Cluster-based congestion control for sensor networks
In wireless sensor networks, multiple flows from data collecting sensors to an aggregating sink could traverse paths that are largely interference coupled. These interference effects manifest themselves as congestion, and cause the flows to experience high packet loss and arbitrary packet delays. This is particularly problematic in event-based sensor networks (such as those in disaster recovery missions) where some flows are of greater importance than others and require a higher fidelity in terms of packet delivery and timeliness. In this paper we present COMUT (Congestion control for Multi-class Traffic), a distributed cluster-based mechanism for supporting multiple classes of traffic in sensor networks. COMUT is based on the self-organization of the network into clusters, each of which autonomously and proactively monitors congestion within its localized scope. The clusters then exchange appropriate information to facilitate system wide rate control where, each data source, depending on the relative importance of its data flow and the experienced congestion en route the sink, is coerced into controlling its rate. Our simulation results demonstrate that (i) our techniques are highly effective in dealing with multiple, interfering flows and in achieving high delivery ratios and low delays compared to traditional approaches, (ii) operate successfully over multiple underlying routing protocols, (iii) provide higher throughput to higher importance flows, (iv) are responsive to failures and, finally, (v) achieve substantial energy savings due to the considerable reduction in packet drops via the effective regulation of the network load.
clusters sensor networks rate control algorithms design experimentation real time