This chapter presents an optimization framework to manage green datacenters using multilevel energy reduction techniques in a joint approach. A green datacenter exploits renewable energy sources and active Uninterruptible Power Supply (UPS) units to reduce the energy intake from the grid while improving its Quality of Service (QoS) . At server level, the state-of-the-art correlation-aware Virtual Machines (VMs) consolidation technique allows to maximize server’s energy efficiency. At system level, heterogeneous Energy Storage Systems (ESS) replace standard UPSs, while a dedicated optimization strategy aims at maximizing the lifetime of the battery banks and to reduce the energy bill , considering the load of the servers. Results demonstrate, under different number of VMs in the system, up to 11.6% energy savings, 10.4% improvement of QoS compared to existing correlation-aware VM allocation schemes for datacenters and up to 96% electricity bill savings.

Joint Computing and Electric Systems Optimization for Green Datacenters / Pahlevan, Ali; Rossi, Maurizio; Pablo, G.  Del Valle; Brunelli, Davide; Atienza, David. - STAMPA. - (2016), pp. 1-21. [10.1007/978-94-017-7358-4_35-1]

Joint Computing and Electric Systems Optimization for Green Datacenters

Rossi, Maurizio;Brunelli, Davide;
2016-01-01

Abstract

This chapter presents an optimization framework to manage green datacenters using multilevel energy reduction techniques in a joint approach. A green datacenter exploits renewable energy sources and active Uninterruptible Power Supply (UPS) units to reduce the energy intake from the grid while improving its Quality of Service (QoS) . At server level, the state-of-the-art correlation-aware Virtual Machines (VMs) consolidation technique allows to maximize server’s energy efficiency. At system level, heterogeneous Energy Storage Systems (ESS) replace standard UPSs, while a dedicated optimization strategy aims at maximizing the lifetime of the battery banks and to reduce the energy bill , considering the load of the servers. Results demonstrate, under different number of VMs in the system, up to 11.6% energy savings, 10.4% improvement of QoS compared to existing correlation-aware VM allocation schemes for datacenters and up to 96% electricity bill savings.
2016
Handbook of Hardware/Software Codesign
Netherlands
Springer Netherlands
978-94-017-7358-4
978-94-017-7358-4
Pahlevan, Ali; Rossi, Maurizio; Pablo, G.  Del Valle; Brunelli, Davide; Atienza, David
Joint Computing and Electric Systems Optimization for Green Datacenters / Pahlevan, Ali; Rossi, Maurizio; Pablo, G.  Del Valle; Brunelli, Davide; Atienza, David. - STAMPA. - (2016), pp. 1-21. [10.1007/978-94-017-7358-4_35-1]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/190612
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