In LEACH, the minimum amplification energy required for inter cluster or Cluster head to Base station communication and amplification energy required for cluster members to cluster head transmission is identical. As a result packet drop ratio increases. The collisions or interference for other signals also increases. LEACH chosen its cluster heads periodically and distributes energy consumed uniformly by rotation. If we apply heterogeneity in this protocol it gives poor performance and less efficiency. To get an another chance to became a Cluster Head (CH) for next 1/p rounds is very difficult once a CH is formed. For every round, cluster heads are replaced and whole design of the protocol is changed. Basing on the mode of functioning, WSNs can be classified into proactive, reactive and hybrid networks. Reactive networks, respond immediately basing on the decision parameters. Our proposed protocol Enhanced Modified LEACH (EMODLEACH) is a reactive protocol which is implemented in homogeneous network model. We have implemented the concept of Efficient Cluster head Replacement scheme (ECHR)and Dual transmitting power level (DTP) of MODLEACH along with the concept of Efficient Intra Cluster transmission Scheme of TEEN.

Enhanced modified LEACH (EMODLEACH) protocol for WSN

This work proposes an approach for improving energy-efficiency and thus increasing network lifetime in wireless sensor network (WSN) using a logical energy tree (LET). In our scheme, LET is constructed using the remaining available energy in each node. Two routing algorithms are framed based on LET: one with centralized sink node called LETCSN and the other with centralized sink node and secondary sink nodes called LETSSN. sensor nodes are deployed in some fixed patterns. A mathematical model is devised to understand the effect of node deployment pattern on improving network lifetime. Both proposed routing algorithms are evaluated with seven different deployment patterns, simulated in ns-2 and are compared with the existing classic algorithms based on the number of data packets, throughput, network lifetime, and data packet's average network lifetime product. Our evaluation and simulation results show that LETSSN maximizes the network lifetime for all node-deployment patterns taken into consideration.

Prolonging the lifetime of wireless sensor networks using secondary sink nodes

This research expands the scope of wireless sensor network (WSN) optimization from single objective to multi objective optimization. It introduces a WSN's energy-aware and coverage preserve hierarchal clustering and routing model based on multi-objective bat swarm optimization algorithm. Two objectives are taken into consideration; coverage and nodes residual energies. The proposed model optimizes the WSN by selecting the best fitting set of nodes as cluster heads. It works to maximize the WSN's coverage and to minimize the nodes' consumed energy. This minimizes the number of active cluster heads while preserving a higher percentage of the covered nodes in WSN. It extends the longevity of the WSN's lifetime and achieves good functioning reliability. The proposed optimization model overcomes the WSN's coverage and lifetime challenges. The proposed model outperforms the LEACH routing and clustering protocol.

WSN's energy-aware coverage preserving optimization model based on multi-objective bat algorithm

A Wireless Sensor Network (WSN) is an interdisciplinary discipline of sensing, electronics and wireless communication employed widely in environmental monitoring and surveillance applications. The sensor nodes are generally tiny and made of irreplaceable power source and limited capacity for computing, communication, and storage. The power constraint necessitates that the WSN routing protocols conserve energy as critical factor to maximize the network lifetime. Cluster-based approaches are popularly used for its energy efficiency where some nodes designated as Cluster Heads (CHs) organize WSNs for data aggregation and energy saving. The CH is responsible for gathering data from the cluster nodes and conveying it to the base station due to which higher energy drain occurs at CH leading to uneven network degradation. Thus, the selection of CH is critical for improving the WSN performance and lifetime. In this paper, a hybrid Shuffled Frog Leaping Algorithm (AASFLA) with antipredator capabilities to avoid the local minima is proposed. Results show avoidance of suboptimal solution compared to SFLA and particle swarm optimization.

Antipredator Adaptation Shuffled Frog Leap Algorithm to Improve Network Life Time in Wireless Sensor Network

Challenges of wireless sensor networks under-optimization in field of research have been globally concerned. Generally, lifetime extension is still considered to be the most dominant challenge for WSNs. Clustering and routing protocols have been proposed as optimization solutions to extend WSNs lifetime. In this paper, we introduce a newly meta-heuristic population based soft computing algorithm as an optimization technique to extend the WSNs lifetime. The proposed technique applies the population-based metaheuristic bat swarm optimization algorithm. It optimizes the network as a nonlinear problem to select the optimum cluster head nodes across number of generations. The objective; fitness function, employed to minimize the intra-cluster compactness with minimum distance between nodes in same cluster. The proposed technique is simulated and applied into four different wireless sensor networks deployments and compared with the LEACH hierarchal clustering and routing protocol. Results show that this proposed technique outperforms the classical LEACH. It efficiently optimizes the selection of cluster head nodes that ensure optimum coverage and connectivity based on intra-cluster distances. This reduces the energy consumption on each node level and hence increases the lifetime for each node, causing a significant extension in the wireless sensor network lifetime. The comparison between the hard or crisp LEACH routing and the soft or elastic proposed routing technique boasts the performance even more. The paper introduces a performance numerical analysis with the metrics of number of packets sent to sink, number of dead nodes, sum of WSN energy and the network lifetime.

https://www.ijsr.net/archive/v3i5/MDIwMTMxNzEx.pdf

Bat Swarm Algorithm for Wireless Sensor Networks Lifetime Optimization

The data transfer of wireless sensor network (WSN) can not be separated with routing protocol, Energy efficiency is one of the most important factors in wireless sensor networks. In this paper based on the uneven distribution of the LEACH cluster head and the different lengths and base station communications, we present a improved LEACH algorithm which refers to remaining energy and optimal cluster heads. Computer simulation using NS2 reveals that the proposed protocol reduces the energy consumption compared with the existing LEACH protocol.

Research and Improvement of LEACH Protocol for Wireless Sensor Networks

Energy efficiency is a critical issue for sensornetwork. In this paper, we propose an energy efficient context adaptive MAC protocol for wireless sensor networks. The existing approaches try to minimize energy consumption by controlling the duty cycle of transmission period. The New-MAC forecast energy according to the Markov chain, then adjusts the duty cycle through the energy size, then adjusts the duty cycle through the energy size. Computer simulation using NS2 reveals that the proposed protocol significantly reduces the energy consumption compared with the existing S-MAC.

The Research of MAC Protocol Based on Fire System for Wireless Sensor Networks

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Research and Improvement of LEACH Protocol for Wireless Sensor Networks

The Research of MAC Protocol Based on Fire System for Wireless Sensor Networks