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A server farm is examined, where a number of servers are used to offer a service to impatient customers. Every completed request generates a certain amount of profit, running servers consume electricity for power and cooling, while waiting customers might leave the system before receiving service if they experience excessive delays. A dynamic allocation policy aiming at satisfying the conflicting...
Apache Hadoop is a framework for managing large scale storage based datacenters whose primary job is to deliver data to clients. In such systems, the primary job is to associate each data request to a specific data replica among many available replicas. This assignment impacts the workload and power distribution across the storage servers. In this paper, we explore thermal and power aware task scheduling...
Cloud providers, like Amazon, offer their data centers' computational and storage capacities for lease to paying customers. High electricity consumption, associated with running a data center, not only reflects on its carbon footprint, but also increases the costs of running the data center itself. This paper addresses the problem of maximizing the revenues of Cloud providers by trimming down their...
We design, implement and evaluate a power-efficient and traffic-aware transcoding system on multicore servers that appropriately adjusts the processor operating level. The system is capable of configuring the number of active cores and core frequency “on-the-fly” according to the varying traffic rate. Results on an AMD machine show that our system saves 51.0% power consumption compared to a native...
In this paper, a performance-power relationship model is proposed through profiling Web server on blade machine. The fine-grained profiling results show that Web serverpsilas performance (exemplified by CPU utilization and response time) is almost linear with workload on it, and the power consumption of the server is linear with the CPU utilization for a given CPU frequency. A model is deduced which...
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