Temporary Cluster Heads Research Articles

Hybrid fuzzy logic and artificial Flora optimization algorithm-based two tier cluster head selection for improving energy efficiency in WSNs

Wireless Sensor Network (WSN) is the one of the hot area of research in which energy stability and network lifetime are considered to be the twin challenges during its application. Clustering is the optimum energy efficiency strategy that organizes the sensor nodes into potential groups for the objective of attaining energy stability and network lifetime. In this energy potent clustering process, cluster head selection is determined to be highly significant in order to balance energy among the nodes sensor nodes. Moreover, two-tier cluster head selection that includes temporary and final cluster head is identified to be challenging in WSNs. In this paper, Hybrid Fuzzy Logic and Artificial Flora Optimization Algorithm (FL-AFA)-based Two Tier Cluster Head Selection is proposed for improving energy efficiency and prolog network lifetime. This FL-AFA scheme achieved the cluster head selection in two stages, such as, i) Temporary Cluster Head (TCH) selection using FL and, ii) Final Cluster Head (FCH) selection using AFA. In the first stage, the concept of fuzzy logic applied over the input parameters of residual energy (RE), distance to BS (DTBS), and node degree (NDE). In the second stage, the benefits of AFA is employed for computing the fitness function through distance to nearby nodes (DNN), cluster compactness estimation factor (CCEF), and position estimation (PE). Simulation experiments of the proposed FL-AFA scheme and the benchmarked schemes are conducted based on the evaluation metrics of energy efficiency, network lifetime, average delay, and packet delivery ratio (PDR) under the impact of different sensor nodes. .

RETRACTED ARTICLE: Pivot variable location-based clustering algorithm for reducing dead nodes in wireless sensor networks

The information technology has grown so rapidly that it has led to the development of compact size and inexpensive sensor nodes. Several sensor nodes together form a WSN. Though the WSN is compact in size, they can be equipped with radio transceivers, sensors, microprocessors which are embedded and sensors. One of the major critical issues with WSN is energy efficiency. With WSN, various energy-efficient techniques are being employed. Among clustering techniques, LEACH, HEED, EAMMH, TEEN, SEP, DEEC, K-means clustering algorithm are some of the most popular energy-efficient techniques which are employed. These are hierarchical based protocol which saves energy by balancing the energy expense. Detailed review and analysis of these protocols are presented, and midpoint location algorithm is proposed in this paper. The methodology used for reduction in dead nodes while transmitting the data is also discussed. In the proposed work, path construction phase (PCP) and alternative path construction phase (APCP) are created in order to reduce dead nodes. During the processes of data transmission if a node is found out that it will fail and APCP is applied, the cluster head is changed while applying the APCP. The cluster head is chosen based on midpoint location and highest node energy. The cluster head becomes permanent if the node has midpoint location and the highest energy. If the node does not have midpoint location and highest energy, it becomes a temporary cluster head. The proposed techniques are compared with EAMMH protocol and LEACH protocol using MATLAB. When compared with EAMMH, the dead nodes were reduced with subsequent rounds.

Energy Balance Based Uneven Cluster Routing Protocol Using Ant Colony Taboo for Wireless Sensor Networks

To overcome the drawbacks of the short lifetime in wireless sensor networks (WSNs) caused by the imbalanced energy consumption, this paper proposes an efficient ant colony taboo based energy balance routing protocol using uneven cluster (ACTEBUC) for WSNs. The mechanism of temporary cluster head election is improved, the generation of random numbers is optimized, and the energy, distance and density factors are deduced into the threshold value. The real cluster heads are selected based on the node’s competition radius and communication cost that are used for the uneven clustering. Once finishing the cluster, ACTEBUC optimizes ant colony, and improves the probability of selecting next hop node, the pheromone update and the inspiring factor. The pheromone updating is added to the tasks of the forward ant to speed up the convergence rate. The path length is considered when pheromone updating is executed by the backward ant, the ants release more pheromones on the node which is closer to the destination node, which makes the destination node is more likely to be found and speeds up the convergence rate of the algorithm. Meanwhile, a route optimizing algorithm is proposed to increase network lifetime by adjusting the transmission route, and it finds the optimal path to minimize the communication energy consumption. The performance of the proposed algorithm is simulated using MATLAB. Comparing with the results of other algorithms, the simulation results show that the proposed algorithm can efficiently balance the energy consumption, and demonstrate the good performance of the proposed algorithms to increase network lifetime. Also ACTEBUC has the ability to enhance the data transmission reliability.

