Data transfer planning with tree placement for collaborative environments

Holub, Petr; Rudová, Hana; Liška, Miloš

doi:10.1007/s10601-011-9106-7

Cited by 9 publications

(3 citation statements)

References 44 publications

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“…The optimization problem may be solved by any optimization problem solvers, such as CPLEX [2] and GLPK [1]. However, the formulation does not prevent cycles of the assigned paths, and we realize a common cycle elimination technique [20,12], which iteratively removes a link from any cycle until the solution is cycle free. In particular, we develop an optimal algorithm using CPLEX [2] and the cycle elimination technique [20,12].…”

Section: Problem Formulationmentioning

confidence: 99%

Sais

Liao

Hou

Lin

et al. 2014

Proceedings of the 1st International Workshop on Emerging Multimedia Applications and Services for Smart Cities

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We consider the problem of efficiently using smartphone users to augment the stationary infrastructure sensors for better situation awareness in smart cities. We envision a dynamic sensing platform that intelligently assigns sensing tasks to volunteered smartphone users, in order to answer queries by performing sensing tasks at specific locations that may not be covered by in-situ infrastructure sensors. We mathematically formulate the problem into an integer programming problem to minimize the overall energy consumption while satisfying the required query accuracy. We present an optimal algorithm to solve this problem using an existing computationally expensive optimization solver. To reduce the running time, we also propose a more practical heuristic algorithm. Our trace-driven simulation results reveal the benefits of our proposed heuristic algorithm, it: (i) finishes all the tasks, (ii) achieves 6 times shorter response time, and (iii) performs better with more volunteers. In contrast, exclusively using in-situ sensors completes 6% of the tasks, while using in-situ sensors with opportunistic sensing (without user intervention) completes 20% of the tasks. Our prototype system is validated in a user study and receives fairly positive feedback from the smartphone users who utilize it to submit and answer various spatial/temporal dependent queries.

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Section: Problem Formulationmentioning

confidence: 99%

Sais

Liao

Hou

Lin

et al. 2014

Proceedings of the 1st International Workshop on Emerging Multimedia Applications and Services for Smart Cities

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“…NameOriginator and description mspp16 P. Troubil, P. Holub, M. Liška, H. Rudová[67,101] Media Streams Planning Problem-A network optimization problem regarding routing of multiple concurrent multimedia streams with bandwidth close to capacity of network links…”

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confidence: 99%

Miplib 2010

Koch

Achterberg

Andersen³

et al. 2011

Math. Prog. Comp.

312

172

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This paper reports on the fifth version of the Mixed Integer Programming Library. The miplib 2010 is the first miplib release that has been assembled by a large group from academia and from industry, all of whom work in integer programming. There was mutual consent that the concept of the library had to be expanded in order to fulfill the needs of the community. The new version comprises 361 instances sorted into several groups. This includes the main benchmark test set of 87 instances, which

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“…Typical communication schemes of target applications of the MSPP[35]. Producers are depicted black, distributors grey, and consumers white.…”

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confidence: 99%

Media Streams Planning with Uncertain Link Capacities

Troubil

Rudová

Holub

2014

2014 IEEE 13th International Symposium on Network Computing and Applications

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Interactive collaborative environments built upon high quality video applications require minimum capture-todisplay latency to maintain feeling of natural communication. In practice, end users often encounter interruptions due to network congestion, which they could not avoid without knowledge of physical network infrastructure. We solve the problem of application level multipoint routing without assuming accurate knowledge of network link capacities, but rather relying on their estimates by network inference and bandwidth measurement tools. Our approach can handle uncertainties caused by both unreliable bandwidth measurements and unexpected capacity sharing. Support for on-the-fly transcoding of data streams on multicast agents allows per-recipient adaptation of video quality and bandwidth. We have implemented an ant colony optimization algorithm in the CoUniverse middleware for orchestration of collaborative environments. Experiments show very good quality of results on most practical use cases and ability to solve significantly larger instances than optimal approaches based on mixed integer programming.

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Data transfer planning with tree placement for collaborative environments

Cited by 9 publications

References 44 publications

Sais

Sais

Miplib 2010

Media Streams Planning with Uncertain Link Capacities

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