Energy Efficient Stable Election Protocol for Clustered Heterogeneous Wireless Sensor Networks

Abstract: We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes. Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs). The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP), which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP.

Wireless Sensor Network (WSN) is a wireless network that involves sensors in the network. The sensor node on the WSN will collect data information from the environment around the sensor. However, each sensor node has storage capacity, processing power, communication range, and battery life limitations. The use of energy consumption from these factors is the main problem because each sensor node uses its power consumption from the battery. Stable Election Protocol (SEP) is a type of routing protocol on WSN that uses the clustering method. SEP has a function to extend the time interval before the first node dies. This research was carried out on the SEP protocol with alive node parameters, total initial energy, and stability. This study indicates that on a network that uses 100 nodes with sink positions (0, 100), two nodes are still alive and several nodes that are still alive in several sink positions that use 200 nodes. For networks where there is still a lot of energy remaining in the sink position (0, 100) with the network using 100 nodes and for networks using 200 nodes, the remaining energy is mainly in the sink position (100, 100). The highest stability period is in the sink position (50, 50) for networks using 100 nodes, and for networks using 200 nodes, the highest stability period is in the sink position (100, 50).

Energy conservation is a major challenging issue in the field of Wireless Sensor Networks (WSNs) since the sensor nodes are battery operated. Among the various topology control techniques, clustering is best and popular technique which provides both energy conservation and scalability. A cluster based routing protocols consists of mainly three phases: cluster head selection, cluster formation and data communication phase. In this paper, a fuzzy logic based cluster head selection method is proposed. In this method, energy of cluster head, node centrality and distance of node from the base station act as fuzzy descriptors to the Mamdani fuzzy inference system. The proposed Fuzzy Logic based Cluster Head Selection (FLCHS) method helps in balancing the load of nodes and leads to energy conservation. The proposed approach FLCHS is compared with the well known Stable Election Protocol (SEP) for heterogeneous networks. The FLCHS protocol performs better than SEP protocol in terms of network lifetime, energy consumption and throughput.

In Wireless Sensor Networks the nodes have restricted battery power and the exhaustion of battery depends on various issues. In recent developments, various clustering protocols have been proposed to diminish the energy depletion of the node and prolong the network lifespan by reducing power consumption. However, each protocol is inappropriate for heterogeneous wireless sensor networks. The efficiency of heterogeneous wireless sensor networks declines as changing the node heterogeneity. This paper reviews cluster head selection criteria of various clustering protocols for heterogeneous wireless sensor networks in terms of node heterogeneity and compares the performance of these protocols on several parameters like clustering technique, cluster head selection criteria, nodes lifetime, energy efficiency under two-level and three-level heterogeneous wireless sensor networks protocols Stable Election Protocol (SEP), Zonal-Stable Election Protocol (ZSEP), Distributed Energy-Efficient Clustering (DEEC), A Direct Transmission And Residual Energy Based Stable Election Protocol (DTRE-SEP), Developed Distributed Energy-Efficient Clustering (DDEEC), Zone-Based Heterogeneous Clustering Protocol (ZBHCP), Enhanced Distributed Energy Efficient Clustering (EDEEC), Threshold Distributed Energy Efficient Clustering (TDEEC), Enhanced Stable Election Protocol (SEP-E), and Threshold Stable Election Protocol (TSEP). The comparison has shown that the TDEEC has very effective results over other over two-level and three-level heterogeneous wireless sensor networks protocols and has extended the unstable region significantly. From simulations, it can also be proved that adding node heterogeneity can significantly increase the network life.

The lifetime of Wireless Sensor Network (WSN) is based on the energy of each sensor. Therefore, numerous routing protocols have been introduced such as SEP (Stable Election Protocol), LEACH (Low energy adaptive clustering hierarchy) and EAMMH (Energy Aware Multi-hop Multi-path Hierarchical routing protocol) to stable the lifetime of WSN by efficient utilization of energy of the sensors. In WSN networks data is collected and forwarded wirelessly to the base stations. Routing protocols in WSN provide an efficient path for multi-hop communication because the transmission range and battery power storage of nodes is limited. As nodes are usually deployed in remote areas so, they face challenges of long lifetime, network architecture, security issues, and network coverage. Many routing protocols have been developed to increase the efficiency of networks. Out of these clustering algorithms are the best choice to increase the lifetime of the nodes. Each protocol has its limitations in different scenarios. In this paper, we discussed and compared the performance of LEACH, EAMMH and SEP. SEP is an efficient algorithm due to its weighted cluster head (CH) selection method. Simulation results are obtained using MATLAB. Design metrics of energy consumption and network lifetime are under consideration in this research work.

