Energy Efficient Resource Management in Virtualized Cloud Data Centers

By Anton Beloglazov, Rajkumar Buyya. 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, 2010

874 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/ea23c2b22698ad2f39c7b21dc43c8befa3f77bf5

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In Computer Networks and Communications

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Citations in the corpus

A Survey on Mobile Edge Computing: The Communication Perspective (2017, background): “It is worthwhile to note that the implementation of GLB requires efficient resource management techniques at edge servers, such as dynamic right-sizing and VM management [191]–[194].”
Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing (2016, background): “However, this approach did not consider mobility usage and the similar research focusing on energy-aware cloud computing systems has been accomplished by other scholars (Mezmaz et al., 2011; Beloglazov and Buyya, 2010; Berl et al., 2010).”
Resource Management in Clouds: Survey and Research Challenges (2015, background): “bin packing problem, as for example in [23, 140, 204].”
A survey on virtual machine migration and server consolidation frameworks for cloud data centers (2015, methodology): “Dynamic resource assignment policy attributes (Beloglazov and Buyya, 2010c; Miet al., 2010; Wood et al., 2009) follow “resource on demand” mode to assign resources to the hosted VMs.”
DENS: data center energy-efficient network-aware scheduling (2010, neutral): “tween computing servers [30] targeting energy-efficient [3]”
Live Video Analytics at Scale with Approximation and Delay-Tolerance (2017, background): “Autonomic computing [24, 26,29,66,70,77] allocate resources to VMs and web applications to maximize their quality of service.”
Data Center Energy Consumption Modeling: A Survey (2016, methodology): “Such predictions can then be used to improve the energy efficiency of the data center, for example by incorporating the model into techniques such as temperature or energy aware scheduling [18], dynamic voltage frequency scaling (DVFS) [19][20][21], resource virtualization [22], improving the algori”
Resource Central: Understanding and Predicting Workloads for Improved Resource Management in Large Cloud Platforms (2017, methodology): “In fact, computing an optimal solution for such a bin-packing problem is infeasible, so prior works have used heuristics [2, 3, 24].”