A computational field framework for collaborative task execution in volunteer clouds

Stefano Sebastio; Michele Amoretti; Alberto Lluch Lafuente

doi:10.1145/2593929.2593943

A computational field framework for collaborative task execution in volunteer clouds

Stefano Sebastio
, Michele Amoretti
, Alberto Lluch Lafuente

IMT Institute for Advanced Studies Lucca
University of Parma

Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review

Abstract

The increasing diffusion of cloud technologies offers new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing computational resources. The high complexity, dynamism and unpredictability of such scenarios call for decentralized self-* approaches. We present in this paper a framework for the design and evaluation of self-adaptive collaborative task execution strategies in volunteer clouds. As a byproduct, we propose a novel strategy based on the Ant Colony Optimization paradigm, that we validate through simulation-based statistical analysis over Google cluster data.

Original language	English
Title of host publication	SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Number of pages	10
Publisher	ACM
Publication date	2014
Pages	105-114
ISBN (Print)	978-1-4503-2864-7
DOIs	https://doi.org/10.1145/2593929.2593943
Publication status	Published - 2014
Externally published	Yes
Event	9^th International Symposium on Software Engineering for Adaptive and Self-Managing Systems - Hyderabad, India Duration: 2 Jun 2014 → 3 Jun 2014 Conference number: 9

Conference

Conference	9^th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Number	9
Country/Territory	India
City	Hyderabad
Period	02/06/2014 → 03/06/2014

Keywords

ant colony optimization
bio-inspired algorithms
cloud computing
distributed tasks execution
peer-to-peer
self-* systems
spatial computing
volunteer computing

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10.1145/2593929.2593943

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title = "A computational field framework for collaborative task execution in volunteer clouds",

abstract = " The increasing diffusion of cloud technologies offers new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing computational resources. The high complexity, dynamism and unpredictability of such scenarios call for decentralized self-* approaches. We present in this paper a framework for the design and evaluation of self-adaptive collaborative task execution strategies in volunteer clouds. As a byproduct, we propose a novel strategy based on the Ant Colony Optimization paradigm, that we validate through simulation-based statistical analysis over Google cluster data. ",

keywords = "ant colony optimization, bio-inspired algorithms, cloud computing, distributed tasks execution, peer-to-peer, self-* systems, spatial computing, volunteer computing",

author = "Stefano Sebastio and Michele Amoretti and \{Lluch Lafuente\}, Alberto",

year = "2014",

doi = "10.1145/2593929.2593943",

language = "English",

isbn = "978-1-4503-2864-7",

pages = "105--114",

booktitle = "SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems",

publisher = "ACM",

note = "9<sup>th</sup> International Symposium on Software Engineering for Adaptive and Self-Managing Systems ; Conference date: 02-06-2014 Through 03-06-2014",

}

Sebastio, S, Amoretti, M & Lluch Lafuente, A 2014, A computational field framework for collaborative task execution in volunteer clouds. in SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. ACM, pp. 105-114, 9^th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Hyderabad, India, 02/06/2014. https://doi.org/10.1145/2593929.2593943

A computational field framework for collaborative task execution in volunteer clouds. / Sebastio, Stefano; Amoretti, Michele; Lluch Lafuente, Alberto.
SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. ACM, 2014. p. 105-114.

Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research › peer-review

TY - ABST

T1 - A computational field framework for collaborative task execution in volunteer clouds

AU - Sebastio, Stefano

AU - Amoretti, Michele

AU - Lluch Lafuente, Alberto

N1 - Conference code: 9

PY - 2014

Y1 - 2014

N2 - The increasing diffusion of cloud technologies offers new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing computational resources. The high complexity, dynamism and unpredictability of such scenarios call for decentralized self-* approaches. We present in this paper a framework for the design and evaluation of self-adaptive collaborative task execution strategies in volunteer clouds. As a byproduct, we propose a novel strategy based on the Ant Colony Optimization paradigm, that we validate through simulation-based statistical analysis over Google cluster data.

AB - The increasing diffusion of cloud technologies offers new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing computational resources. The high complexity, dynamism and unpredictability of such scenarios call for decentralized self-* approaches. We present in this paper a framework for the design and evaluation of self-adaptive collaborative task execution strategies in volunteer clouds. As a byproduct, we propose a novel strategy based on the Ant Colony Optimization paradigm, that we validate through simulation-based statistical analysis over Google cluster data.

KW - ant colony optimization

KW - bio-inspired algorithms

KW - cloud computing

KW - distributed tasks execution

KW - peer-to-peer

KW - self- systems

KW - spatial computing

KW - volunteer computing

U2 - 10.1145/2593929.2593943

DO - 10.1145/2593929.2593943

M3 - Conference abstract in proceedings

SN - 978-1-4503-2864-7

SP - 105

EP - 114

BT - SEAMS 2014 Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

PB - ACM

T2 - 9<sup>th</sup> International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Y2 - 2 June 2014 through 3 June 2014

ER -

A computational field framework for collaborative task execution in volunteer clouds

Abstract

Conference

Keywords

Access to Document

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