUTHOR]

Time synchronization is a crucial service task in a distributed network. Although several works are reported in routing and medium access control of mobile wireless sensor networks (MWSNs), or for navigation in a collaborative swarm of robots, prior time synchronization is stated as one of the prior requirement. In this paper, we study the problem of time synchronization over a wireless network for a swarm robotic system. We propose a fully decentralized, energy efficient framework for global synchronization of swarm of robots. The major contribution of this work is in terms of proposing a scalable, topology independent, mobility-assisted time synchronization framework with resynchronization interval in the order of several minutes (tested up to 10 min) which we believe will accelerate development of swarm robotic systems and mobile wireless sensor networks for several human-friendly real-world applications. The proposed framework which implements time synchronization in two phases, (1) One-way time offset compensation and (2) Relative skew fingerprinting based frequency offset compensation, is flexible and can be tuned easily to suit several application scenarios. Another unique characteristic of the framework is that it utilizes only one-way messages for the time offset and frequency offset compensation. We also demonstrate that the protocol scales very well for multi-hop scenarios and that bounded synchronization error across the network can be achieved using the framework. Analysis on the suitability of our framework for dynamic environments is also presented. We also present a fair comparative analysis of our work with the predictive protocols based on techniques such as Linear regression, Linear prediction and Kalman filter and consensus based synchronization proposed for static networks. The results and analysis presented here are derived from the analytical and empirical study on mobile nodes/robots spread over a duration of 5 months. [ABSTRACT FROM AUTHOR]

Clustered WSN (Wireless Sensor Networks) is a hierarchical network structure that conserves energy by distributing the task of sensing and data transfer to destination among the non-CH (Cluster-Head) and CH (Cluster Head) node in a cluster. In clustered MWSN (Mobile Wireless Sensor Network), cluster maintenance to increase at a reception at the destination during communication operation is difficult due to the movement of CHs and non-CH nodes in and out of the cluster. To conserve energy and increased data transfer to the destination, it is necessary to find the duration after which sensor node's role should be changed from CH to non-CH and vice-versa. In this paper, we have proposed an energy independent round time scheme to identify the duration after which re-clustering procedure should be invoked for changing roles of sensor nodes as CHs and associated nodes to conserve energy and increased data delivery. This depends on the dissemination interval of the sensor nodes rather than sensor node's energy. We have also provided a complete analytical estimate of network energy consumption with energy consumed in every phase of a around. [ABSTRACT FROM AUTHOR]

Selective forwarding attacks in mobile wireless sensor networks are difficult to detect because they selectively delete packets. Such attacks are more dangerous than selective forwarding attacks in wireless sensor networks because it is difficult to detect a selective forwarding attack that occurs on sensor nodes with high mobility. In order to detect such attacks, a fog computing-based selective forwarding attack detection technique has been proposed. However, in the ad hoc on-demand distance vector (AODV) routing scheme using a single path, all packets are dropped until a selective forwarding attack is detected. In addition, energy consumption for path re-setting is significant because sensor nodes move frequently. To solve this problem, we propose a selective forwarding attack detection method using an ad hoc on-demand multipath distance vector (AOMDV) routing technique. The proposed scheme increases the packet transmission probability to the BS and increases the energy efficiency of the sensor network. Experiments with the proposed method show that the energy efficiency of the sensor network is improved by about 10%. [ABSTRACT FROM AUTHOR]