Cloud computing is an emerging paradigm that provides computing resources as a service over a network. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication, which brings data (e.g., databases) closer to data consumers (e.g., cloud applications), is seen as a promising solution. It allows minimizing network delays and bandwidth usage. In this paper we study data replication in cloud computing data centers. Unlike other approaches available in the literature, we consider both energy efficiency and bandwidth consumption of the system, in addition to the improved Quality of Service (QoS) as a result of the reduced communication delays. The evaluation results obtained during extensive simulations help to unveil performance and energy efficiency tradeoffs and guide the design of future data replication solutions.

Cloud computing is a computing model where users access ICT services and resources without regard to where the services are hosted. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. In this paper, we present models for energy consumption and bandwidth demand of database access in cloud computing datacenter. In addition, we propose an energy efficient replication strategy based on the proposed models, which results in improved Quality of Service (QoS) with reduced communication delays. The evaluation results obtained with extensive simulations help to unveil performance and energy efficiency tradeoffs and guide the design of future data replication solutions.

Improving the energy efficiency of the ICT sector is becoming an ambitious challenge for industries and research communities alike. Understanding how the energy is consumed in each part of an ICT system becomes fundamental in order to minimize the overall energy consumed by the system itself. In this paper, we propose an experimentally-driven approach to (i) characterize typical wireless access network gateways from an energy consumption standpoint and (ii) develop simple and accurate power consumption models for such gateways. In this work we focused our attention on the monitoring, measurement and analysis of the energy consumption patterns of WiFi and WiMAX gateways. Our measurements show that the power consumption of such gateways exhibits a linear dependence on the traffic until a saturation point is reached.