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Internet Protocol version 6 (IPv6) address configuration is needed to meet the needs of current portable devices and wearable applications, where each device needs its own unique identification number. High complexity in Wireless Sensor Network (WSN) and Internet of Things (IoT) environments has increased challenges, such as low energy consumption and high overhead in IPv6 address configuration. The proposed IPv6 generation is based on a hybrid mathematical approach that retains the IP address's confidentiality and prevents Denial of Service (DoS) attacks from new and existing nodes in the network. In this paper, the proposed hybrid protocol for DoS attacks from new and existing nodes is analyzed. It is evident from the results that the rate of successful configuration, overhead, and energy consumption is found to be better than the existing approach, namely, Programming Protocol-independent Packet Processors Duplicate Address Detection (P4DAD), match prevention technique, etc. • Focuses on IPv6 using a hybrid Duplicate Address Detection (DAD). • Reduces the energy consumption of the IPv6 as compared to P4DAD, etc. • Reduces the long wait time compared to EUI-64. • ASR is investigated for the Hybrid DAD under three different scenarios [ABSTRACT FROM AUTHOR]

Topology control in Underwater Wireless Sensor Networks (UWSNs) has been an active area of research owing to unique challenges an underwater environment poses. Node mobility due to water currents creates problems in localization and data transfer. In this paper, we propose an energy efficient topology control for mobile UWSNs using Expectation Maximization (EM) and Vickrey–Clarke–Groves (VCG) Auction mechanism. In the first stage, followed by a water current induced topology disturbance, the designated cluster head runs the EM algorithm to find similar sensor nodes in its proximity. In the second stage, cluster head runs VCG auction mechanism to compensate sensor nodes for costs incurred during data transfer. This ensures seamless data transmission between sensor nodes of heterogeneous ownership leading to higher energy efficiency. Simulations present higher energy efficiency of the network post EM and VCG steps. Comparison with existing protocols demonstrates superior performance of the protocol proposed in this paper. [Display omitted] • Node mobility in underwater sensor networks disturbs network topology. • Extant game theory-based protocols for topology control are not flexible enough. • Our protocol uses Expectation Maximization for soft clustering of sensor nodes. • Sensor nodes are compensated for data transfer through an auction mechanism. • Our protocol gives better results in simulations-based comparisons with extant protocols. [ABSTRACT FROM AUTHOR]

This paper presents an energy-efficient technique for resolving intra-cluster contentions in cluster-based wireless sensor networks. The proposed technique, bit map – binary countdown (BM–BCD), provides collision-free medium access by exchanging short signal tones between the head node and member nodes of the cluster. The BM–BCD improves existing tone-based contention resolution schemes in the following two aspects. Firstly, BM–BCD overcomes the hidden terminal problem by actively involving head node into the contention resolution process. Secondly, BM–BCD introduces a novel group-splitting algorithm which improves energy efficiency of member nodes by spreading the contention resolution over all available elimination rounds. The paper also introduces a simple intra-cluster MAC protocol, named STAR–TONE, which incorporates the proposed BM–BCD, and provides an analytical model for dimensioning main protocol parameters. Our analysis, verified by simulations, demonstrates that BM–BCD reduces the power consumption during contention for up to 44.5% compared to the baseline countdown protocol under bursty traffic conditions. [ABSTRACT FROM AUTHOR]

Highlights • A Low complexity, energy efficient image compression suitable for WSNs. • The integration of DTT in lossy image compression. • A ROI coding for WSNs preserving energy and improving quality. • A considerable reduction in energy consumption and data transferred. • Helping development of smart surveillance systems using low-power cameras. Abstract Reducing the algorithmic complexity of image compression techniques is a major challenge in wireless image sensor networks (WISNs). Many image compression standards, such as JPEG and JPEG2000, are unsuitable for implementation in WISNs because of their high energy consumption. In this paper, a solution to this problem is proposed. It consists of a region-of-interest (ROI) based image compression using the discrete Tchebichef transform (DTT).The main idea is about compressing only the ROI instead of the whole image. The DTT is used as an alternative to the discrete cosine transform (DCT) due to its low complexity and good energy compaction. Simulation results have shown that the proposed method reduces the number of arithmetic operations, the processing/transmission energy consumption and the amount of transmitted data. The savings obtained generally exceed 50%. Furthermore, it has a competitive compression efficiency compared with the state-of-the-art image compression techniques. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

