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ASTAS: Architecture for Scalable and Transparent Anycast Services
Stevens, Tim,De Leenheer, Marc,Develder, Chris,De Turck, Filip,Dhoedt, Bart,Demeester, Piet The Korea Institute of Information and Commucation 2007 Journal of communications and networks Vol.9 No.4
Native information provider(IP) anycast suffers from routing scalability issues and the lack of stateful communication support. For this reason, we propose architecture for scalable and transparent anycast services(ASTAS), a proxy-based architecture that provides support for stateful anycast communications, while retaining the transparency offered by native anycast. Dynamic resource assignment for each initiated session guarantees that a connection is established with the most suitable target server, based on network and server conditions. Traffic engineering in the overlay can be realized in an effective way due to the dissemination of aggregated state information in the anycast overlay. To minimize the total deployment cost for ASTAS architectures, we propose optimized proxy placement and path finding heuristics based on look-ahead information gathered in network nodes. Contrary to a regular integer linear program(ILP) formulation, these heuristics allow to optimize proxy placement in large networks. A use case on a European reference network illustrates that lower proxy costs enable proxy deployment closer to the end-users, resulting in a reduced network load.
Mets, Kevin,D'hulst, Reinhilde,Develder, Chris The Korea Institute of Information and Commucation 2012 Journal of communications and networks Vol.14 No.6
A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.
Kevin Mets,Reinhilde D’hulst,Chris Develder 한국통신학회 2012 Journal of communications and networks Vol.14 No.6
A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination,which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.