Near-Optimal Deterministic Steiner Tree Maintenance in Sensor Networks

Author:

Sharma Gokarna1,Busch Costas2

Affiliation:

1. Kent State University, Kent, USA

2. Louisiana State University, Baton Rouge, USA

Abstract

We consider the group-communication maintenance problem between a set of k mobile agents that are tracked by a static sensor network. We develop a scalable deterministic distributed algorithm for maintaining a Steiner tree of the agents so that group communication between them can be provided with the minimum total cost possible. The main idea is that our algorithm maintains a virtual tree of mobile agents that can be immediately converted to an actual Steiner tree at all times. Our algorithm achieves the Steiner tree with total length at most O (log k ) times the length of the optimal Steiner tree in the constant-doubling graph model. The total communication cost (the number of messages) to maintain the Steiner tree is only O (min{log n , log D }) times the optimal communication cost, where n and D , respectively, are the number of nodes and the diameter of the constant-doubling network. We also develop improved algorithms for the mobile k -center, sparse-aggregation, and distributed-matching problems. Experimental evaluation results show the benefits of our algorithms compared to previous algorithms. These four problems are NP-hard and, to the best of our knowledge, our algorithms are the first near-optimal deterministic algorithms for maintaining approximate solutions to these important network problems with low maintenance costs in a distributed setting.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

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