Abstract Wireless sensor networks consist of a set of connected devices deployed to report sensitive environmental data. Key management in wireless sensor networks remains a challenging issue due to the limited resource capacity of devices. Most existing solutions focus only on the key storage and updating optimization giving less attention to the mobility, which is more needed in the nowadays applications. In this paper, we propose a secure and efficient key management system with mobility support. The proposed scheme is based on hybrid key establishment to meet both the robustness and efficiency requirements. The sensor nodes can be mobile, where they could leave, rejoin their cluster, or join other ones. We incorporate lightweight techniques for sensor node integration, departure, revocation and key updating. Its efficiency is evaluated by comparison with other concurrent schemes, where it demonstrates the best results. [ABSTRACT FROM AUTHOR]

Abstract In a tree-based Wireless Sensor and Actor Network (WSAN), data acquisition can be done through a mobile actor to reduce the traffic congestion. However, packet dropping at the resource-limited (such as, buffer space and energy) intermediate nodes leads to poor data delivery and energy efficiency. In this paper, a Markov Decision Process (MDP) based buffer management mechanism has been proposed in tree-based WSAN to reduce the data delivery delay and to improve the energy efficiency. A mathematical model for a mobile actor has been presented to analyze buffer occupancy and energy consumption with real-time traffic. The state of a node is represented based on buffer levels which may change with dynamic traffic. The buffer states are analyzed at which packets will be dropped to minimize the average delivery delay and energy consumption. Extensive simulations have been performed to show the efficacy of proposed mechanism in terms of average end-to-end delay and energy consumption. [ABSTRACT FROM AUTHOR]

Exploiting sink mobility for balancing the energy dissipation of sensor nodes and preventing energy holes is a growing trend in the field of wireless sensor network (WSN). The mobile sink moves throughout the network and collects data in a single-hop fashion resulting in less energy consumption of the sensor nodes. Despite the advantage of this scheme, data forwarding to the mobile sink during an emergency situation is a major issue that should be dealt with. For efficient data delivery within the stipulated deadline, the sensor node which has sensed a delay-intolerant data needs to forward the data towards the mobile sink. In this paper, a Moore curve based trajectory of the mobile sink has been considered for efficient sink based data collection. This work is also motivated by anycast forwarding of delay sensitive data to the mobile sink before the sensed data lose its relevance, where the node follows a strict sleep-wake pattern. We have evaluated the effectiveness of the proposed trajectory based data collection scheme by simulation using MATLAB. The delay-intolerant data routing scheme (DRS) shows that the data reaches the mobile sink within the given deadline while restricting the energy dissipation of the sensor nodes to a minimum. This have been verified by extensive simulations which show that when compared to static sink, the usage of a mobile sink improves the network lifetime by almost 12%. This work has also been compared with an existing work (PMDD) to show its validity. The simulation results depict that DRS shows an improvement of about 25%–29% in terms of network lifetime. [ABSTRACT FROM AUTHOR]

In recent decades, cluster-based schemes have emerged as viable solutions for energy conservation problem in wireless sensor networks (WSN). However, most of the existing solutions incur imbalanced energy consumption and high network overheads. In addition, existing cluster-based solutions do not optimize route discovery based on the restricted resources of sensor nodes. Moreover, most of the cluster-based solutions perform periodical re-clustering for load balancing, which results in shortening network lifetime. This research paper presents a Dynamic Energy-aware Fault Tolerant Routing (DEFTR) protocol that exploits uniform-sized network partitioning based on network size and utilizes a multi-facet routing mechanism, which takes into consideration the residual energy, and position and link quality of neighbors. Furthermore, DEFTR not only offers reliable and energy efficient data routing but also supports fault tolerance. Simulation results demonstrate that DEFTR improved the network lifetime by 20.9% and throughput by 35%, also it reduced the delay by 29% and transmission cost by 46% in comparison to the existing work. [ABSTRACT FROM AUTHOR]

In recent years, resource constrained hardware makes the operating system simplicity a most crucial design criterion. The majority of research in such operating systems has focused on the reactive nature of an event-driven kernel. However, the event-based kernel may result in the latency of processing events and erroneous energy profiling. Most battery-driven wireless sensor nodes use the radio event to wake up sleeping nodes, but the radio always consumes more energy than other components during the transmission intervals. The contribution of this paper is that we present EXOS , a timer-driven operating system which can both process periodic events on time and obtain rapid responses to external signals. The system kernel can be easily ported to any other memory-constrained target platforms. EXOS is able to provide the detailed prediction of each component's energy consumption during program execution. The evaluation has demonstrated that EXOS can be practically integrated into wireless sensor networks. [ABSTRACT FROM AUTHOR]

