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At the age of petascale machines, cloud computing and peer-to-peer systems, large-scale distributed systems need an ever-increasing amount of energy. These systems urgently require effective and scalable solutions to manage and limit their electrical consumption. As of now, most efforts are focused on energy-efficient hardware designs. Thus, the challenge is to coordinate all these low-level improvements at the middleware level to improve the energy efficiency of the overall systems. Resource-management solutions can indeed benefit from a broader view to pool the resources and to share them according to the needs of each user. In this paper, we propose ERIDIS, an Energy-efficient Reservation Infrastructure for large-scale DIstributed Systems. It provides a unified and generic framework to manage resources from Grids, Clouds and dedicated networks in an energy-efficient way.

In this paper, a location-aided resource reservation scheme for handoff based on mobility prediction is proposed for wireless cellular networks. We analyze the performance of the proposed scheme and propose a two-dimensional random walk model for simulation. Performance evaluation is done by computing several key performance criteria, i.e., prediction accuracy, average number of reservation per call, reservation efficiency, and reservation time overhead. The influences of threshold distance, average distance where the mobile station moves along a straight line, location error and sample time are investigated, and the effectiveness of mobility prediction is also evaluated. Performance comparison reveals that the proposed scheme performs better than a solely distance-based scheme without mobility prediction.