Process Allocation Algorithms for Saving Power Consumption in Peer-to-Peer Systems

Enokido, Tomoya; Aikebaier, Ailixier; Takizawa, Makoto

doi:10.1109/tie.2010.2060453

Cited by 185 publications

(59 citation statements)

References 14 publications

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“…In the category of process-based resource allocation, computing the amount of electric power consumed to perform processes in each computer is addressed in [31]. It uses a macro level model to show the relation between the amount of computation and the total power consumption of peer computers in order to perform Web types of application processes.…”

Section: Process/content-based Resource Allocation Approachesmentioning

confidence: 99%

Energy Efficiency in P2P Systems and Applications

Brienza

Cebeci

Masoumzadeh

et al. 2015

Large-Scale Distributed Systems and Energy Efficiency

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P2P systems and applications have achieved increasing popularity in the last years due to the characteristics of dynamicity and scalability of the peer-to-peer paradigm. Currently, P2P applications -especially file sharing and file distribution applications -generate a remarkable portion of the overall Internet traffic. However, many common P2P protocols do not consider the energy problem. Frequently, hosts are requested to stay on and connected to the network for long times. Therefore, they are very energy-consuming. In this chapter, we present a general taxonomy to classify possible approaches to the energy problem in P2P systems and applications. Then, we survey the main solutions available in the literature, focusing on two relevant classes of P2P protocols, namely file sharing/distribution protocols (e.g., BitTorrent and Gnutella) and epidemic P2P protocols.

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Section: Process/content-based Resource Allocation Approachesmentioning

confidence: 99%

Energy Efficiency in P2P Systems and Applications

Brienza

Cebeci

Masoumzadeh

et al. 2015

Large-Scale Distributed Systems and Energy Efficiency

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“…We take an experimentation-based approach to modelling the power consumption of a server [20][21][22][23][24]. First, we measure how much electric power a server consumes to perform application processes on a server.…”

Section: Related Studiesmentioning

confidence: 99%

Power consumption and processing models of servers in computation and storage based applications

Inoue

Aikebaier

Enokido

et al. 2013

Mathematical and Computer Modelling

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a b s t r a c tThe electric power consumption of information systems has to be reduced in addition to increasing the performance and fault tolerance in order to realize green societies. Here, servers mainly consume electric power to perform processes requested by clients compared with clients. We consider computation (CP) and storage (ST ) types of application processes on servers. In CP processes, CPU is mainly consumed as in scientific computation. In ST processes, files in storage drives are mainly manipulated. First, we present the storage and computation based power consumption (SCBPC) model of a server to perform ST and CP processes. In the SCBPC model, the power consumption rate of a server depends on the types of processes concurrently performed and is independent of the number of processes. Then, we discuss the storage and computation based processing (SCBP) model to perform CP and ST processes on a server. Here, the execution times of a CP process and an ST process depend on the number of CP processes and the number of CP and ST processes concurrently performed, respectively. By using the SCBPC and SCBP models, we discuss an energy-aware (EA) algorithm to select a server for a process so that not only the execution time but also the power consumption can be reduced. We evaluate the EA algorithm in terms of total power consumption of servers and total execution time of processes. We show not only the total power consumption but also the total execution time can be reduced in the EA algorithm.

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“…In order to realize ecosystems [1], it is significant to reduce the total electric power consumption of servers in addition to achieving the performance and reliability objectives like response time. By abstracting essential properties which dominate the power consumption of a server from the experimental results, power consumption models of a server to perform application processes are discussed at macro level [2][3][4][5][6]. We classify application processes into three types; computation (CP), communication (CM), and storage (ST) types.…”

Section: Introductionmentioning

confidence: 99%

“…Here, the power consumption rate of a server is proportional to the total transmission rate. The power consumption model of a server to perform a general type of application process is also discussed [3]. We consider computation (CP) and storage (ST) types of application processes in this paper.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient dynamic clusters of servers

et al. 2014

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Electric power consumed by servers has to be reduced in order to realize green societies. We consider computation (CP) and storage (ST) types of application processes performed on servers in this paper, where CPU and storage drives are mainly used, respectively. In the storage-and computation-based power consumption model proposed by the authors, the power consumption rate of a server depends on what types of processes are performed but is independent of how may processes are performed on the server. In the storage-and computation-based processing model, the execution time of an ST process depends on the number of concurrent CP and ST processes but the execution time of a CP process depends on only CP processes and is independent of ST processes. In our previous studies, the energy-aware algorithm is discussed to select a server in a cluster of servers for each request so that the total power consumption of the servers can be reduced. However, a server consumes electric power even if the server is idle, i.e. no process is performed. In this paper, we discuss a dynamic energyaware (DEA) cluster which includes only active servers where at least one process is performed. A server for each request is selected in a dynamic cluster so that the total 123 D. Duolikun et al.power consumption of servers in the cluster can be reduced. We evaluate the DEA algorithm in terms of the total power consumption and average execution time and show the total power consumption can be reduced.

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Process Allocation Algorithms for Saving Power Consumption in Peer-to-Peer Systems

Cited by 185 publications

References 14 publications

Energy Efficiency in P2P Systems and Applications

Energy Efficiency in P2P Systems and Applications

Power consumption and processing models of servers in computation and storage based applications

Energy-efficient dynamic clusters of servers

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