This paper proposes a Cluster-Based Data Aggregation (CBDA) method for identifying pests in Arabica Coffee plantation using Wireless Sensor Networks (WSNs). Acoustic signals that are generated with biting sound by the pests inside stem are captured by WSN. Information regarding existence of pests is aggregated at Cluster-Head (CH) and is conveyed to base station. CH is selected using five states of each node: i-band, o-band, cluster-head request, idle and cluster-head. CH performs data aggregation with residual energy, time stamp using Kolmogorov’s zero-one law to eliminate redundancy. Simulation analysis of CBDA is compared with fast local clustering, energy-efficient reliable data aggregation technique and energy-efficient data aggregation transfer in terms of aggregation ratio, message overhead, control overhead, packet delivery ratio, algorithmic complexity, delay, energy consumption, time-out period and clustering time. The CBDA simulation results outperform compared to the corresponding techniques. [ABSTRACT FROM AUTHOR]

The Ultraviolet (UV) Non-line-of-sight (NOLS) communications are becoming a research hotspot in recent years. For wireless UV networks, there are some well-known existing issues such as network connectivity, power control and channel assignment. In this paper, a Fast Power Control and Channel Assignment scheme (FPCCA) is proposed to reduce interference and save energy. Firstly, the FPCCA is compared with the traditional channel assignment which without power control. It is proved that the approach of FPCCA can save energy more than 10%. Then, the FPCCA is both applied in the UV and Wireless Mesh Networks (WMN). The performance of FPCCA with different angles and network traffic loads is simulated and analyzed. When the traffic load is fixed, the performance metrics of FPCCA in UV are better than that in WMN. Meanwhile, the FPCCA not only ensures the quickness and accuracy of channel assignment, but also saves energy and improves the throughput. [ABSTRACT FROM AUTHOR]

Wireless sensor networks comprise nodes with limited power supply. The dense deployment of nodes on a terrain for monitoring the environment causes contention in wireless channels that leads to interference and high energy consumption. The topology of the network changes frequently because of failure of nodes, addition of new nodes, and channel fading. Topology control is an important technique for reducing energy consumption, interference, and maintaining connectivity in the network. This paper provides a survey on state scheduling-based topology control techniques for unattended wireless sensor networks. Topology control algorithms for both flat and hierarchical networks are discussed. The algorithms are further categorized according to the key parameters used for state scheduling. The advantages, disadvantages, and results of the algorithms are tabulated. In addition, we highlight future research directions in designing state scheduling-based topology control algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes two architectures, including an Opportunistic Large Array Concentric Routing Algorithm with Geographic Relay Nodes (OLACRA-GRN) architecture, and an Opportunistic Large Array Concentric Routing Algorithm with Relay Nodes (OLACRA-RN) architecture. First, the OLACRA-GRN architecture with the geographic information of relay nodes reduces node energy consumption and finds the optimum number of relay nodes to forward the data; an analysis of the characteristics of the energy model is also presented. Besides, the OLACRA-RN architecture without the geographic information of relay nodes is proposed, which can find the number layer of concentric circles in the sensing field. The optimal number layer of concentric circles is calculated according to the distance between the sink and field boundary. Simulation results show that our proposed OLACRA-GRN and OLACRA-RN architectures can effectively reduce node energy consumption more than Opportunistic Large Array Concentric Routing Algorithm (OLACRA) architecture. [ABSTRACT FROM AUTHOR]

