Promoting congestion control in opportunistic networks
Andrew Grundy, Milena Radenkovic · 2010
This paper is concerned with congestion aware forwarding algorithms within opportunistic networks. We remove the reoccurring assumption of unlimited storage, and make it evident that congestion is a prominent problem that needs to be addressed. We propose a distributed congestion control algorithm that adaptively chooses the next hop based on contact history and statistics, as well as storage statistics. We aim to distribute the load away from the storage hotspots in order to spread the traffic around. We perform an extensive set of trace driven simulations for “several-to-many” communication patterns in opportunistic networks. We show that congestion control is an essential component in the transfer of data in opportunistic networks, and can be achieved in a fully open loop manner and by only local dissemination of statistics of nodes availability and connectivity. Our results with real connectivity traces show that by using novel availability heuristic we achieve higher levels of sent and delivered packets and outperform current opportunistic forwarding protocols, such as SimBetTS and FairRoute.