<p class='IJASEITAbtract'><span lang='EN-GB'>T</span><span lang='EN-GB'>he technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.</span>

Internet of Things (IoT) is an important technique in the modern wireless telecommunications field. It is based on a collection of sensor nodes connected through wireless sensor networks (WSNs). The lifetime of this network is affected by the battery power of the connected sensor nodes. Network clustering techniques are used to improve energy consumption and extend the lifetime of the WSN. These techniques divide the sensor nodes into clusters and every cluster has a unique cluster head (CH) node. Recently, clustering-based metaheuristic techniques are used to solve this problem and find the optimal CH nodes under certain considerations such as less energy consumption and high reliability. This paper proposes a new clustering scheme for heterogeneous WSN using Coyote Optimization based on a Fuzzy Logic (COFL) algorithm. It uses the coyote optimization algorithm (COA) in conjunction with fuzzy logic (FL) system to reinforce and balance the clustering process for increasing the wireless network lifetime and reducing energy consumption. FL based clustering is adapted to determine a tentative set of CHs. The output of the FL is added as a solution within the initial solutions of the COA. Furthermore, a new fitness function has been adapted to minimize the total intra-cluster distance between each CH node and its cluster members and minimize the inter-cluster distance between the CHs nodes and the base station. An extensive simulation with three different scenarios is performed. The performance of the proposed COFL algorithm is compared with the well-known algorithms; namely low-energy adaptive clustering hierarchy protocol (LEACH) and stable election protocol (SEP) as traditional protocols and also coyote optimization algorithm (COA), grey wolf optimization (GWO), and particle swarm optimization (PSO). The COFL algorithm outperforms other algorithms in terms of alive node analysis, energy consumption, throughput, and central tendency measurements for alive nodes and normalized energy.

Wireless sensor networks (WSNs) are being applied widely for data collection, especially to carry out the mission-critical tasks. Therefore, one of the most challenging tasks of mission-critical sensors and sensor networks is the development of energy efficient (EE) routing protocols. Comparing with flat routing protocols, more EE can be achieved in hierarchical routing protocols. In this paper, we propose an enhanced balanced energy efficient network-integrated super-heterogeneous (E-BEENISH) routing protocol, by analyzing communication energy consumption of the clusters and a large range of energy levels in heterogeneous WSNs. E-BEENISH is based on weighted election probabilities of each node to become a cluster head according to the remaining energy and the distance from the sink to the node. Moreover, we also study the impact of the heterogeneity of nodes in terms of energy. Studying the sensitivity of our stable election protocol, we conclude heterogeneity parameters capturing energy imbalance in the network and find that the E-BEENISH yields the longer stability region for the suitable weight of energy and distance. Our results show by simulation that the E-BEENISH can improve system lifetime by an order of magnitude compared to obtained using current clustering protocols, which is crucial for many applications.

Mobile target tracking consists in detecting and locating targets in a surveillance region. Wireless Multimedia Sensor Networks (WMSN) can provide more information about the moving target than classical Wireless Sensor Networks (WSN), but their process and the transmission of multimedia data are costly which reduces the network's lifetime. In this paper, we propose a low-cost new solution for tracking a mobile target called EAOT (Energy Aware Object Tracking). It consists of a distributed cooperative algorithm that runs in heterogeneous Wireless Sensor Networks composed of both scalar and multimedia sensors. The scalar sensors (MS) are equipped with a motion detector; their role is to detect the target and then activate the camera sensors (CS) through message exchanges. We conducted simulations to evaluate the performance of the proposed mechanism in terms of tracking accuracy, number of exchanged messages, energy consumption, and spatial average deviation. The results are compared to two existing solutions: one based on simple camera sensors which always run in active mode and the other one based on the optimal camera node selection (OCNS) to track the target. The obtained results show that for the same number of nodes, EAOT consumes between 2.6% and 44% less energy than OCNS depending on the distribution of MS/CS.

