Stateless Multicasting In Ad-Hoc Networks Guided By Motion Estimation

摘要

Multica st routing protocols typically rely on the a priori creation of a multicast tree (or mesh), w hich requires the individual nodes to maintain state information. In sensor networks where traffic is bursty, with long periods of silence between the bursts of data, this multicast state maintenance adds a large amount of overhead for no benefit to the application. Thus, Chen-Hsiang Feng et al. have developed a stateless receiver-based multicast protocol that simply uses a list of the multicast members (e.g., sinks), embedded in packet headers, to enable receivers to decide the best way to forw ard the multicast traffic. This protocol, called RBMulticast (Receiver-Based Multicast), exploits the knowledge of the geographic locations of the nodes to remove the need for costly state maintenance (e.g., tree/mesheighbor table maintenance), ma king it ideally suited for sensor network multicast applications. But the problem in this approach is that to know geographic locations of all nodes at particular node frequent beacons must be sent by all nodes. Through these beacons, each node knows about the geographic locations of all other nodes. But if the node speed is high & nodes moves great distance in the beacon interval RBMulticast will fail. Routing will get longer hops & packet delivery ratio will drop. To solve this problem, we propose motion estimation & RBMulticast guided by location learnt using motion estimation