Resource Scheduling for Energy-Aware Reconfigurable Internet Data Centers

Author(s):  
Mohammad Shojafar ◽  
Nicola Cordeschi ◽  
Enzo Baccarelli

The pervasive use of cloud computing and the resulting growing number of Internet data centers have brought forth many concerns, including electrical energy cost, energy dissipation, cooling and carbon emission. Therefore, the need for efficient workload schedulers which are capable of minimizing the consumed energy becomes increasingly important. Green computing, a new trend for high-end computing, attempts to approach this problem by delivering both high performance and reduced energy consumption. Motivated by these considerations, in this chapter, we propose a joint computation-and-communication adaptive resource-provisioning scheduler for virtualized data centers, e.g., the Internet Data Center (IDC) scheduler, which exploits the DVFS-enabled reconfiguration capability of the underlying virtualized computing/communication platform. Specifically, we present and test a dynamic resource provisioning scheduler, which adaptively controls the execution time and bandwidth usage of each input job, as well as the internal and external switching costs on per-Virtual Machine (VM) basis.

Author(s):  
Salini Suresh ◽  
L. Manjunatha Rao

Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high- performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on–demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources.


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