Cost-driven autonomous mobility

Deng, Xiao Yan; Michaelson, Greg; Trinder, Phil

doi:10.1016/j.cl.2009.01.003

Cited by 7 publications

(13 citation statements)

References 24 publications

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“…S = (CP U speed) · (1 − non AM P load), is used to differentiate the total resources of a location from the resources available for AMPs. The current research, like the previous AMP investigations [1,7,8], assumes that all resources of a location are available for AMPs, and the CPU speed coincides with the available speed, except the case of the root location where the external load is higher.…”

Section: Cost Model and Parameterisationmentioning

confidence: 99%

“…Location thrashing is illustrated in Figure 1(a) which shows AMP movements in the experiments with the real system [1] based on scenario 3 (Section 3.1). In Figure 1 [8] incurs two performance penalties, namely the cost of additional communication and the cost of slower execution.…”

Section: Location Thrashingmentioning

confidence: 99%

“…For all scenarios Loc1 is the root location. By the root location we mean the location where all AMPs start; it is also called either initiating location or first location in [1]. In the experiments we use large and small AMPs.…”

Section: Amp Distribution Scenariosmentioning

confidence: 99%

“…To analyse AMP behaviour on local area networks (LANs) we have constructed a simulation model [2]. Comparing the simulation results and observations of the real system [1] shows that simulated and real AMPs enter the same stable states (i.e. where no AMP can reduce its execution time by moving).…”

Section: Introductionmentioning

confidence: 99%

“…Autonomous mobile programs (AMPs) are mobile agents that improve execution efficiency by managing load; AMPs are aware of their resource needs, sensitive to the execution environment and periodically seek a better location to reduce execution time [1]. To analyse AMP behaviour on local area networks (LANs) we have constructed a simulation model [2].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Redundant movements in autonomous mobility: Experimental and theoretical analysis

Chechina¹,

King²,

Trinder³

2011

Journal of Parallel and Distributed Computing

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Distributed load balancers exhibit thrashing where tasks are repeatedly moved between locations due to incomplete global load information. This paper shows that systems of Autonomous Mobile Programs (AMPs) exhibit the same behaviour, and identifies two types of redundant movement (greedy effect). AMPs are unusual in that, in place of some external load management system, each AMP periodically recalculates network and program parameters and may independently move to a better execution environment. Load management emerges from the behaviour of collections of AMPs.The paper explores the extent of greedy effects by simulating collections of AMPs and proposes negotiating AMPs (NAMPs) to ameliorate the problem. We present the design of AMPs with a competitive negotiation scheme (cNAMPs), and compare their performance with AMPs by simulation. We establish new properties of balanced networks of AMPs, and use these to provide a theoretical analysis of greedy effects.

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Section: Cost Model and Parameterisationmentioning

confidence: 99%

Section: Location Thrashingmentioning

confidence: 99%

Section: Amp Distribution Scenariosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Redundant movements in autonomous mobility: Experimental and theoretical analysis

Chechina¹,

King²,

Trinder³

2011

Journal of Parallel and Distributed Computing

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Resource analyses for parallel and distributed coordination

Trinder

Cole

Hammond

et al. 2011

Concurrency and Computation

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SUMMARYPredicting the resources that are consumed by a program component is crucial for many parallel or distributed systems. In this context, the main resources of interest are execution time, space and communication/synchronisation costs. There has recently been significant progress in resource analysis technology, notably in type-based analyses and abstract interpretation. At the same time, parallel and distributed computing are becoming increasingly important.This paper synthesises progress in both areas to survey the state-of-the-art in resource analysis for parallel and distributed computing. We articulate a general model of resource analysis and describe parallel/distributed resource analysis together with the relationship to sequential analysis. We use three parallel or distributed resource analyses as examples and provide a critical evaluation of the analyses. We investigate why the chosen analysis is effective for each application and identify general principles governing why the resource analysis is effective.

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Characterising Effective Resource Analyses for Parallel and Distributed Coordination

Trinder

Cole

Loidl

et al. 2010

Foundational and Practical Aspects of Resource Analysis

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An important application of resource analysis is to improve the performance of parallel and distributed programs. In this context key resources are time, space and communication. Given the spectrum of cost models and associated analysis techniques available, what combination should be selected for a specific parallel or distributed context? We address the question as follows. We outline a continuum of coordination cost models and a range of analysis techniques. We consider six representative parallel/distributed applications of resource analysis techniques, and aim to extract general principles governing why the combination of techniques is effective in its context.

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Cost-driven autonomous mobility

Cited by 7 publications

References 24 publications

Redundant movements in autonomous mobility: Experimental and theoretical analysis

Redundant movements in autonomous mobility: Experimental and theoretical analysis

Resource analyses for parallel and distributed coordination

Characterising Effective Resource Analyses for Parallel and Distributed Coordination

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