Energy-Efficient Collaborative Communication for Optimization Cluster Heads Selection Based on Genetic Algorithms in Wireless Sensor Networks

To solve the energy constraint problem caused by the neighborhood of the sink, which is burdened with heavy relay traffic via multihop communication and tends to die earlier, a new energy-efficient collaborative communication model is proposed based on genetic algorithms in wireless sensor networks (WSNs). By setting the threshold value for a new generation judgment function, the proposed algorithm would be capable of judging whether the sensor nodes can be a cluster head. Then, the genetic algorithms will filter out some nodes from these temporary cluster heads to get the final cluster heads. Simulation results show that the proposed algorithm can allocate energy to each node of WSNs and postpone the death of the first node. In this manner, the lifetime of WSNs is effectively prolonged.

An Improved LEACH Protocol Based on Nodes' Remaining Energy and Location

WSN (Wireless Sensor Network) consists of large hundreds and thousands of sensor nodes which have limited energy, and the energy cannot be added. Hence, how to design a property routing protocol to prolong the lifetime of the network needs to be addressed. This paper mainly studied the typical hierarchical routing protocol such as LEACH better in the saving energy cost. However the distribution of cluster heads in LEACH is uneven, LEACH-E-D protocol is proposed. In order to make the energy distribute more evenly among different nodes, we improve the tradition equation used for selecting cluster heads with considering the nodes’ Energy (E) and the average distance of the temporary cluster (D). Meanwhile, we propose to establish temporary cluster heads by E and final cluster heads by D, which aims to balance network load and prolong the lifetime. Simulations through OMNET++ 4.0 show that our improved protocol –LEACH-E-D performs better than the LEACH.

Efficient Clustering Technique for Cooperative Wireless Sensor Network

The nodes of a wireless sensor network (WSN) collect the data of interest from the deployment area and cooperatively send it to sink in multiple hops. Recently, virtual multiple input multiple output (V-MIMO) technique has been introduced in which the node cooperation is extended to form a virtual antenna array and communication is accomplished using space time block coding. The present work extends the scope of VMIMO by proposing a new clustering technique. It creates the temporary cluster heads and their respective cooperative nodes, collects information from them and then the final clustering is accordingly done. The simulation result shows significant improvement in the energy efficiency of the WSN.

Performance Analysis of a Cluster-Based MAC Protocol for Wireless Ad Hoc Networks

An analytical model to evaluate the non-saturated performance of the Distributed Queuing Medium Access Control Protocol for Ad Hoc Networks (DQMANs) in single-hop networks is presented in this paper. DQMAN is comprised of a spontaneous, temporary, and dynamic clustering mechanism integrated with a near-optimum distributed queuing Medium Access Control (MAC) protocol. Clustering is executed in a distributed manner using a mechanism inspired by the Distributed Coordination Function (DCF) of the IEEE 802.11. Once a station seizes the channel, it becomes the temporary clusterhead of a spontaneous cluster and it coordinates the peer-to-peer communications between the clustermembers. Within each cluster, a near-optimum distributed queuing MAC protocol is executed. The theoretical performance analysis of DQMAN in single-hop networks under non-saturation conditions is presented in this paper. The approach integrates the analysis of the clustering mechanism into the MAC layer model. Up to the knowledge of the authors, this approach is novel in the literature. In addition, the performance of an ad hoc network using DQMAN is compared to that obtained when using the DCF of the IEEE 802.11, as a benchmark reference.