Game of energy consumption balancing in heterogeneous sensor networks

Abstract

In a multi-hop sensor network, sensors largely rely on other nodes as a traffic relay to communicate with targets that are not reachable by one hop. Depending on the topology and position of nodes, some sensors receive more relaying traffic and lose their energy faster. Such imbalanced energy consumption may lead to server problems like network partitioning. In this paper, we study the problem of energy consumption balancing (ECB) in heterogeneous sensor networks by assuming general any-to-any traffic pattern. We consider both factors of transmission power and forwarding load in measuring energy consumption. To find a solution, we formulate the problem as a strategic network formation game with a new utility function. We show that this game is guaranteed to converge to strongly connected topologies which have better ECB and bounded inefficiency. We propose a localized algorithm in which every node knows only about its k-hop neighbourhood. Through simulations on uniform and clustered networks with various densities, we show that the performance of our algorithm is comparable with global and centralized algorithms.

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“…Motivated by GT, in this article, it is used to allocate the MNs in the cross coverages to different CHs. Next, we plan to use GT 6,20 to model and address the situation. Additionally, before the nodes' allocation in the cross coverages, the number and the distribution of the CHs are first considered for the purpose of achieving higher performance of the WSNs.…”

A Fuzzy Data Fusion Solution to Enhance the QoS and the Energy Consumption in Wireless Sensor Networks

“…Home automation, health, industry, and road monitoring are some examples of application fields [1]. In recent studies, conducted in various scenarios, in which WSNs are applied, researchers accomplished that WSNs design has to meet specific features, such as low implementation cost [2], scalability [3], low power consumption [4], Quality of Service [5], and real-time constraints satisfaction [6].…”