Strong Minimum Interference Topology for Wireless Sensor Networks

Panda, B. S.; Shetty, D. Pushparaj

doi:10.1007/978-3-642-29280-4_43

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…In Figure 1, we have shown average interference of our heuristic and compare it with the algorithm improved SMIT [9]. In Table 6.1, we have shown the comparison of the total interference between our heuristic and the algorithm proposed in [9]. These experimental results demonstrate that our heuristic outperform existing algorithm.…”

Section: Resultsmentioning

confidence: 85%

“…We have taken average value of the total interference of the nodes in the network. In Figure 1, we have shown average interference of our heuristic and compare it with the algorithm improved SMIT [9]. In Table 6.1, we have shown the comparison of the total interference between our heuristic and the algorithm proposed in [9].…”

Section: Resultsmentioning

confidence: 99%

“…Their algorithm works for many connectivity predicate like simple connectivity, strong connectivity, broadcast, k-edge(vertex) connectivity, spanner, and so on. They also proved that any polynomial time α-approximation algorithm for minimum total range assignment problem with connectivity predicate P can be used for designing a polynomial time α-approximation algorithm for minimum total interference problem for P. Panda and Shetty [9] considered 2D networks with sender centric model and proposed an optimal solution for minimizing the maximum interference and a 2-factor approximation algorithm for average interference. Moscibroda and Wattenhofer [8] proposed O(log n)-factor greedy algorithm for minimizing average interference.…”

Section: Related Workmentioning

confidence: 99%

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Improved Interference in Wireless Sensor Networks

Agrawal

Das

2013

Distributed Computing and Internet Technology

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Given a set V of n sensor node distributed on a 2-dimensional plane and a source node s ∈ V, the interference problem deals with assigning transmission range to each v ∈ V such that the members in V maintain connectivity predicate P, and the maximum/total interference is minimum. We propose algorithm for both minimizing maximum interference and minimizing total interference of the networks. For minimizing maximum interference we present optimum solution with running time O((Pn + n 2 ) log n) for connectivity predicate P like strong connectivity, broadcast (s is the source), k-edge(vertex) connectivity, spanner, where O(Pn) is the time complexity for checking the connectivity predicate P. The running time of the previous best known solution was O(Pn × n 2 ) [3]. For the minimizing total interference we propose optimum algorithm for the connectivity predicate broadcast. The running time of the propose algorithm is O(n). For the same problem, the previous best known result was 2(1 + ln(n − 1))-factor approximation algorithm [3]. We also propose a heuristic for minimizing total interference in the case of strongly connected predicate and compare our result with the best result available in the literature. Experimental results demonstrate that our heuristic outperform existing result.

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Section: Resultsmentioning

confidence: 85%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Improved Interference in Wireless Sensor Networks

Agrawal

Das

2013

Distributed Computing and Internet Technology

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“…Owing to the technical advantages of self‐organisation, rapid deployment, high‐fault tolerance, and strong concealment, WSN has been used in smart city [2], smart agriculture [3], and other fields widely. However, with the rapid development of WSN, the increasing number of nodes and the complexity of the application environment make communication interference among nodes [4] increasingly serious, which causes unnecessary energy consumption. Moreover, the limited battery energy makes WSN have a limited lifetime, and the data retransmission between nodes wastes more energy and also reduces the network lifetime.…”

Section: Introductionmentioning

confidence: 99%

Distributed resource allocation optimisation algorithm based on particle swarm optimisation in wireless sensor network

et al. 2020

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“…Bilò and Proietti [3] proposed an algorithm for minimizing the maximum Sender interference that gives an optimal solution and also studied the computational hardness of several minimization problems with some constraints on the connectivity predicate. Panda and Shetty [11] considered the two dimensional networks with sender centric model and proposed an algorithm for minimizing the maximum interference that gives an optimal solution. The authors also proposed a 2-factor approximation algorithm for minimizing the average interference.…”

Section: Introductionmentioning

confidence: 99%

Minimizing the maximum sender interference by deploying additional nodes in a Wireless Sensor Network

Shetty¹,

Lakshmi²

2019

ejgta

Self Cite

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Interference is one of the major challenges faced by communication networks. Since the interference leads to packet loss, packet collision and data re-transmission, higher the interference, higher is the energy consumption. Several algorithms were proposed for reducing the interference in a wireless sensor network (WSN). By deploying additional nodes at an appropriate position in a WSN, it is possible to reduce the interference. We propose an algorithm in which, the main objective is to reduce the maximum Sender interference by deploying the additional nodes in the network, while the connectivity of the network is preserved. We use the properties of Gabriel graph to achieve the reduction in interference. We present the simulation results which show the number of additional nodes to be deployed. The comparison of the maximum Sender interference obtained by the proposed algorithm with that of the Euclidean minimum spanning tree (MST) of the given network is presented through simulation. We show that the additional number of nodes required for deployment has an upper bound of n/2, where n is the number of nodes. We also compute the average reduction in Sender interference of the network for a various number of nodes.

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Strong Minimum Interference Topology for Wireless Sensor Networks

Cited by 6 publications

References 8 publications

Improved Interference in Wireless Sensor Networks

Improved Interference in Wireless Sensor Networks

Distributed resource allocation optimisation algorithm based on particle swarm optimisation in wireless sensor network

Minimizing the maximum sender interference by deploying additional nodes in a Wireless Sensor Network

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