Routing for Power Minimization in the Speed Scaling Model

Andrews, Matthew; Anta, Antonio Fernández; Zhang, Lisa; Zhao, Wenbo

doi:10.1109/tnet.2011.2159864

Cited by 51 publications

(73 citation statements)

References 25 publications

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“…The goal is to route all packets minimizing the aggregated cost. In [22,23] the authors show offline algorithms for this problem with undirected graph and homogeneous link cost functions that achieve polynomial and polylogarithmic approximation, respectively. The cost function is the αth power of the link load plus a link assignment cost, for any constant α > 1.…”

Section: Related Workmentioning

confidence: 99%

Power-efficient assignment of virtual machines to physical machines

Aroca

Anta

Mosteiro

et al. 2016

Future Generation Computer Systems

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h i g h l i g h t s • Formal definition of 4 versions of the Virtual Machine Assignment problem (VMA). • Study of hardness of the offline version. • Study of competitiveness of the online version. • Proposal of algorithms for the online version. a b s t r a c tMotivated by current trends in cloud computing, we study a version of the generalized assignment problem where a set of virtual processors has to be implemented by a set of identical processors. For literature consistency, we say that a set of virtual machines (VMs) is assigned to a set of physical machines (PMs). The optimization criterion is to minimize the power consumed by all the PMs. We term the problem Virtual Machine Assignment (VMA). Crucial differences with previous work include a variable number of PMs, that each VM must be assigned to exactly one PM (i.e., VMs cannot be implemented fractionally), and a minimum power consumption for each active PM. Such infrastructure may be strictly constrained in the number of PMs or in the PMs' capacity, depending on how costly (in terms of power consumption) it is to add a new PM to the system or to heavily load some of the existing PMs. Low usage or ample budget yields models where PM capacity and/or the number of PMs may be assumed unbounded for all practical purposes. We study four VMA problems depending on whether the capacity or the number of PMs is bounded or not. Specifically, we study hardness and online competitiveness for a variety of cases. To the best of our knowledge, this is the first comprehensive study of the VMA problem for this cost function.

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Section: Related Workmentioning

confidence: 99%

Power-efficient assignment of virtual machines to physical machines

Aroca

Anta

Mosteiro

et al. 2016

Future Generation Computer Systems

View full text Add to dashboard Cite

show abstract

“…The goal is to route all packets minimizing the aggregated cost. In [6] and [7] the authors show offline algorithms for this problem with undirected graph and homogeneous link cost functions that achieve polynomial and polylogarithmic approximation, respectively. The cost function is the α-th power of the link load plus a link assignment cost, for any constant α > 1.…”

Section: Related Workmentioning

confidence: 99%

Power-Efficient Assignment of Virtual Machines to Physical Machines

Aroca

Anta

Mosteiro

et al. 2014

Adaptive Resource Management and Scheduling for Cloud Computing

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Abstract. Motivated by current trends in cloud computing, we study a version of the generalized assignment problem where a set of virtual processors has to be implemented by a set of identical processors. For literature consistency, we say that a set of virtual machines (VMs) is assigned to a set of physical machines (PMs). The optimization criteria is to minimize the power consumed by all the PMs. We term the problem Virtual Machine Assignment (VMA). Crucial differences with previous work include a variable number of PMs, that each VM must be assigned to exactly one PM (i.e., VMs cannot be implemented fractionally), and a minimum power consumption for each active PM. Such infrastructure may be strictly constrained in the number of PMs or in the PMs' capacity, depending on how costly (in terms of power consumption) it is to add a new PM to the system or to heavily load some of the existing PMs. Low usage or ample budget yields models where PM capacity and/or the number of PMs may be assumed unbounded for all practical purposes. We study four VMA problems depending on whether the capacity or the number of PMs is bounded or not. Specifically, we study hardness and online competitiveness for a variety of cases. To the best of our knowledge, this is the first comprehensive study of the VMA problem for this cost function.

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“…The software ILOG CPLEX 10.1 [9] was used to solve all the LP and MILP problems. Similar to [3], the simulation runs were performed on two well-known network topologies: the Abilene research network with 10 nodes and 13 links, and the NSF network with 14 nodes and 20 links, which are shown in Fig. 1.…”

Section: The Time Complexity Of This Algorithm Ismentioning

confidence: 99%

“…In [20], Nedevschi et al showed that even simple schemes for sleeping or rate-adaptation can offer substantial power savings without noticeably increasing loss and with a small increase in latency. In a closely related work [3], Andrews et al studied a routing problem with the objective of provisioning guaranteed bandwidth for a given traffic demand matrix while minimizing power consumption using rate adaptation. They showed that if the link power consumption curve is superadditive, there is no bounded approximation in general for integral routing.…”

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confidence: 99%