Weak state routing for large scale dynamic networks

  • Authors:
  • Utku Günay Acer;Shivkumar Kalyanaraman;Alhussein A. Abouzeid

  • Affiliations:
  • Rensselaer Polytechnic Institute, Troy, NY;Rensselaer Polytechnic Institute, Troy, NY;Rensselaer Polytechnic Institute, Troy, NY

  • Venue:
  • Proceedings of the 13th annual ACM international conference on Mobile computing and networking
  • Year:
  • 2007

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Abstract

Routing in communication networks involves the indirection from a persistent name (or ID) to a locator and delivering packets based upon the locator. In a large-scale, highly dynamic network, the ID-to-locator mappings are both large in number, and change often. Traditional routing protocols require high overhead to keep these in directions up-to-date. In this paper, we propose Weak State Routing (WSR), a routing mechanism for large-scale highly dynamic networks. WSR's novelty is that it uses random directional walks biased occasionally by weak indirection state information in intermediate nodes. The indirection state information is weak, i.e. interpreted not as absolute truth, but as probabilistic hints. Nodes only have partial information about the region a destination node is likely to be. This method allows us to aggregate information about a number of remote locations in a geographic region. In other words, the state information maps a set-of-IDs to a it geographical region. The intermediate nodes receiving the random walk use a method similar to longest-prefix-match in order to prioritize their mappings to decide how to bias and forward the random walk. WSR can also be viewed as an unstructured distributed hashing technique. WSR displays good rare-object recall with scalability properties similar to structured DHTs, albeit with more tolerance to dynamism and without constraining the degree distribution of the underlying network. Through simulations, we show that WSR offers a high packet delivery ratio, more than 98%. The control packet overhead incurred in the network scales as O(N) for N-node networks. The number of mappings stored in the network appears to scale as Θ(N(3/2)). We compare WSR with Dynamic Source Routing (DSR) and geographic forwarding (GPSR) combined with Grid Location Service (GLS). Our results indicate that WSR delivers more packets with less overhead at the cost of increased path length.