An Integrated Power Consumption Model for Communication and Transaction Based Applications

2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems

2012

Self Cite

In information systems, a client first selects a server in a cluster of servers and issues a request to the server. The request is performed as a process in the server. In this paper, we consider a computation process which mainly consumes CPU resource. Cooling devices like fans consume the electric power in addition to CPU and other devices in a server. The rotation speed of a fan is changed in servers according to the temperature of a server. Thus, the total power consumption of a server depends on not only computational devices like CPU but also cooling devices. The extended simple power consumption (ESPC) model of a server is proposed to perform processes. In this paper, the ESPC model is improved to consider a server with a multi-core CPU. It is critical to discuss how to select a server for each request from clients in order to not only achieve performance objectives but also reduce the total power consumption of a system based on the ESPC model. The improved power consumption laxity based (IPCLB) algorithm for selecting a server is proposed in this paper, which consumes the minimum power to perform the process. We evaluate the ESPC model and the IPCLB algorithm in terms of the power consumption and elapse time in this paper.

Section: B Total Power Consumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Energy-Efficient Server Selection Algorithm Based on the Extended Simple Power Consumption Model

Enokido

2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems

2012

Self Cite

“…The simple power consumption (SPC) model [12], [16] and extended simple power consumption (ESPC) model [17] are discussed to show how a server consumes the electric power to perform computation type application processes. Scientific applications are typical examples of computation applications.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we would rather discuss softwareoriented aspects of information systems to reduce the electric power consumption in a cluster of servers to realize the high performance and scalable information systems [10], [11]. Applications are classified into computation [12], [13], communication [14], storage [15] and general [16] type applications.…”

Section: Introductionmentioning

confidence: 99%

Transmission Power Consumption Laxity-Based (TPCL) Algorithm for Communication Type Applications

Enokido

2012 Seventh International Conference on Broadband, Wireless Computing, Communication and Applications

2012

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In order to realize energy-aware information systems, it is critical to discuss how to reduce the total electric power consumption of information systems. In this paper, we consider communication type applications where a server transmits a large volume of data to clients. A client first selects a server in a cluster of servers and issues a file transmission request to the server. In order to realize the server selection algorithm, it is critical to define a power consumption model of a server to perform processes. In our previous studies, the transmission power consumption (TPC) model and the extended TPC (ETPC) model of a server to transmit files to clients are proposed. In the TPC model, the electric power consumption of cooling devices like fans is assumed to be constant. Thus, the total power consumption of a server depends on not only computation and communication devices but also cooling devices. In the ETPC model, the power consumption of cooling devices is considered. Each server can be modeled as TPC or ETPC depending on cooling devices. In this paper, we newly propose the transmission power consumption laxity-based (TPCLB) algorithm for a cluster of servers which are based on the TPC and ETPC models so that the total power consumption in a cluster of servers can be reduced. We evaluate the TPCLB algorithm in terms of the total power consumption and elapse time compared with the round-robin (RR) algorithm.

Simple estimation and energy‐aware migration models of virtual machines in a server cluster

Watanabe

Duolikun

Concurrency and Computation

2018

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Summary In order to realize green society, it is critical to reduce electric energy consumed by servers in clusters. In our previous studies, these types of algorithms are proposed to select an energy‐efficient server to perform an application process issued by a client. In this paper, we newly discuss a migration approach to reducing the electric energy consumption of servers where virtual machines with application processes migrate to more energy‐efficient servers. We propose a new algorithm called ISEAM2 to reduce the electric energy consumption of servers. Here, a pair of a host server and a virtual machine on the host server are first selected to perform a process issued by an application. In addition, a target virtual machine on a host server and a guest server to which the target virtual machine migrates are selected so that the electric energy consumption of the host and guest servers can be minimized. Thus, virtual machines with application processes migrate to more energy‐efficient servers. We also propose a simple way to estimate the termination time of every process on each server. In the evaluation, we show the total electric energy consumption and total active time of servers, and the average execution time of processes can be reduced in the ISEAM2 algorithm compared with other algorithms.