Providing Scalable Data Services in Ubiquitous Networks

Abstract

Abstract. 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 particular, 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.

Resilient design of recharging station networks for electric transportation vehicles

“…A systematic and generic approach to the design and operation of networked systems has gained attention in recent publications [1][2][3][4][5][6], following important results in the analysis of networks [7][8]. In some of our recent publications, it has been shown that efficiency and robustness are important considerations in the design of networks, leading to different optimal topologies [9][10].…”