• Whether it is a homogeneous WSNs or a heterogeneous WSNs, the cluster head selection scheme is extremely important and will affect the performance of the entire network. • The traditional LEACH clustering scheme and DEEC clustering scheme only consider the remaining energy of the node or the initial energy of the node when selecting the cluster head. This paper comprehensively considers the remaining energy of the node, the relative density of the node, and the relative distance between the node and the base station to generate the probability of the node being elected as the cluster head. • This paper considers an improved low-energy dynamic clustering scheme based on fuzzy logic to balance the energy consumption of the network and prolong the lifetime of network. • A low-power dynamic clustering scheme based on fuzzy logic provides an effective method for multi-layer clustering networks. It is inconvenient to replace the sensor nodes with limited energy in wireless sensor networks (WSNs) when they are deployed in remote or dangerous monitoring area, that makes energy consumption become the main issue to limit wide application of WSNs. Existing clustering methods only consider heterogeneity of node energy for head selection, irrespective of differences in network structure and node density. Fuzzy logic scheme is applied in this paper to consider multiple factors clustering with the purpose of prolonging network lifetime. In addition to the initial energy, the relative density of nodes and the relative distance between nodes and base station are considered to select the cluster head dynamically. Experimental results have demonstrated that the proposed dynamic clustering scheme can balance the energy consumption of the nodes in both homogeneous and heterogeneous networks, effectively prolong the lifetime of the network, maintain the accuracy of data aggregation. [Display omitted] [ABSTRACT FROM AUTHOR]

Due to strict inherent limitations in terms of processing power, storage and bandwidth, data processing is a challenge in the wireless multimedia sensor networks. In this paper, we provide an energy-saving audio data compression technique for such a network using lifting based partial discrete wavelet transform (PDWT). Unlike existing implementation of such a lifting based PDWT, we exploit both spatial and temporal correlation of data together, with an objective to save energy while achieving acceptable signal-to-noise ratio (SNR). We subsequently design a tree based routing scheme and an encoding scheme to be used with the proposed compression scheme with a target to reduce energy further. Finally, the design feasibility along with simulation results, including statistical analysis is presented to evaluate efficacy of the scheme in terms of two conflicting parameters viz. energy consumption and SNR. The comparative results confirm our scheme’s supremacy over a few competing schemes. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are formed by a large number of sensor nodes which are commonly known as motes. In the past few years, several reliable, congestion controlled and energy efficient transport layer protocols in wireless sensor networks have been developed and proposed in the literature. In this paper, we have presented a hybrid and dynamic reliable transport protocol which provides the mechanism to dynamically assign the timing parameters to the nodes as well as enhance the protocol performance by using a hybrid Acknowledgement/Negative Acknowledgement scheme. The performance of proposed protocol is tested under TinyOS Simulator varying different parameters and protocol settings and found that proposed protocol is able to program all the nodes when given proper pump/fetch ratios, is able to solve the booting sensor nodes problem by being able to wait till all the nodes finished booting and solves the all-packets-lost problem by acknowledging the receipt of its first packet delivered that is the inform message. [ABSTRACT FROM AUTHOR]

In a wireless sensor network where sensors are arranged into a flat topology, sensors near the sink consume much more energy than sensors at the boundary of the network. Sensors near the sink relay many packets than far away sensors to the sink. After these sensors expire, energy holes are created near the sink. Therefore, other sensors cannot reach to the sink and the network becomes disconnected. In this paper, we propose some strategies that can balance energy consumption of the deployed sensors and reduce energy holes from the network by balancing the communication load as equally as possible. We performed extensive experiments on the proposed algorithm using various network scenarios and compared it with other existing algorithms. The experimental results verify the effectiveness and feasibility of the proposed work in terms of network lifetime, energy consumption, and other important network parameters. [ABSTRACT FROM AUTHOR]

The efficiency of interconnect network-on-chip (NoC) design significantly affects the thermal and energy-consumption problems. The wireless interconnect NoC (WiNoC) design provides a promising NoC architecture for multicast in chip multiprocessor (CMP) as compared with fully wired NoC. However, wireless routers (WRs) cost a larger area size as well as larger energy consumption than wired routers do. In this paper, we study a 2-tier wire–wireless hybrid NoC (WHNoC) architecture in an ( NS ) -processing-element (PE) CMP where N PEs use wires to connect with a wireless-enabled hub forming a star topology subnet and S wireless-enabled hubs form a fully connected WiNoC, named sWHNoC. We first investigate the performance of slotted p -persistent carrier sense multiple access (CSMA) protocol on the fully connected WiNoC. To greatly reduce the energy consumption of WiNoC, we propose an energy-proportional multicast scheme (EMS) by using a power-gating (PG) technique to switch off non-member WRs during the period of multicast transmission. A comprehensive comparison of the star-ring WHNoC, the mesh-based WHNoC, and the proposed sWHNoC is studied. Detailed analyses of the energy consumption of sWHNoC are presented. The correctness of analysis is validated by using Orion 2.0 simulator. Based on our investigation, the sWHNoC with the slotted p -persistent CSMA and the EMS will significantly reduce the energy consumption as well as the transmission latency in CMP. [ABSTRACT FROM AUTHOR]

