This paper considers the problem of performing decentralised co-ordination of low-power embedded devices (as is required within many environmental sensing and surveillance applications). Specifically, we address the generic problem of maximising social welfare within a group of interacting agents. We propose a novel representation of the problem, as a cyclic bipartite factor graph, composed of variable and function nodes (representing the agents' states and utilities respectively). We show that such representation allows us to use an extension of the max-sum algorithm to generate approximate solutions to this global optimisation problem through local decentralised message passing. We empirically evaluate this approach on a canonical coordination problem (graph colouring), and benchmark it against state of the art approximate and complete algorithms (DSA and DPOP). We show that our approach is robust to lossy communication, that it generates solutions closer to those of DPOP than DSA is able to,and that it does so with a communication cost (in terms of total messages size) that scales very well with the number of agents in the system (compared to the exponential increase of DPOP). Finally, we describe a hardware implementation of our algorithm operating on low-power Chipcon CC2431 System-on-Chip sensor nodes.
本文考虑了低功耗嵌入式设备执行分散式协调的问题(这是许多环境传感和监视应用程序所要求的)。具体来说,我们解决了在一组交互主体内最大化社会福利的通用问题。我们提出了一个新颖的问题表示形式,即由变量和功能节点组成的循环二元因子图(分别表示代理的状态和效用)。我们表明,这种表示使我们能够使用max-sum算法的扩展,通过局部分散的消息传递来生成针对此全局优化问题的近似解。我们根据规范的协调问题(图形着色)对这种方法进行经验评估,并针对最先进的近似和完整算法(DSA和DPOP)对它进行基准测试。我们证明了我们的方法对于有损通信具有鲁棒性,它产生的解决方案比DSA能够解决的问题更接近DPOP,并且这样做的通信成本(就总消息大小而言)与数字的比例很好地扩展。系统中代理的数量(与DPOP的指数增长相比)。最后,我们描述了在低功耗Chipcon CC2431片上系统传感器节点上运行的算法的硬件实现。 P>
机译:使用最大和算法的传感器网络基于代理的分散式协调
机译:通过最大和算法的有界近似分散式协调
机译:事实设备的分散协调,可使用智能编程来增强电力系统的稳定性
机译:使用MAX-SUM算法分散协调低功耗嵌入式设备
机译:低功耗可穿戴生物电子设备的嵌入式系统设计
机译:低功耗嵌入式处理器中的快速决策算法用于异构无线传感器网络中基于质量的移动传感器连接
机译:采用最大和算法的低功耗嵌入式设备的分散协调