ACM SIGNUM Newsletter
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Online computation and competitive analysis
Online computation and competitive analysis
Mobile IP; Design Principles and Practices
Mobile IP; Design Principles and Practices
Networking Infrastructure for Pervasive Computing: Enabling Technologies and Systems
Networking Infrastructure for Pervasive Computing: Enabling Technologies and Systems
Automated Configuration of TCP/IP with DHCP
IEEE Internet Computing
Adaptive Physical Design for Curated Archives
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
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Topology is a fundamental part of a network that governs connectivity between nodes, the amount of data flow and the efficiency of data flow between nodes. In traditional networks, due to physical limitations, topology remains static for the course of the network operation. Ubiquitous data networks (UDNs), alternatively, are more adaptive and can be configured for changes in their topology. This flexibility in controlling their topology makes them very appealing and an attractive medium for supporting "anywhere, any place" communication. However, it raises the problem of designing a dynamic topology. The dynamic topology design problem is of particular interest to application service providers who need to provide cost-effective data services on a ubiquitous network. In this paper we describe algorithms that decide when and how the topology should be reconfigured in response to a change in the data communication requirements of the network. In par ticular, we describe and compare a greedy algorithm, which is often used for topology reconfiguration, with a non-greedy algorithm based on metrical task systems. Experiments show the algorithm based on metrical task system has comparable performance to the greedy algorithm at a much lower reconfiguration cost.