oa Analysis Of Energy Consumption Fairness In Video Sensor Networks

The use of more effective processing tools such as advanced video codecs in wireless sensor networks (WSNs) has enabled widespread adoption of video-based WSNs for monitoring and surveillance applications. Considering that in video-based WSN applications large amounts of energy resources are required for both compression and transmission of video content, optimizing the energy consumption is of paramount importance. There is a trade-off between the encoding complexity and compression performance in the sense that high compression efficiency comes at the expense of increased encoding complexity. On the other hand, there is a direct relationship between coding complexity and energy consumption. Since the nodes in a video sensor network (VSN) share the same wireless medium, there is also an issue with fairness of bandwidth allocation per each node. Nevertheless, the fairness of resource allocation (encoding and transmission energy) for nodes placed at different locations in VSNs has a significant effect on energy consumption. In our study, our objective is to maximize the lifetime of the network by reducing the consumption of the node with the maximum energy usage. Our research focuses on VSNs with linear topology where the nth node relays its data through the nth-1 node, and the node closest to the sink relays information from all the other nodes. In our approach, we analyze the relation between the fairness of nodes' resource allocation, video quality and VSNs' energy consumption to propose an algorithm for adjusting the coding parameters and fairness ratio of each node such that energy consumption is balanced. Our results show that by allocating higher fairness ratios to the closest nodes to the sink, we reduce the maximum energy consumption and achieve a more balanced energy usuge. For instance, in the case of a VSN with six nodes, by allocating the fairness ratios between 0.17 to 0.3 to the closer nodes to the sink, the maximum energy consumption is reduced by 11.28%, with standard deviation of nodes' energy consumption (STDen) of 0.09W compared to 0.25W achieved by the maximum fairness scheme.