Energy Aware SEP Based on Dual Cluster Heads and Dual Sink Approach in WSN

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

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Low Loss Energy-Aware Routing Protocol for Data Gathering Applications in Wireless Sensor Network

Internet and Distributed Computing Advancements ◽

10.4018/978-1-4666-0161-1.ch011 ◽

2012 ◽

pp. 272-302

Author(s):

Basma M. Mohammad El-Basioni ◽

Sherine M. Abd El-Kader ◽

Hussein S. Eissa ◽

Mohammed M. Zahra

Keyword(s):

Routing Protocol ◽

Packet Loss ◽

Data Gathering ◽

Wireless Sensor ◽

Low Loss ◽

Energy Aware ◽

Cluster Heads ◽

Energy Aware Routing ◽

Quality Of Service Parameters

But, as the energy-efficiency is critical for periodical data gathering applications in wireless sensor networks, it has the highest priority in algorithms design; also the latency, packet loss, and throughput are important factors and should be addressed. This chapter proposes a routing protocol inspired by an energy-efficient cluster-based routing protocol called Energy-Aware Routing Protocol (EAP). The new enhanced protocol that is called Low Loss Energy-Aware Routing Protocol (LLEAP) enhances the performance of EAP in terms of some quality of service parameters by adding a second iteration for constructing the tree structure for multi-hop communication among cluster heads, by modifying the used weights of the cluster heads and parent node selection, and finally by selecting suitable aggregation method to decrease losses and delay. Simulation results showed that LLEAP significantly outperforms EAP in terms of packet loss percentage by on average 93.4%.

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An Improved Energy-Aware Cluster Heads Selection Method for Wireless Sensor Networks Based on K-means and Binary Particle Swarm Optimization

Lecture Notes in Computer Science - Advances in Swarm Intelligence ◽

10.1007/978-3-319-11897-0_15 ◽

2014 ◽

pp. 125-134 ◽

Cited By ~ 3

Author(s):

Qianqian Pan ◽

Qingjian Ni ◽

Huimin Du ◽

Yiyun Yao ◽

Qing Lv

Keyword(s):

Wireless Sensor Networks ◽

Particle Swarm Optimization ◽

Sensor Networks ◽

Particle Swarm ◽

Selection Method ◽

Wireless Sensor ◽

Binary Particle Swarm Optimization ◽

Energy Aware ◽

Swarm Optimization ◽

Cluster Heads

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Energy Efficiency Analysis in ERA using NFL-BA Algorithm

International Journal of Scientific Research in Science and Technology ◽

10.32628/ijsrst207477 ◽

2020 ◽

pp. 340-348

Author(s):

Palky Mehta ◽

H. L. Sharma

Keyword(s):

Cluster Head ◽

Vital Role ◽

Wireless Sensor ◽

Energy Usage ◽

Cluster Heads ◽

Comparison Results ◽

Current Scenario ◽

Energy Efficiency Analysis ◽

Selection Of

In the current scenario of Wireless Sensor Network (WSN), power consumption is the major issue associated with nodes in WSN. LEACH technique plays a vital role of clustering in WSN and reduces the energy usage effectively. But LEACH has its own limitation in order to search cluster head nodes which are randomly distributed over the network. In this paper, ERA-NFL- BA algorithm is being proposed for selects the cluster heads in WSN. This algorithm help in selection of cluster heads can freely transform from global search to local search. At the end, a comparison has been done with earlier researcher using protocol ERA-NFL, which clearly shown that proposed Algorithm is best suited and from comparison results that ERA-NFL-BA has given better performance.

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