Energy-Aware Autonomic Resource Allocation in Multi tier Virtualized Environments
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Abstract

With the increase of energy consumption associated with IT infrastructures, energy management is becoming a priority in the design and operation of complex service-based systems. At the same time, service providers need to comply with Service Level Agreement (SLA) contracts which determine the revenues and penalties on the basis of the achieved performance level. This paper focuses on the resource allocation problem in multitier virtualized systems with the goal of maximizing the SLAs revenue while minimizing energy costs. The main novelty of our approach is to address—in a unifying framework—service centers resource management by exploiting as actuation mechanisms allocation of virtual machines (VMs) to servers, load balancing, capacity allocation, server power state tuning, and dynamic voltage/frequency scaling. Resource management is modeled as an NP-hard mixed integer nonlinear programming problem, and solved by a local search procedure. To validate its effectiveness, the proposed model is compared to top-performing state-of-the-art techniques. The evaluation is based on simulation and on real experiments performed in a prototype environment. Synthetic as well as realistic workloads and a number of different scenarios of interest are considered. Results show that we are able to yield significant revenue gains for the provider when compared to alternative methods (up to 45 percent).Moreover; solutions are robust to service time and workload variations.
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#2

With the increase in energy consumption associated with IT infrastructures, energy management is becoming a priority in the design and operation of complex service-based systems. At the same time, service providers must comply with Service Level Agreement (SLA) contracts that determine revenues and penalties based on the level of performance achieved. This paper focuses on the problem of allocating resources in multi-topic virtualised systems with the aim of maximising revenue from SLAs while minimising energy costs. The main novelty of our approach is to approach -in a unified framework- the management of resources of the service centres by exploiting as mechanisms of action the assignment of virtual machines to servers, load balancing, capacity allocation, state adjustment Server power and dynamic voltage / frequency escalation. Resource management is modelled as a nonlinear programming problem for NP-hard mixed integers and is solved by a local search procedure. To validate its effectiveness, the proposed model is compared with the most advanced techniques of the state of the art. The evaluation is based on simulation and actual experiments performed in a prototype environment. Synthetic workloads are considered as well as realistic and a number of different scenarios of interest. The results show that we are able to make significant revenue gains for the provider compared to alternative methods (up to 45 percent). In addition, the solutions are robust at the time of service and variations in workload.
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