Network Connectivity under Probabilistic Communication Models in Wireless Sensor Networks

Hefeeda, Mohamed; Ahmadi, Hossein

doi:10.1109/mobhoc.2007.4428600

Cited by 12 publications

(6 citation statements)

References 19 publications

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“…It will suffer from extremely low network reachability. Very interesting, a recent work [15] also noticed the impact of lossy links to the topology control. The authors studied the network reachability (but a different term) using the probabilistic model instead of the traditional deterministic model.…”

Section: Related Workmentioning

confidence: 97%

Opportunity-Based Topology Control in Wireless Sensor Networks

Liu

Zhang

2010

IEEE Trans. Parallel Distrib. Syst.

110

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Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either "connected" or "disconnected." These approaches are called connectivity-based topology control. In real environments, however, there are many intermittently connected wireless links called lossy links. Taking a succeeded lossy link as an advantage, we are able to construct more energy-efficient topologies. Toward this end, we propose a novel opportunity-based topology control. We show that opportunity-based topology control is a problem of NP-hard. To address this problem in a practical way, we design a fully distributed algorithm called CONREAP based on reliability theory. We prove that CONREAP has a guaranteed performance. The worst running time is OðjEjÞ, where E is the link set of the original topology, and the space requirement for individual nodes is OðdÞ, where d is the node degree. To evaluate the performance of CONREAP, we design and implement a prototype system consisting of 50 Berkeley Mica2 motes. We also conducted comprehensive simulations. Experimental results show that compared with the connectivity-based topology control algorithms, CONREAP can improve the energy efficiency of a network up to six times.Index Terms-Topology control transitional region network reachability.

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Section: Related Workmentioning

confidence: 97%

Opportunity-Based Topology Control in Wireless Sensor Networks

Liu

Zhang

2010

IEEE Trans. Parallel Distrib. Syst.

110

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“…In order to improve the coverage and connectivity of the network effectively, References [15] used a mobile node Mules to optimize the topology of UWSN. A topology control algorithm PCMP was proposed in References [16] to optimize the connectivity and coverage of underwater wireless sensor networks, and the data packet transmission rate between nodes was used to calculate and determine the connectivity probability of the nodes. However, the underwater sensor node is influenced by uncertain factors such as water flow and fish swarm, making the original network failed locally and the network paralyzed, thus the robustness of the network topology is poor.…”

Section: Related Workmentioning

confidence: 99%

“…As shown in Table 2, Each node i calculates its own number k of neighbors according to the set R of neighbor nodes, builds its sub-graph matrix i G of weight link set i W from Formula (12) and (13), and determines whether the link set it builds satisfies the construction of a rigid matrix based on Definition 4-6 and Lemma 2. If so, a rigid matrix M can be constructed from Formula (14) - (16), and an optimal subrigid matrix c M will be constructed according to Property 3. Finally, the link set D to be deleted can be obtained from the optimal rigid sub-graph matrix, using which, the neighbor node set R of each node can be updated.…”

Section: Redundant Link Deletion Stagementioning

confidence: 99%

Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Wei

Han

2020

IEEE Access

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Aiming at the problems of unbalanced energy consumption, redundant links, short life cycle in underwater sensor networks, a topology control algorithm for underwater wireless sensor networks based on potential-game and optimal rigid sub-graph is proposed. Firstly, based on the potential game theory, the topology control model of underwater sensor network is constructed, which considers network coverage, connectivity, transmission energy consumption, end-to-end delay, transmission success rate, node residual energy and so on. It is proved that the model is an ordinal potential game and has a Nash equilibrium solution. Then, the link weight function of node load and node residual energy is introduced, and the redundant links in the network are eliminated by using the principle of optimal rigid sub-graph.Simulation experiments and contrast analysis show that compared with other network models, the network topology model constructed in this paper has lowed node load and stronger energy balance, prolongs the life cycle of the network and more conforms to the underwater environment. INDEX TERMS redundant links, topology control, potential-game, optimal rigid sub-graph, life cycle.

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“…Notice that [11] does not need location information such as [16]. Very interesting, a recent work [13] also noticed the impact of lossy links to the topology control. The authors studied the network reachability (but a different term) using the probabilistic model instead of the traditional deterministic model.…”

Section: Related Workmentioning

confidence: 99%

Opportunity-Based Topology Control in Wireless Sensor Networks

Liu

Zhang

2008

2008 the 28th International Conference on Distributed Computing Systems

View full text Add to dashboard Cite

Topology control is an effective method to improve the energy efficiency of wireless sensor networks (WSNs). Traditional approaches are based on the assumption that a pair of nodes is either "connected" or "disconnected". These approaches are called connectivity-based topology control. In real environments however, there are many intermittently connected wireless links called lossy links. Taking a succeeded lossy link as an advantage, we are able to construct more energy-efficient topologies. Towards this end, we propose a novel opportunity-based topology control. We show that opportunity-based topology control is a problem of NPhard. To address this problem in a practical way, we design a fully distributed algorithm called CONREAP based on reliability theory. We prove that CONREAP has a guaranteed performance. The worst running time is O(|E|) where E is the link set of the original topology, and the space requirement for individual nodes is O(d) where d is the node degree. To evaluate the performance of CONREAP, we design and implement a prototype system consisting of 50 Berkeley Mica2 motes. We also conducted comprehensive simulations. Experimental results show that compared with the connectivity-based topology control algorithms, CONREAP can improve the energy efficiency of a network up to 6 times.

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Network Connectivity under Probabilistic Communication Models in Wireless Sensor Networks

Abstract: Abstract

Cited by 12 publications

References 19 publications

Opportunity-Based Topology Control in Wireless Sensor Networks

Opportunity-Based Topology Control in Wireless Sensor Networks

Topology Control Algorithm of Underwater Sensor Network Based on Potential-Game and Optimal Rigid Sub-Graph

Opportunity-Based Topology Control in Wireless Sensor Networks

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