Network Lifetime Aware Routing Algorithm for Energy Harvesting Wireless Sensor Networks

Author(s):  
Amena Zahan Prithibi ◽  
Syeda Kanij Faria ◽  
Palash Roy ◽  
Md. Abdur Razzaque
2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Sohail Jabbar ◽  
Rabia Iram ◽  
Muhammad Imran ◽  
Awais Ahmad ◽  
Anand Paul ◽  
...  

Network lifetime is one of the most prominent barriers in deploying wireless sensor networks for large-scale applications because these networks employ sensors with nonrenewable scarce energy resources. Sensor nodes dissipate most of their energy in complex routing mechanisms. To cope with limited energy problem, we present EASARA, an energy aware simple ant routing algorithm based on ant colony optimization. Unlike most algorithms, EASARA strives to avoid low energy routes and optimizes the routing process through selection of least hop count path with more energy. It consists of three phases, that is, route discovery, forwarding node, and route selection. We have improved the route discovery procedure and mainly concentrate on energy efficient forwarding node and route selection, so that the network lifetime can be prolonged. The four possible cases of forwarding node and route selection are presented. The performance of EASARA is validated through simulation. Simulation results demonstrate the performance supremacy of EASARA over contemporary scheme in terms of various metrics.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianpo Li ◽  
Xue Jiang ◽  
I-Tai Lu

Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.


2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668968 ◽  
Author(s):  
Sunyong Kim ◽  
Chiwoo Cho ◽  
Kyung-Joon Park ◽  
Hyuk Lim

In wireless sensor networks powered by battery-limited energy harvesting, sensor nodes that have relatively more energy can help other sensor nodes reduce their energy consumption by compressing the sensing data packets in order to consequently extend the network lifetime. In this article, we consider a data compression technique that can shorten the data packet itself to reduce the energies consumed for packet transmission and reception and to eventually increase the entire network lifetime. First, we present an energy consumption model, in which the energy consumption at each sensor node is derived. We then propose a data compression algorithm that determines the compression level at each sensor node to decrease the total energy consumption depending on the average energy level of neighboring sensor nodes while maximizing the lifetime of multihop wireless sensor networks with energy harvesting. Numerical simulations show that the proposed algorithm achieves a reduced average energy consumption while extending the entire network lifetime.


2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Gong Chen ◽  
Liansheng Tan ◽  
Yanlin Gong ◽  
Wei Zhang

An important performance concern for wireless sensor networks (WSNs) is the total energy dissipated by all the nodes in the network over the course of network lifetime. In this paper, we propose a routing algorithm termed as PCA-guided routing algorithm (PCA-RA) by exploring the principal component analysis (PCA) approach. Our algorithm remarkably reduces energy consumption and prolongs network lifetime by realizing the objective of minimizing the sum of distances between the nodes and the cluster centers in a WSN network. It is demonstrated that the PCA-RA can be efficiently implemented in WSNs by forming a nearly optimalK-means-like clustering structure. In addition, it can decrease the network load while maintaining the accuracy of the sensor measurements during data aggregating process. We validate the efficacy and efficiency of the proposed algorithm by simulations. Both theoretical analyses and simulation results demonstrate that this algorithm can perform significantly with less energy consumption and thus prolong the system lifetime for the networks.


2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
M. Kalpana ◽  
R. Dhanalakshmi ◽  
P. Parthiban

This research work proposes a mathematical model for the lifetime of wireless sensor networks (WSN). It also proposes an energy efficient routing algorithm for WSN called hierarchical energy tree based routing algorithm (HETRA) based on hierarchical energy tree constructed using the available energy in each node. The energy efficiency is further augmented by reducing the packet drops using exponential congestion control algorithm (TCP/EXP). The algorithms are evaluated in WSNs interconnected to fixed network with seven distribution patterns, simulated in ns2 and compared with the existing algorithms based on the parameters such as number of data packets, throughput, network lifetime, and data packets average network lifetime product. Evaluation and simulation results show that the combination of HETRA and TCP/EXP maximizes longer network lifetime in all the patterns. The lifetime of the network with HETRA algorithm has increased approximately 3.2 times that of the network implemented with AODV.


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