A genetic algorithm based approach for energy efficient routing in two-tiered sensor networks

Bari, Ataul; Wazed, S.; Jaekel, Arunita; Bandyopadhyay, Subir

doi:10.1016/j.adhoc.2008.04.003

Cited by 173 publications

(83 citation statements)

References 22 publications

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“…Lin et al [17] applied a genetic algorithm (GA) based approach to route selection and capacity flow assignment. A number of papers have demonstrated the usefulness of a GA based approach in sensor networks [18,19,20,21]. The work of [20] focused on deriving an energy efficient scheme that satisfy the required detection probability [21] using a distributed GA.…”

Section: Related Workmentioning

confidence: 99%

Real Time Routing Algorithm Based On NSGA-II in Wireless Mesh Networks

Routeh¹

2015

IJIRCCE

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ABSTRACT:With the growing demand for real time services in Wireless Networks, quality of service (QoS) based routing has emerged as an interesting research topic. But offering some QoS guarantee in wireless networks raises significant challenges. This paper presents a real time routing algorithm based on NSGA-II. This algorithm has been widely used in optimization problems. NSGA-II is a non-dominated sorting genetic algorithm which consists of multi objective functions. NSGA-II algorithm starts with a random population. Each individual in population is considered as a chromosome. Two objective functions were considered in this paper: (i) End to end delay, (ii) path reliability. Final solutions were sorted by Pareto front method. The wireless mesh network was modeled as an undirected graph, in which the sets of nodes N and links L represent computer sites and communication cables. Experimental results proved that the proposed NSGA-II routing algorithm can achieve better performance in compare of other well-known methods like Ad Hoc on Demand Distance Vector (AODV).

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Section: Related Workmentioning

confidence: 99%

Real Time Routing Algorithm Based On NSGA-II in Wireless Mesh Networks

Routeh¹

2015

IJIRCCE

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“…Finally once node density  is given, we can obtain the best hop length using equation (6) for each unknown nodes.…”

Section: Best Hop Length Computationmentioning

confidence: 99%

“…Until now many algorithms especially designed for WSNs environment have been proposed and can be sorted into range-based category [6], such as AoA (Angle of Arrival) measurement [7], ToA (Time of Arrival), TDoA (Time Difference of Arrival) [8,9], and RSS (Received Signal Strength) [10,11]. The RSS way is superior to the technologies based on TDOA, TOA and AOA [10].…”

Section: Introductionmentioning

confidence: 99%

Robust Localization Algorithm Based on Best Length Optimization for Wireless Sensor Networks

Zhang

et al. 2016

TELKOMNIKA

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“…In [17,[23][24][25], authors have focused on the upper tier of the network to find the routing schedule. It is assumed in their approach that the relay nodes (cluster heads) contain relatively high energy compared to normal sensor nodes, and these nodes are used throughout the network lifetime as cluster heads.…”

Section: Introductionmentioning

confidence: 99%

“…Selection of cluster head periodically and strategically can avoid such circumstances. Low Energy Adaptive Clustering Hierarchy (LEACH) [11,12], Hybrid Energy Efficient Distributed Clustering (HEED) [13], Energy Efficient Dynamic Clustering Algorithm (EEDCA) [26], Genetic Algorithm based Weighted Clustering Algorithm (GA-WCA) [27], and Location Aware 2 Dimensional Genetic Algorithm (LA2D-GA) [28] are algorithms for cluster head selection while GA based routing [23] and Minimum Hop Routing Model (MHRM) [17,25] are centralized routing algorithms for WSN available in the literature.…”

Section: Introductionmentioning

confidence: 99%

Synthesized Cluster Head Selection and Routing for Two Tier Wireless Sensor Network

Rana

Zaveri

2013

Journal of Computer Networks and Communications

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Large scale sensor networks can be efficiently managed by dividing them into several clusters. With the help of cluster heads, each cluster communicates using some routing schedule. It is essential to rotate the role of cluster heads in a cluster to distribute energy consumption if we do not have dedicated high energy cluster heads. Usually routing and cluster head selection for such networks have been separately solved. If cluster heads are selected with the consideration of routing and routing schedule is prepared with the consideration of selected cluster heads, it can help each other. We have proposed an integrated approach of cluster head selection and routing in two tier wireless sensor network (WSN) using Genetic Algorithm based cluster head selection with A-Star algorithm based routing method to extend life of WSN. This approach can lead to significant improvements in the network lifetime over other techniques.

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A genetic algorithm based approach for energy efficient routing in two-tiered sensor networks

Cited by 173 publications

References 22 publications

Real Time Routing Algorithm Based On NSGA-II in Wireless Mesh Networks

Real Time Routing Algorithm Based On NSGA-II in Wireless Mesh Networks

Robust Localization Algorithm Based on Best Length Optimization for Wireless Sensor Networks

Synthesized Cluster Head Selection and Routing for Two Tier Wireless Sensor Network

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