References of "Khan, Samee Ullah"
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See detaile-STAB: Energy-Efficient Scheduling for Cloud Computing Applications with Traffic Load Balancing
Kliazovich, Dzmitry UL; Arzo, Sisay T.; Granelli, Fabrizio et al

in IEEE International Conference on Green Computing and Communications (GreenCom), Beijing, China 2013 (2013)

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See detailA survey on resource allocation in high performance distributed computing systems
Hussain, Hameed; Malik, Saif Ur Rehman; Hameed, Abdul et al

in Parallel Computing (2013), 39(11), 709-736

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and ... [more ▼]

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature. [less ▲]

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See detailAccounting for load variation in energy-efficient data centers
Kliazovich, Dzmitry UL; Arzo, Sisay T.; Granelli, Fabrizio et al

in IEEE International Conference on Communications (ICC), Budapest, Hungary, 2013 (2013)

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See detailDENS: data center energy-efficient network-aware scheduling
Kliazovich, Dzmitry UL; Bouvry, Pascal UL; Khan, Samee Ullah

in Cluster Computing (2013), 16(1), 65-75

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See detailSimulating Communication Processes in Energy-Efficient Cloud Computing Systems
Kliazovich, Dzmitry UL; Bouvry, Pascal UL; Khan, Samee Ullah

in CLOUDNET (2012)

Cloud computing data centers are becoming increasingly popular for the provisioning of computing resources. The cost and operating expenses of data centers have skyrocketed with the increase in computing ... [more ▼]

Cloud computing data centers are becoming increasingly popular for the provisioning of computing resources. The cost and operating expenses of data centers have skyrocketed with the increase in computing capacity. In this chapter, we survey the main techniques behind enabling energy efficiency in data centers and present simulation environment for energy-aware cloud computing. Along with the workload distribution, the focus is devoted to simulating packet-level communications in realistic setups. Finally, the effectiveness of common power management solutions is assessed and a scheduling methodology that combines energy efficiency and network awareness is presented. [less ▲]

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See detailAn overview of energy efficiency techniques in cluster computing systems
Valentini, Giorgio Luigi; Lassonde, Walter; Khan, Samee Ullah et al

in Cluster Computing (2011), 16(1), 3-15

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See detailDENS: Data Center Energy-Efficient Network-Aware Scheduling
Kliazovich, Dzmitry UL; Bouvry, Pascal UL; Khan, Samee Ullah

in IEEE/ACM International Conference on Green Computing and Communications (GreenCom), Hangzhou, China, 2010 (2010)

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The state of the art in data center energy optimization is focusing only on job distribution ... [more ▼]

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The state of the art in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, termed DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network). [less ▲]

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See detailGreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers
Kliazovich, Dzmitry UL; Bouvry, Pascal UL; Audzevich, Yury et al

in IEEE Global Communications Conference (GLOBECOM), Miami, FL, USA, 2009 (2009)

Detailed reference viewed: 520 (1 UL)