Energy efficient Hybrid Clustering Algorithm for Wireless Sensor Network

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

SummaryEnergy consumption in wireless sensor network (WSN) is one of the important issues as tiny sensor nodes are equipped with a non‐replaceable batteries. Clustering is one of the effective means to prolong the network lifetime in WSN by reducing the number of packets to be sent from cluster heads (CHs) to base station (BS). Recently, game theory techniques have been applied in the clustering process for optimal CH election at each round. However, none of them have considered the energy parameter in their game strategy and multihop routing for data transmission. In this manuscript, an energy‐efficient game‐theoretic clustering and multi‐hop routing scheme (EGCR) has been proposed where the non‐cooperative approach of game theory is used to elect optimal CHs. In the proposed game theoretic framework, each node behaves in a selfish manner while considering the residual energy of nodes and focuses on increasing the overall lifetime of the network. Nash equilibrium is determined among a set of pure and mixed strategies, and then the expected payoff of a node is determined for Nash equilibria. Apart from the energy‐efficient clustering, the EGCR also proposes a multi‐hop routing solution for data transmission that further enhances the lifetime of whole network. In the multi‐hop routing approach, inter‐cluster and intra‐cluster routing techniques are proposed to identify optimal routes from nodes to CHs and from CHs to BS by using various factors such as node centrality, distance from the node to BS, and residual energy. The proposed algorithm is compared with traditional clustering schemes like low‐energy adaptive clustering hierarchy (LEACH) and efficient energy‐aware game theory‐based clustering (EEGC) and also with existing game theory‐based algorithms such as clustered routing for selfish sensors (CROSS), localized game theoretical clustering algorithm (LGCA), and energy‐efficient clustering algorithm based on game theory (ECAGT). Simulation experiments validate that the proposed algorithm enhances the network's lifetime up to 47.49% compared to existing clustering algorithms.

Ultra-wideband (UWB) radio communication sys- tems operate using extremely short duration base-band pulses. This paper compares the performance of three competing multi- ple access modulation schemes that have been proposed for appli- cation to UWB based wireless sensor networks. These multiple access schemes are ultra-wideband Time-Hopping (TH-UWB), Direct Sequence Spread Spectrum (DSSS-UWB) and Orthogonal Frequency Division Multiplexing (OFDM-UWB). Each system was investigated under four operating conditions of different bandwidths and bit rates for three different transmission ranges. The attributes measured to compare the performance of the multiple access schemes under consideration were packet link error rate, throughput and energy efficiency. TH-UWB outper- forms DSSS-UWB and OFDM-UWB for high bandwidth condi- tions. Whereas, DSSS-UWB performs better in low bandwidth conditions compared to the other two systems. Decreasing the transmission range significantly degrades the overall performance of the systems. I. INTRODUCTION Wireless sensor networks are special networks composing of a large number of inexpensive, low-power communication sensing devices (sensor nodes), which are densely deployed throughout a physical space and have the capability of col- laborating with each other to monitor a wide variety of ambient conditions. Realisation of sensor network applications requires wireless ad hoc networking techniques (1), therefore the sensor nodes are deployed in an ad hoc fashion and are required to organize themselves to form a multi-hop wireless communication network. Efficient and reliable communication between multiple sen- sor network entities is a big challenge. The increased collision probability resulting from multiple sensor nodes transmitting data simultaneously over the same transmission medium is a common problem facing communication in wireless networks. This problem can be overcome by using reliable multiple access techniques. An ideal wireless sensor communication network would require a multiple access scheme that allows the accommodation of multiple users and provides effective communication. It must also offer some measure of security and should have low probability of intercept. It should also be resistant to jamming and must be energy efficient. Ultra-wideband (UWB) radio is an emerging technology that operates using extremely short duration base-band pulses and has a number of advantages that makes it an attractive choice for sensor networks. In particular, UWB systems have low power and low complexity. They have a noise like signal and are therefore resistant to severe multipath and jamming. They also provide greater bandwidth and are more cost ef- fective for providing increased throughput without increasing power. The three approaches to multiple access in UWB are:

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

In Wireless Sensor Networks (WSN), cluster networks structures have the advantage of providing scalable and energy-efficient solutions as the sensor nodes are highly energy-constrained.In this paper, we propose a dynamic clustering algorithm for WSN which is in application to event monitoring.In this clustering algorithm, the cluster head selection approach takes the received signal strength residual energy of node and distance between the cluster head and the sink node into consideration.Through this method, the cluster size is constrained and the energy consumption of intra-cluster communication is reduced.The simulation results show that the proposed algorithm can efficiently conserve energy and prolong the lifetime of WSN, especially when the sink node is far from the network.

