Virtual position based geographic routing for wireless sensor networks

You, Jiaxi; Han, Qi; Lieckfeldt, Dominik; Salzmann, Jakob; Timmermann, Dirk

doi:10.1016/j.comcom.2009.12.007

Cited by 16 publications

(20 citation statements)

References 14 publications

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“…When the density of deployment is low, voids appear frequently in the network [3]. This metric illustrates the ability of avoiding routing hole of greedy-PViP.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…A geographic routing method usually combines a geographic greedy forwarding with a recovery mechanism to solve the local minimum problem. This problem is generally resolved through combining greedy forwarding with the well known face routing [3]. Although face routing necessitates a node to communicate with its neighbors to establish a planarized graph and construct routes to traverse around the void.…”

Section: Related Workmentioning

confidence: 99%

“…• Average end-to-end delay: This is defined as the average hop count of packets from their source to the destination [3]. Given the same success rate, small packet delay (in hops) represents better performance in terms of routing efficiency and energy consumption.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…This needs information exchange between the neighbors and increases the protocol overhead. Geographic routing strategies thus normally operate in two modes: Greedy forwarding mode and void handling mode [3]. In the greedy-forwarding mode, selection of a next hop node for packet forwarding is performed according to the position of the sender node, its one-hop neighbors, and the destination node.…”

Section: Related Workmentioning

confidence: 99%

“…If an intermediate node is unable to locate a neighbor with positive progress towards the destination node, it switches to the void bypassing mode. In [3], the authors present an algorithm, called Greedy virtual position (Greedy-ViP) for void-bypassing that uses position of all node's direct neighbors coordinate for computing virtual position of nodes. Our proposed scheme improves the performance of this protocol.…”

Section: Related Workmentioning

confidence: 99%

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Positive virtual based geographic routing for wireless sensor networks

Ghaffari

Bahanfar

2012

IEICE Electron. Express

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Communications void in geographical routing protocols effects the performance of these routing protocols. A geographic routing protocol usually uses a greedy forwarding scheme with a recovery policy to solve the void problem. In this paper, we propose a new positive virtual position (PViP) scheme, for solving the local minimum problem. Positive virtual position of nodes are considered when selecting the next optimum neighbor node. Positive virtual position of a node is the average positions of node's itself position and all single-hop neighbor nodes that are closer to the sink than itself. Simulation results demonstrate that proposed scheme increases the success delivery rate compared with other schemes without any significant overhead.

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“…When the density of deployment is low, voids appear frequently in the network [3]. This metric illustrates the ability of avoiding routing hole of greedy-PViP.…”

Section: Performance Evaluationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Positive virtual based geographic routing for wireless sensor networks

Ghaffari

Bahanfar

2012

IEICE Electron. Express

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A Geography-Based Void-Bypassing Routing Protocol for Wireless Sensor Network

Fan

Wei

2016

Wireless Pers Commun

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Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition

Konstantinidis

Yang

2011

Computer Communications

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a b s t r a c tThe K-connected Deployment and Power Assignment Problem (DPAP) in WSNs aims at deciding both the sensor locations and transmit power levels, for maximizing the network coverage and lifetime objectives under K-connectivity constraints, in a single run. Recently, it is shown that the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is a strong enough tool for dealing with unconstraint real life problems (such as DPAP), emphasizing the importance of incorporating problem-specific knowledge for increasing its efficiency. In a constrained Multi-objective Optimization Problem (such as K-connected DPAP), the search space is divided into feasible and infeasible regions. Therefore, problem-specific operators are designed for MOEA/D to direct the search into optimal, feasible regions of the space. Namely, a DPAP-specific population initialization that seeds the initial solutions into promising regions, problem-specific genetic operators (i.e. M-tournament selection, adaptive crossover and mutation) for generating good, feasible solutions and a DPAP-specific Repair Heuristic (RH) that transforms an infeasible solution into a feasible one and maintains the MOEA/D's efficiency simultaneously. Simulation results have shown the importance of each proposed operator and their interrelation, as well as the superiority of the DPAP-specific MOEA/D against the popular constrained NSGA-II in several WSN instances.

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Virtual position based geographic routing for wireless sensor networks

Cited by 16 publications

References 14 publications

Positive virtual based geographic routing for wireless sensor networks

Positive virtual based geographic routing for wireless sensor networks

A Geography-Based Void-Bypassing Routing Protocol for Wireless Sensor Network

Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition

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