Model-based compression in wireless ad hoc networks

  • Authors:
  • Milenko Drinic;Darko Kirovski;Miodrag Potkonjak

  • Affiliations:
  • Microsoft Research, Redmond, WA;Microsoft Research, Redmond, WA;University of California, Los Angeles, CA

  • Venue:
  • Proceedings of the 1st international conference on Embedded networked sensor systems
  • Year:
  • 2003

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Abstract

We present a technique for compression of shortest paths routing tables for wireless ad hoc networks. The main characteristic of such networks is that geographic location of nodes determines network topology. As opposed to encoding individual node locations, at each node our approach groups the remaining nodes in the network into regions. All shortest paths to nodes in a specific region are routed via the same neighboring node. In this paper, we propose an algorithm for dividing a network field into distinct regions to minimize routing table size while guaranteeing shortest path routes. We show that this problem is NP-hard, propose a heuristic to find efficient solutions, and empirically demonstrate the resulting system performance from the perspective of compression ratio and scalability. In our experiments, routing tables compressed using this technique, require 88.9% to 97.9% less storage than uncompressed tables.In order to achieve energy efficient routing, we propose an augmentation to the original routing mechanism that enables load balancing flexibility along with guaranteed shortest path routing at the expense of larger routing tables. Preliminary experiments estimate 10% lifetime extension of network nodes with a tradeoff of an increase in the size of routing tables. Finally, we propose a compression technique that aims at representing trajectories in a sensing network in a compact manner. This approach relies on trajectory prediction using three weighted Markov models, a local, regional and global one, all of them with context-length equal to one. Finally, we discuss a range of possible applications that rely on the developed prediction and routing models.