Wireless multimedia sensor networks (WMSNs) are capable of retrieving audio, image and video data in addition to scalar sensor data. The lifetime of these networks is mainly dependent on the communication and computational energy consumption of the node. In this paper, compressed sensing (CS)-based image transmission is proposed to reduce the energy consumption considerably with acceptable image quality. A unique encoding algorithm is formulated for the CS measurements attained with the Bernoulli measurement matrix. The proposed CS method produces better results at a lower sparsity range. Experimental analysis is performed using the Atmega 128 processor of Mica2 to compute the execution time and energy consumption in the hardware platform. The proposed CS method has a considerable reduction in energy consumption and better image quality than the conventional CS method. The simulation results show the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

The main constraint of wireless sensor networks (WSNs) is the limited and generally irreplaceable power source of the sensor nodes. Therefore, designing energy saving routing algorithm is one of the most focused research issues. In this paper, we propose an energy aware routing algorithm for cluster based WSNs. The algorithm is based on a clever strategy of cluster head (CH) selection, residual energy of the CHs and the intra-cluster distance for cluster formation. To facilitate data routing, a directed virtual backbone of CHs is constructed which is rooted at the sink. The proposed algorithm is also shown to balance energy consumption of the CHs during data routing process. We prove that the algorithm achieves constant message and linear time complexity. We test the proposed algorithm extensively. The experimental results show that the algorithm outperforms other existing algorithms in terms of network lifetime, energy consumption and other parameters. [ABSTRACT FROM AUTHOR]

The number of wireless sensor network deployments for real-life applications has rapidly increased in recent years. However, power consumption is a critical problem affecting the lifetime of wireless sensor networks (WSNs). A number of techniques have been proposed to solve this power problem. Among the proposed techniques, data compression scheme is one that can be used to reduce the volume of data to be transmitted. This paper therefore proposes a fast and efficient lossless adaptive compression scheme (FELACS) for WSNs. FELACS was proposed to enable a fast and low memory compression algorithm for WSNs. FELACS generates its coding tables on the fly and compresses data very fast. FELACS is lightweight, robust to packet losses and has very low complexity. FELACS achieved compression rates of 4.11 bits per sample. In addition, it achieved power savings up to 70.61% using the real-world test datasets. [ABSTRACT FROM AUTHOR]

Mobile sink trajectory plays a pivotal role for network coverage, data collection and data dissemination in wireless sensor networks. Considering this, we propose a novel approach for mobile sink trajectory in wireless sensor networks. Our proposed approach is based on Hilbert Space Filling Curve, however, the proposed approach is different from the previous work in a sense that the curve order changes according to node density. In this paper, we investigate the mobile sink trajectory based on Hilbert Curve Order which depends upon the size of the network. Second, we calculate the Hilbert Curve Order based on node density to re-dimension the mobile sink trajectory. Finally, we perform extensive simulations to evaluate the effectiveness of proposed approach in terms of network coverage and scalability. Simulation results confirm that our proposed approach outperforms with size based Hilbert Curve in terms of network coverage, packet delivery ratio and average energy consumption. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid trust model, and a multifactor, depending on trust value of sensor nodes, remaining energy, and hop count, routing strategy known as Temperature-Aware Trusted Routing Scheme (TTRS). In fact, it establishes the shortest and most trusted routing path. The multifactor strategy selects trustworthy nodes to forward data and reduce energy utilization due to secure shorter routing paths. TTRS incorporates an efficient multifactor hotspot node detection algorithm (HNDA) along with route discovery as well as route maintenance mechanism to detect malicious relay nodes for consistent data delivery in an unattended environment. Experimental results express the admirable average performance gain of TTRS in terms of accurate trust evaluation, network lifetime, packet delivery rate, and average energy consumption per node, as compared to ATRP, EOSR, and SQEER. Consequently, TTRS is more accurate than the aforementioned competitive schemes under different loads in a hostile environment. [ABSTRACT FROM AUTHOR]

