Load balancing and unbalancing for power and performance in cluster-based systems

By Eduardo Pinheiro, Ricardo Bianchini, Enrique V. Carrera, Taliver Heath. 2001

582 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/819071f138c37e46f33f57ea89106e79234b2468

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In Computer Networks and Communications

In Information Systems

Citations in the corpus

Making Scheduling "Cool": Temperature-Aware Workload Placement in Data Centers (2005, background): “The latter approaches focus on location-oblivious, global system power consumption (total heat load) through the use of global power management [12, 25], load balancing [11, 24], and power reduction features in individual servers [14].”
Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing (2012, background): “Only a single application is assumed to be run in the system and, like in [7], load balancing is supposed to be done by an external system.”
Managing energy and server resources in hosting centers (2001, background): “Energy-conscious switching was recently proposed independently [12, 33] and appears to be new in the literature.”
JouleSort: a balanced energy-efficiency benchmark (2007, unknown): “[6, 11, 30, 32]).”
A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems (2010, methodology): “[21] have proposed a technique for managing a cluster of physical machines with the objective of minimizing the power consumption while providing the required QoS.”
Conserving disk energy in network servers (2003, methodology): “A few efforts [30, 29, 6] have been made to conserve energy in network servers.”
Power and energy management for server systems (2004, background): “A few research efforts [7, 30, 31] have examined energy management strategies in se rver clusters.”
Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments (2010, background): “Resource allocation is combined with energy management by turning off servers with no load, or low load after unloading the servers [26][37].”
EnaCloud: An Energy-Saving Application Live Placement Approach for Cloud Computing Environments (2009, background): “Some research work [3][4][5][16][17] implement energyefficiency policy in a front-end load balancer to distribute the requests to backend servers, so as to minimize the energy consumption without violating application's QoS requirements.”
Energy Efficient Resource Management in Virtualized Cloud Data Centers (2010, unknown): “Later on, the context has been shifted to data centers [12, 7] and virtual computing environments such as Clouds.”