Prolonged network lifetime, scalability and efficient load balancing are essential for optimal performance of a wireless sensor network. Clustering provides an effective way of extending the lifetime of a sensor network. Clustering is the process that divides sensor networks into smaller localized group (called clusters) of members with a cluster head. Clustering protocols need to elect optimal number of clusters in hierarchically structured wireless sensor networks. Any clustering scheme that elects clusters uniformly (irrespective of the distance from Base Station) incurs excessive energy usage on clusters proximal and distant to Base Station. In single hop networks a gradual increment in the energy depletion rate is observed as the distance from the cluster head increases[17]. This work focuses on the analysis of wasteful energy consumption within a uniform cluster head election model (EPEM) and provides an analytical solution to reduce the overall consumption of energy usage amongst the clusters elected in a wireless sensor network. A circular model of sensor network is considered, where the sensor nodes are deployed around a centrally located Base Station. The sensor network is divided into several concentric rings centred at the Base Station. A model, Unequal Probability Election Model (UEPEM), which elects cluster heads non-uniformly is proposed. The probability of cluster head election depends on the distance from the Base Station. UEPEM reduces the overall energy usage by about 21% over EPEM. The performance of UEPEM improves as the number of rings is increased.

In wireless sensor networks, power is the most essential resource because each sensor node has limited batteries. Many kinds of existing clustering protocols have been developed to balance and maximize lifetime of the sensor nodes in wireless sensor networks. These protocols select cluster heads periodically, and they considered only `How can we select cluster heads energy-efficiently?' or `What is the best selection of cluster heads?' without considering energy-efficient period of the cluster heads replacement. Unnecessary head selection may dissipate limited battery power of the entire sensor networks. In this paper, we present T-LEACH, which is a threshold-based cluster head replacement scheme for clustering protocols of wireless sensor networks. T-LEACH minimizes the number of cluster head selection by using threshold of residual energy. Reducing the amount of head selection and replacement cost, the lifetime of the entire networks can be extended compared with the existing clustering protocols. Our simulation results show that T-LEACH outperformed LEACH in terms of balancing energy consumption and network lifetime.

An efficient cluster head selection for wireless sensor network-based smart agriculture systems

Clustering techniques in wireless sensor networks (WSNs) compare to random selection techniques is less costly due to the saving of time in journeys, reduction in number of transmissions and receptions at each node, identification, contacts, etc., which are valuable for increasing the overall network life, scalability of WSNs. Clustering sensor nodes is an effective and efficient technique for achieving the requirement. The maximizing lifetime of network by minimizing energy consumption poses a challenge in design of protocols. Therefore, proper organization of clustering and orientation of nodes within the cluster becomes one of the important issues to extend the lifetime of the whole sensor network through Cluster Head (CH). We investigate the problem of energy consumption in CH rotation in WSNs. In this paper, CH selection algorithm has been proposed from an unequal cluster. The total energy and expected number of packet retransmissions in delivering a packet from the sensor node to other nodes have been mathematically derived. In this paper, we applied the approach for producing energy-aware unequal clusters with optimal selection of CH and discussed several aspects of the network mathematically and statistically. The simulation results demonstrate that our approach of re-clustering in terms of energy consumption and lifetime parameters.

The present cluster head selection is fixed as a static node, so the cluster head becomes malicious the entire cluster communication is discarded in wireless sensor networks (WSNs). As per our new approach, the cluster heads are using fault tolerance schemes supports for selection cluster head through the game theory. This process may take additional energy to detect malicious cluster heads and to recover the network communication in the cluster. This article proposes fault-tolerant backup cluster head (BCH) selection influenced by game theory in wireless sensor networks WSNs by utilizing less energy. In WSNs, the malicious cluster heads can be exhibited efficiently using game theory through the different network conditions such as scalability, mobility, and energy utilization. Due to scalable WSNs, the cluster node is increasing in the cluster head becomes malicious thus network lifetime is reduced. So, the fault-tolerant BCH technique is incorporated to increase the lifetime of WSNs. So, the efficiency of the sensor network is reduced due to the cooperation of malicious and normal nodes. The malicious cluster heads being detected based on node parameters and the clustered network operations are carried out through fault-tolerant backup cluster head in WSNs. The simulation results have obtained for the proposed scheme compared with the network parameters such as dead nodes, alive nodes, and average energy of active nodes in the network.KeywordsWireless sensor networkGame theoryFault-tolerant networkCluster head selectionBackup cluster head