• The article is focused on improving the performance of data transmission in wireless sensor network. The highlights of the research are as follows. • Active relay nodes are identified with fuzzy logic and utility factor. • Coverage distance is measured with Received Signal Strength (RSS) • The fuzzy inference system selects the next relay node according to the coverage distance, energy and utility factor and bandwidth availability factors. • By choosing relay node according to the above mentioned factors, the data transmission performance is improved. Numerous sensor nodes are getting utilized in the field of Wireless Sensor Network (WSN) for complex communication. In the recent scenario, there is a lack in the number of sensor node placement with less sensing and communication capabilities. There is less involvement with the characteristics of sensor nodes for direct communication with remote nodes. During the communication, sensor data are communicated to the sink with the help of sensor hubs. Therefore to improve the performance of QoS, routing in the integration of relay node selection plays an important role in WSN. In this paper, we propose Fuzzy based Relay Node Selection and Energy Efficient Routing (FRNSEER) make the routing more efficient by selecting the effective relay node while communicating with the sink node. For selecting the sink node, fuzzy rules are used where active relay nodes are selected as the outcome. The active relay node selection helps to determine the better energy and utility factor during the transmission process. To make better communication between the relay node and the sink node, sensor hubs are used with a lower energy expenditure schedule with expected functions of neighbor/working nodes. In the performance analysis, the proposed mechanism will perform better in terms of packet rate with low energy consumption compared to the existing algorithms such as Fuzzy-based Hyper Round Policy (FHRP) and Neural Network-based Localisation Scheme (NNBLS). [Display omitted] [ABSTRACT FROM AUTHOR]

• The node energy consumption caused by flooding communication mechanism should be solved. • The condition of sleeping state and the time of waking up should be judged reasonably. • Ensure the opportunity to participate in communication while reducing energy consumption of nodes. • Asynchronous sleeping mechanism based on the historical encounter information and movement status of the node. The opportunistic network is based on the idea of "Store-Carry-Forward" between nodes which haven't complete communication links. It uses the encounter opportunity presented by node mobility to establish a route to realize communication. The traditional Epidemic algorithm uses the flooding mechanism which greatly increases the energy consumption of nodes, and it is often unable to supplement the energy of nodes at any time in the application environment of the opportunistic network. Therefore, this paper proposes an asynchronous sleep mechanism, which allows nodes to judge whether to enter the sleep state according to their own energy situation, real-time state and other information. It ensures that the nodes do not miss the possible communication opportunities by dynamically controlling the sleep time and wake-up time. The simulation results show that the proposed EASE algorithm can guarantee the network performance and greatly reduce the energy consumption of nodes compared with the classical opportunistic network routing algorithms. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy optimization is the most important to improve the lifetime of a wireless sensor network. Nodes in sensor networks require to have an optimal mechanism for utilizing energy A new technique named Hybrid Optimization Algorithm, presented in this paper, is based on Lagrangian relaxation and entropy for reducing the energy consumption. The proposed model helps to maintain multi-hop connectivity with dynamic action. The nodes are allowed to communicate based on energy, bandwidth, neighbor connectivity, hop count, to maintain high QoS energy parameters. The simulations are in NS2 software. The proposed approach evaluates total consumed energy, average remaining energy, packets received rate, drop rate, normalized routing overhead, delay, throughput, goodput, jitter, and network lifetime. The comparison results show that the nodes' lifetime improved with a Hybrid Optimal Based Cluster Formation (HOBCF) algorithm. [ABSTRACT FROM AUTHOR]

Internet of Things has been a pivotal technology enabler for realizing smart cities vision through the provision of connectivity for everyday objects by means of wireless sensor networks (WSNs). Scalability, flexibility, route efficiency, mobility support and reduced overhead in routing protocols are desired functions in large-scale WSNs. Given the several geographic routing schemes proposed, mainly focusing on positioning, location error, and energy consumption, still exhibit higher delays and overhead which significantly affect the performance of the network. In this paper, an energy-efficient geographic (EEG) routing protocol has been proposed that focuses on network throughput and energy consumption of sensor nodes. Moreover, this strategy also helps in avoiding void region's creation in the network. The proposed protocol reduces the energy hole problem by efficiently balancing the energy consumption among sensor nodes. The extensive simulations illustrate that the proposed scheme manages energy consumption and packet delivery ratio more efficiently in comparison to a state-of-the-art geographic routing protocol. [ABSTRACT FROM AUTHOR]