Recent advancements in miniaturization and inter-operability of wireless technologies have enabled a variant of Wireless Sensor Network (WSN), called Heterogeneous Wireless Sensor Network (HWSN). This plays a significant role in most popular applications of WSN such as habitat monitoring, volcano monitoring, military applications, etc. Similar to WSN, power resources are of utmost importance in HWSN too. Hence, several techniques have already been proposed to achieve energy-efficient network operations in heterogeneous networks. Among all those proposed schemes, the notion of clustering has proved its worth in obtaining energy-efficient clusters throughout the network. However, most of such clustering-based schemes utilize a dynamic probabilistic approach to deal with multilevel energy heterogeneity, which consumes many nodes' energy in the cluster formation. Moreover, with the varying degree of energy heterogeneity, most probabilistic schemes underperform and fail to compete. In this work, a Metaheuristic Multilevel Heterogeneous Clustering Technique (MMHCT) for Heterogeneous Wireless Sensor Networks has been proposed. MMHCT not only reduces the energy consumption in cluster-formation over the network rounds but also distributes the load evenly among the clusters to prolong the network lifetime. The supremacy of the proposed scheme is shown through various experiments against a state-of-the-art scheme, DEBCRP (Differential Evolution Based Clustering Routing Protocol) and the results confirm gains of 50%, 29.69%, 30.22%, 65.65%, & 37.17% in terms of network lifetime under 1-level, 2-level, 3-level, 4-level, & 5-level of energy heterogeneity respectively.

Attaining a prolonged network lifetime, maximized coverage, and high performance are vital design factors that have to be maintained in a Wireless Sensor Networks (WSN). Such factors are dependent on the stability and optimality of the protocol employed to formulate Sensor Nodes (SNs) into mutual clusters that effectively work around fulfilling specific performance goals. SEP is a heterogeneity-aware protocol implemented based on Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, designed to prolong the stability period of the network defined by the time interval before the death of the first SN. Nevertheless, adaptability in design is a scheme that has not been extensively applied in the formation of WSN election protocols. Adapt-𝑃 is a probabilistic model for adaptivity designed to evolve the probability of selecting a cluster-head based on the active status of the WSN, represented by the residual energy of and distances between SNs. However, the adaptive probability 𝑃adp formalized in Adapt-𝑃 is developed based on the remaining number of SNs 𝜁 and optimal clustering κmax, yet 𝑃adp does not implement the probabilistic ratios of energy and distance factors in the network. Furthermore, Adapt-𝑃 does not localize cluster-heads in the first round properly because of its reliance on distance computations defined in LEACH, that might result in uneven distribution of cluster-heads in the WSN area and hence might at some rounds yield inefficient consumption of energy. This paper utilizes 𝑘-means++ and Adapt-𝑃 to propose 𝑃c𝜅max-means++ clustering algorithm that better manages the distribution of cluster-heads and produces an enhanced performance. The algorithm employs an optimized cluster-head election probability 𝑃c developed based on energy-based 𝑃𝜂(𝑗,𝑖) and distance-based 𝑃𝜓(𝑗,𝑖) quality probabilities along with the adaptive probability 𝑃adp, utilizing the energy 𝜀 and distance optimality 𝑑opt factors. Furthermore, the algorithm utilizes the optimal clustering 𝜅max derived in Adapt-𝑃 to perform adaptive clustering through 𝜅max-means++. The proposed 𝑃c𝜅max-means++ is compared with the energy-based algorithm 𝑃𝜂𝜀𝜅max-means++ and distance-based 𝑃𝜓𝑑opt𝜅max-means++ algorithm, and has shown an optimized performance in term of residual energy and stability period of the network.