The sensor network performs gathering, monitoring, and tracking of objects in the given area. The sensor nodes are normally distributed randomly in the network area for collecting the information. The major issues in Wireless Sensor Networks (WSN) are coverage, energy, and limited resources. Sensor Nodes’ (SN) performance depends on so many parameters but normally depends on Residual Energy (RE) and Distance from the base station. The Cluster Head (CH) cooperatively communicates with Base Station (BS) via routing protocols. The proposed Energy Efficient Multilevel Region Based (EEMRB) protocol performs the task by partitioning the entire network area into multiple levels and sub-levels. The sub-levels are partitioned to perform clusters to communicate the sensor via CH (s) using single/multi-hop communication to BS. The proposed protocol is compared with the Stable Election Protocol and shows improvement in network lifetime. Based on the proposed protocol data set, a Multivariate Polynomial Regression (MPR) Model is proposed to predict network lifetime. The model uses packet size and node density as network design parameters. The simulation results show that the size of the packet and network area play a major role in network lifetime. Therefore, the lifetime of the predicted model and EEMRB protocol are close to each other. This prediction model is suitable for the prediction of any network area's lifetime.

Nowadays advanced technology of Wireless Sensor Networks used in many applications like health, environment, battle field etc. The sensor nodes equipped with limited power sources. Therefore, efficiently utilizing sensor nodes energy can maintain a prolonged network lifetime . One of the major issues in sensor networks is developing an energy-efficient routing protocol to improve the lifetime of the networks. In this paper, we propose EELBCRP (Energy-Efficient Level Based Clustering Routing Protocol), a protocol for wireless sensor networks. Network partitioned into annular rings by using various power levels at base station and each ring having various sensor nodes. Also consider the residual energy of each node and distance from the BS of nodes as the principle of cluster-head election. The mathematical formulae for election the cluster head is provided. The model developed is simulated in MATLAB. The results are obtained in terms of three metrics- lifetime of the network, number of clusters and energy consumption of clusters heads. From the results of simulation, it is observed that the performance of EELBCRP is better in terms of energy consumption of CH, number of clusters and lifetime of network compared with LEACH.

Maximisation of network lifetime is the issue of prime importance in Wireless Sensor Network (WSN). An energy–efficient clustering algorithm with load balancing can achieve this challenging goal. We propose Density–based Dynamic Clustering (DDC) algorithm for clustering and cluster head election mechanism with the use of independence set. Furthermore, a distributed algorithm (DISD - Distributed Independence Set Discovery) is designed for cluster head election in O(1) complexity per sensor node. In this, we dynamically find an optimal sensor cover to dominate maximum sensors within a cluster, therefore forming an InDependence Set (IDS). Only the members of IDS are allowed to participate in the cluster head selection (rotation), thereby establishing load balancing and energy management. Our model is designed for dual modes: low– and high–traffic session. According to the flow of packets, the sleep management technique is modified. Network simulator is used for the simulation of our proposed algorithms.

Clustering is an efficient topology control approach for maximizing the lifetime and scalability of Wireless Sensor Networks (WSNs). Many cluster-based routing techniques have been proposed in the literature. However, in most of the proposed protocols, the communication between a sensor node and its designated cluster head (CH) is assumed to be single-hop. Multi-hop communication can be used when the communication range of the sensor nodes is limited or the number of sensor nodes is very large in a network. Moreover, they used a predetermined percentage of CHs regardless of the network density or the number of live nodes. Clustering is known to be non-deterministic polynomial (NP)-hard problems for a WSN. Particle Swarm Optimization (PSO) is a swarm intelligent approach that can be applied for finding fast and efficient solutions of such problems. In this paper, we propose a novel centralized PSO protocol for Hierarchical Clustering (PSO-HC) in WSNs. Our objective is to maximize the network lifetime by minimizing the number of active CHs and to maximize the network scalability by using two-hop communication between the sensor nodes and their respective CHs. The effect of using a realistic network and energy consumption model in cluster-based communication for WSN was investigated. Extensive simulations show that PSO-HC outperforms the well-known cluster-based sensor network protocols in terms of average consumed energy and throughput.