In this paper, we propose a traffic engineering-based adaptive approach to dynamically reconfigure the computing-plus-communication resources of networked data centers which support in real-time the service requirements of mobile clients connected by TCP/IP energy-limited wireless backbones. The goal is to maximize the energy-efficiency, while meeting hard QoS requirements on the delivered transmission rate and processing delay. In order to cope with the (possibly, unpredictable) fluctuations of the offered workload, the proposed optimal cross-layer resource controller is adaptive. It jointly performs: i) the balanced control and dispatching of the admitted workload; ii) the dynamic reconfiguration of the Virtual Machines (VMs) instantiated onto the parallel computing platform at the data center; and iii) the rate control of the traffic injected into the wireless backbone for delivering the service to the requiring clients. Our experimental results show that the proposed technique improves energy consumption of servers by 25% compared to state of the art improvement on average in the entire data center.
Energy-saving adaptive computing and traffic engineering for real-time-service data centers / Shojafar, Mohammad; Cordeschi, Nicola; Amendola, Danilo; Baccarelli, Enzo. - STAMPA. - (2015), pp. 1800-1806. (Intervento presentato al convegno IEEE International Conference on Communication Workshop, ICCW 2015 tenutosi a London, ENGLAND nel 2015) [10.1109/ICCW.2015.7247442].
Energy-saving adaptive computing and traffic engineering for real-time-service data centers
SHOJAFAR, MOHAMMAD;CORDESCHI, Nicola;AMENDOLA, DANILO;BACCARELLI, Enzo
2015
Abstract
In this paper, we propose a traffic engineering-based adaptive approach to dynamically reconfigure the computing-plus-communication resources of networked data centers which support in real-time the service requirements of mobile clients connected by TCP/IP energy-limited wireless backbones. The goal is to maximize the energy-efficiency, while meeting hard QoS requirements on the delivered transmission rate and processing delay. In order to cope with the (possibly, unpredictable) fluctuations of the offered workload, the proposed optimal cross-layer resource controller is adaptive. It jointly performs: i) the balanced control and dispatching of the admitted workload; ii) the dynamic reconfiguration of the Virtual Machines (VMs) instantiated onto the parallel computing platform at the data center; and iii) the rate control of the traffic injected into the wireless backbone for delivering the service to the requiring clients. Our experimental results show that the proposed technique improves energy consumption of servers by 25% compared to state of the art improvement on average in the entire data center.File | Dimensione | Formato | |
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