Rendezvous regions: a scalable architecture for service location and data-centric storage in large-scale wireless networks

Summary form only given. In large-scale wireless networks such as mobile ad hoc and sensor networks, efficient and robust service discovery and data-access mechanisms are both essential and challenging. Rendezvous-based mechanisms provide a valuable solution for provisioning a wide range of services. We describe rendezvous regions (RRs) - a novel scalable rendezvous-based architecture for wireless networks. RR is a general architecture proposed for service location and bootstrapping in ad hoc networks, in addition to data-centric storage, configuration, and task assignment in sensor networks. In RR the network topology is divided into geographical regions, where each region is responsible for a set of keys representing the services or data of interest. Each key is mapped to a region based on a hash-table-like mapping scheme. A few elected nodes inside each region are responsible for maintaining the mapped information. The service or data provider stores the information in the corresponding region and the seekers retrieve it from there. We run extensive detailed simulations, and high-level simulations and analysis, to investigate the design space, and study the architecture in various environments including node mobility and failures. We evaluate it against other approaches to identify its merits and limitations. The results show high success rate and low overhead even with dynamics. RR scales to large number of nodes and is highly robust and efficient to node failures. It is also robust to node mobility and location inaccuracy with a significant advantage over point-based rendezvous mechanisms.