科研之友
微信
新浪微博
Facebook
分享链接
摘要
We study throughput-optimal scheduling in mobile ad hoc networks with time-varying (fading) channels. Traditional back-pressure algorithms (based on the work by Tassiulas and Ephremides) require instantaneous network state (topology, queues-lengths, and fading channel-state) in order to make scheduling/routing decisions. However, such instantaneous network-wide (global) information is hard to come by in practice, especially when mobility induces a time-varying topology. With information delays and a lack of global network state, different mobile nodes have differing %26quot;views%26quot; of the network, thus inducing uncertainty and inconsistency across mobile nodes in their topology knowledge and network state information. In such a setting, we first characterize the throughput-optimal rate region and develop a back-pressure-like scheduling algorithm, which we show is throughput-optimal. Then, by randomly partitioning the geographic region spatially into disjoint and interference-free sub-areas, and sharing delayed topology and network state information only among nearby mobile nodes, we develop a localized low-complexity scheduling algorithm. The algorithm uses instantaneous local information (the queue length, channel state and current position at a mobile node) along with delayed network state information from nearby nodes (i.e., from nodes that were within a nearby geographic region as opposed to network-wide information). The proposed algorithm is shown to be near-optimal, where the geographic distance over which delayed network-state information is shared determines the provable lower bound on the achievable throughput.
- 出版日期2012-10
