Energy Efficient Shortest Path Routing Protocol for Wireless Sensor Networks

Shivaprakasha, K. S.; Kulkarni, Muralidhar

doi:10.1109/cicn.2011.70

Cited by 12 publications

(11 citation statements)

References 14 publications

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“…Shortest path routing protocol [23] has been one of the easiest algorithm used for finding the best possible route which is shorter in terms of number of hops. A slight modification in the existing algorithm is done to find the energy efficient routes [14]. In EESP [14] route computation is based not only on the distance but also on the residual energy in the nodes.…”

Section: 4energy Efficient Shortest Path Routing Protocolmentioning

confidence: 99%

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Role of Parameters in Different Energy Efficient Routing Protocols in MANETs

Bagga¹,

Singh²,

Gupta³

2016

IJCA

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A mobile adhoc network is a dynamically reconfigured wireless network with no fixed infrastructure. Highly dynamic and distributed nature of the MANETs makes routing a major issue. The high mobility of the nodes results in rapid changes in the routes, thus routing in MANETs consumes huge amount of power and bandwidth and undergoes frequent topology changes to which it adjusts quickly. Energy becomes an important issue in mobile adhoc networks since mobile nodes will be powered by batteries with certain specified capacity. Hence there have been various energy efficient routing protocols which minimize the active communication energy or inactive energy. There are various parameters used by energy efficient protocols to find the best energy rich routes. The purpose of this paper is to summarize different parameters used by protocols to keep the network functioning as long as possible. These parameters are used to compare the energy utilized in various available routes, thus choosing the best route with minimum energy consumption to increase overall network lifetime as much as possible with less battery consumption at each node.

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Section: 4energy Efficient Shortest Path Routing Protocolmentioning

confidence: 99%

“…A slight modification in the existing algorithm is done to find the energy efficient routes [14]. In EESP [14] route computation is based not only on the distance but also on the residual energy in the nodes.…”

Section: 4energy Efficient Shortest Path Routing Protocolmentioning

confidence: 99%

Role of Parameters in Different Energy Efficient Routing Protocols in MANETs

Bagga¹,

Singh²,

Gupta³

2016

IJCA

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“…Both ETX and node energy is used to select between parent nodes of equal hop-count in [9]. The residual-energy is included as a denominator in the additive distance metric in [10]. Using it as in the denominator makes the cost of a node increase toward infinity as energy approaches zero.…”

Section: Related Workmentioning

confidence: 99%

Energy Balancing Algorithms in Wireless Sensor Networks

Fojcik¹,

Øvsthus²,

Kure

2015

Annals of Computer Science and Information Systems

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Abstract-The energy consumption in Wireless Sensor Networks, WSN, need to be balanced in order to avoid early depletion of nodes. In this paper we use a common context to analyze a broad range of the energy balancing algorithms suggested in literature. In addition we suggest three new algorithms to complete the range. Altogether, nine different balancing techniques are analyzed. We focuses on networks running the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) routing protocol. Our simple change in RPL's parent selection procedure can give a significant balancing effect without any increase in management cost. However, the best balancing algorithm is when the nodes exchange residual-energy information to ensure forwarding through the highest residual-energy nexthop node. The increased information exchange implies increased management cost due to the amount of information transmitted and added computational load.

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“…CH selects the members for the cluster based on the energy and the distance from itself. Although EEAODV [18] was proved to perform better, it has been still improved by assigning the job of route establishment to the BS in Optimal Path Energy Efficient Routing (OPEER) [35]. As the BS is not energy constrained, it can be over burdened without affecting the network performance.…”

Section: Related Workmentioning

confidence: 99%

“…Also some of the papers [25,31,35,37,38] have considered a centralized approach where BS does the job of CH selection. However most of the algorithms do not consider dynamic thresholds.…”

Section: Related Workmentioning

confidence: 99%

Improved network survivability using multi-threshold adaptive range clustering (M-TRAC) algorithm for energy balancing in wireless sensor networks

Shivaprakasha

Kulkarni

Joshi

2013

Journal of High Speed Networks

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Wireless Sensor Networks (WSNs) have become one of the most prominent areas of research in the field of modern communication systems. But unlike IP based routing, WSNs focus on data centric communication. Thus routing is one of the important issues to be considered for a WSN. As sensor networks are generally deployed in hostile environments, batteries cannot be recharged often. Thus energy conservation is one of the important design parameters for WSNs. Many energy aware routing protocols were proposed in the literature. Cluster based algorithms were proved to be better compared to multi-hop routing. In this paper an attempt is made in proposing a novel cluster based energy efficient routing algorithm for WSNs namely the Multi-Threshold Adaptive Range Clustering (M-TRAC) algorithm, which incorporates centralized network management with variable thresholds in order to assure a uniform load distribution amongst nodes, thus improving the network lifetime.

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Energy Efficient Shortest Path Routing Protocol for Wireless Sensor Networks

Cited by 12 publications

References 14 publications

Role of Parameters in Different Energy Efficient Routing Protocols in MANETs

Role of Parameters in Different Energy Efficient Routing Protocols in MANETs

Energy Balancing Algorithms in Wireless Sensor Networks

Improved network survivability using multi-threshold adaptive range clustering (M-TRAC) algorithm for energy balancing in wireless sensor networks

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