Wireless sensor networks (WSNs) consist of an enormous number of tiny sensor nodes deployed in huge numbers which are able to sense, process and transmit environmental information to the base station (BS) for a variety of applications. Energy efficiency is one of the primary concerns for maintaining WSN in operation. In this study, an energy efficient clustering protocol based on K‐means algorithm named EECPK‐means has been proposed for WSN where midpoint algorithm is used to improve initial centroid selection procedure. The proposed approach produces balanced clusters to ultimately balance the load of cluster heads (CHs) and prolong the network lifetime. It considers residual energy as the parameter in addition to Euclidean distance used in basic K‐means algorithm for appropriate CH selection. Multi‐hop communication from CH nodes to BS takes place depending on their distances from BS. Simulation result shows that the proposed approach outperforms LEACH‐B, balanced parallel K‐means (BPK‐means), Park's approach and Mk‐means with respect to network lifetime and energy efficiency. Simulation result also demonstrates that the proposed approach can reduce the energy consumption at most 50% compared to LEACH‐B, 14% compared to BPK‐means protocol, 10% compared to Park's approach and 6% compared to Mk‐means.

Designing and development of energy effective path planning algorithm is very key research domain in order to tackle the issues of limited life-time for Wireless Sensor Networks (WSNs). So in WSNs, energy efficiency is major concern of researchers. Overall advancement in routing protocols prove that clustering is much better approach as compared to flat and location-based energy efficient routing protocols. Due to better performance, multiple energy efficient clustering routing protocols have been proposed. But existing clustering algorithms are centralized or distributed, which are not intelligent enough and do not produce hybrid cluster-head selection. In this paper, we propose a cluster structured path planning algorithm named, Hybrid Advance Distributed Centralized Clustering (HADCC) path planning energy efficient algorithm. HADCC proposed model is fascinated with hybrid cluster head selection algorithm. This hybrid algorithm makes decision of cluster head selection of nodes. In order to execute proposed model we have also proposed an advance network topology, in which the whole network region is divided into two physical levels. First physical level consists of a circular region, containing homogeneous normal nodes and all important Base Station. While, second physical level is outer region of the circle that contains advanced heterogeneous nodes. Simulation results indicate that HADCC prolongs the network lifetime as compared to existing advanced clustering routing protocols for both homogeneous and heterogeneous WSNs. HADCC outperforms in case of stability and network life time as compared to the existing clustering algorithms.

Wireless Sensor Networks (WSNs) connected to the Internet of Things (IoT) are increasingly employed in commercial and industrial applications to accomplish various tasks at a low cost. WSNs are essential for gathering diverse types of data within physical environments. A key design objective for WSNs is to balance energy consumption and increase the network’s operating lifetime. Recent studies have shown that mobile base stations (BSs) can significantly extend the lifetime of such networks, especially when their location is optimized using specific criteria. In this study, we propose an algorithm for selecting the optimal BS location in a large network. The algorithm computes a distance metric between sensor nodes (SNs) and potential BS locations on a virtual grid within the WSN. The selection process is repeated periodically to account for dead SNs, allowing the BS to relocate to a new optimal position based on the remaining active nodes after each iteration. Additionally, the inclusion of a relay node (RN) in large networks is explored to improve scalability. The impact of path loss within WSNs is also discussed. The proposed algorithms are applied to the well-known Stable Election Protocol (SEP). Simulation results demonstrate that, compared to other algorithms in the literature, the proposed approaches significantly enhance the lifetime of WSNs.

Wireless sensor networks (WSN) are growing in every aspects ranging from measuring temperature, humidity, rainfall to the battle field. In this type of application there are large numbers of sensors that has not been used and some are work independently. This paper put forward an analytical study of Stable Election Protocol and Modified Stable Election Protocol for heterogeneous wireless sensor networks (WSNs). The purpose of this comparative study is to analyze and identify the suitable platform for more stable and energy efficient heterogeneous WSNs platform. The study is supported by multiple simulations in a random distribution environment with different parameters like number of dead nodes, alive nodes, amount of data transmitted to the destination etc. from the simulation and result analysis we can say M-SEP is more stable and effective than SEP as well as M-SEP provides a longer stability period on an average of 9% extra than SEP.