The remote processing framework for portable computer power saving

Руденко, А. Е.; Reiher, Peter; Popek, Gerald J.; Kuenning, Geoff

doi:10.1145/298151.298385

Cited by 67 publications

(47 citation statements)

References 9 publications

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“…Offloading is also referred to in the literature as remote execution and is employed in computational grid systems to improve the performance of an application typically through the use of Grid RPC [1], [10], [18], [19], to speed execution through parallelization and improved task execution performance. Offloading has also been shown to be effective for mobile, resource constrained devices, to extend battery life and computational capacity [6], [9], [11], [15], [17], [26]. Figure 1 shows the conceptual design of a simple computation offloading system with one client (local computer) and one server (remote computer).…”

Section: Computation Offloadingmentioning

confidence: 99%

Using bandwidth data to make computation offloading decisions

Wolski

Gurun

Krintz

et al. 2008

2008 IEEE International Symposium on Parallel and Distributed Processing

111

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Abstract-We present a framework for making computation offloading decisions in computational grid settings in which schedulers determine when to move parts of a computation to more capable resources to improve performance. Such schedulers must predict when an offloaded computation will outperform one that is local by forecasting the local cost (execution time for computing locally) and remote cost (execution time for computing remotely and transmission time for the input/output of the computation to/from the remote system). Typically, this decision amounts to predicting the bandwidth between the local and remote systems to estimate these costs. Our framework unifies such decision models by formulating the problem as a statistical decision problem that can either be treated "classically" or using a Bayesian approach. Using an implementation of this framework, we evaluate the efficacy of a number of different decision strategies (several of which have been employed by previous systems). Our results indicate that a Bayesian approach employing automatic change-point detection when estimating the prior distribution is the best-performing approach.

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Section: Computation Offloadingmentioning

confidence: 99%

Using bandwidth data to make computation offloading decisions

Wolski

Gurun

Krintz

et al. 2008

2008 IEEE International Symposium on Parallel and Distributed Processing

111

View full text Add to dashboard Cite

show abstract

“…To support a given set of services for power and fault-tolerance management, several possible solutions exist under given levels of redundancy (such as code migration or remote execution) [37], [38], [16]. This section investigates the benefits of a newly proposed scheme, precopying with remote execution, over a baseline code migration technique.…”

Section: Dynamic Power and Fault-tolerance Managementmentioning

confidence: 99%

Electronic textiles: a platform for pervasive computing

Marculescu¹,

Marculescu²,

Zamora³

et al. 2003

Proc. IEEE

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“…The use of remote invocation to reduce the power consumption in mobile systems has previously been investigated in [7], [8]. The goal in both of these efforts was to reduce power consumption by offloading tasks from an energy constrained system to a server without constraints in energy consumption.…”

Section: Related Workmentioning

confidence: 99%

Modeling, analysis, and self-management of electronic textiles

Stanley-Marbell

Marculescu

Mărculescu

et al. 2003

IEEE Trans. Comput.

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Abstract-Scaling in CMOS device technology has made it possible to cheaply embed intelligence in a myriad of devices. In particular, it has become feasible to fabricate flexible materials (e.g., woven fabrics) with large numbers of computing and communication elements embedded into them. Such computational fabrics, electronic textiles, or e-textiles have applications ranging from smart materials for aerospace applications to wearable computing. This paper addresses the modeling of computation, communication and failure in e-textiles and investigates the performance of two techniques, code migration and remote execution, for adapting applications executing over the hardware substrate, to failures in both devices and interconnection links. The investigation is carried out using a cycle-accurate simulation environment developed to model computation, power consumption, and node/link failures for large numbers of computing elements in configurable network topologies. A detailed analysis of the two techniques for adapting applications to the error prone substrate is presented, as well as a study of the effects of parameters, such as failure rates, communication speeds, and topologies, on the efficacy of the techniques and the performance of the system as a whole. It is shown that code migration and remote execution provide feasible methods for adapting applications to take advantage of redundancy in the presence of failures and involve trade offs in communication versus memory requirements in processing elements.

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The remote processing framework for portable computer power saving

Cited by 67 publications

References 9 publications

Using bandwidth data to make computation offloading decisions

Using bandwidth data to make computation offloading decisions

Electronic textiles: a platform for pervasive computing

Modeling, analysis, and self-management of electronic textiles

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