Optimising the coding bit-rates and activity rates of sensor nodes is essential for the functionality and survival of wireless sensor networks as these rates not only affect the amount of information collected by the network, but also affect its power consumption. This study proposes a framework for joint coding bit-rates and activity rates optimisation (CARO) of sensor nodes in wireless visual sensor networks under limited energy constraints. The framework uses the concept of accumulative visual information (AVI) as a measure of the amount of visual information collected from a sensor node. The authors propose two optimisation algorithms for the following two cases: (I) networks with predetermined operation time, where algorithm CARO I maximises the AVI of the network over its predetermined operation time. (II) Best effort networks, where algorithm CARO II maximises the network operation time under constraints on the collected visual information. Simulations show that optimising the rates using CARO maximises the AVI of the network and extends its operation time compared to the straightforward solution when all nodes have equal activity rates. This is because the authors' framework takes into consideration that different nodes in different locations may operate under different conditions and collect information of different significance.

中文翻译：

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无线视觉传感器网络中的联合编码比特率和活动率优化

优化传感器节点的编码比特率和活动速率对于无线传感器网络的功能和生存至关重要，因为这些速率不仅影响网络收集的信息量，还影响其功耗。这项研究提出了一个框架，用于在有限能量约束下的无线视觉传感器网络中的传感器节点联合编码比特率和活动率优化（CARO）。该框架使用累积视觉信息（AVI）的概念来衡量从传感器节点收集的视觉信息量。作者针对以下两种情况提出了两种优化算法：（I）具有预定运行时间的网络，其中算法CARO I在其预定运行时间上最大化网络的AVI。（II）尽力而为网络，算法CARO II在收集的视觉信息约束下最大化了网络运行时间。仿真表明，与所有节点都具有相同活动速率的简单解决方案相比，使用CARO优化速率可最大程度地提高网络的AVI并延长其运行时间。这是因为作者的框架考虑到了不同位置的不同节点可能在不同条件下运行并收集了不同重要性的信息。