Optimizing service ecosystems in the cloud

Usman Wajid; César A. Marín; Nikolay Mehandjiev

doi:10.1007/978-3-642-38082-2_10

Optimizing service ecosystems in the cloud

Usman Wajid, César A. Marín, Nikolay Mehandjiev

Research output: Chapter in Book/Conference proceeding › Chapter

Abstract

A service ecosystem is a virtual space ideally distributed across networks and geographical areas where vast numbers of services and other digital entities can coexist and converge to form ad-hoc solutions. In this paper we present experimental results showing the performance of two optimization models in service ecosystem. We describe the two models and how they operate under service ecosystem conditions. We emulate service ecosystem conditions in a multi-site federated Cloud and test the two models under different scenarios. The experimental results help us to determine strengths and weaknesses of the two optimization models enabling us to make recommendations for their use in different application domains. © The Author(s).

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\|Lect. Notes Comput. Sci.
Subtitle of host publication	The Future Internet Assembly
Place of Publication	Heidelberg
Publisher	Springer Nature
Pages	115-126
Number of pages	11
Volume	7858
DOIs	https://doi.org/10.1007/978-3-642-38082-2_10
Publication status	Published - 2013
Event	2013 Annual Future Internet Assembly, FIA 2013 - Dublin Duration: 1 Jul 2013 → …

Other

Other	2013 Annual Future Internet Assembly, FIA 2013
City	Dublin
Period	1/07/13 → …

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10.1007/978-3-642-38082-2_10

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Wajid, U., Marín, C. A., & Mehandjiev, N. (2013). Optimizing service ecosystems in the cloud. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.: The Future Internet Assembly (Vol. 7858, pp. 115-126). Springer Nature. https://doi.org/10.1007/978-3-642-38082-2_10

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abstract = "A service ecosystem is a virtual space ideally distributed across networks and geographical areas where vast numbers of services and other digital entities can coexist and converge to form ad-hoc solutions. In this paper we present experimental results showing the performance of two optimization models in service ecosystem. We describe the two models and how they operate under service ecosystem conditions. We emulate service ecosystem conditions in a multi-site federated Cloud and test the two models under different scenarios. The experimental results help us to determine strengths and weaknesses of the two optimization models enabling us to make recommendations for their use in different application domains. {\textcopyright} The Author(s).",

author = "Usman Wajid and Mar{\'i}n, {C{\'e}sar A.} and Nikolay Mehandjiev",

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Wajid, U, Marín, CA & Mehandjiev, N 2013, Optimizing service ecosystems in the cloud. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.: The Future Internet Assembly. vol. 7858, Springer Nature, Heidelberg, pp. 115-126, 2013 Annual Future Internet Assembly, FIA 2013, Dublin, 1/07/13. https://doi.org/10.1007/978-3-642-38082-2_10

Optimizing service ecosystems in the cloud. / Wajid, Usman; Marín, César A.; Mehandjiev, Nikolay.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.: The Future Internet Assembly. Vol. 7858 Heidelberg: Springer Nature, 2013. p. 115-126.

Research output: Chapter in Book/Conference proceeding › Chapter

TY - CHAP

T1 - Optimizing service ecosystems in the cloud

AU - Wajid, Usman

AU - Marín, César A.

AU - Mehandjiev, Nikolay

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N2 - A service ecosystem is a virtual space ideally distributed across networks and geographical areas where vast numbers of services and other digital entities can coexist and converge to form ad-hoc solutions. In this paper we present experimental results showing the performance of two optimization models in service ecosystem. We describe the two models and how they operate under service ecosystem conditions. We emulate service ecosystem conditions in a multi-site federated Cloud and test the two models under different scenarios. The experimental results help us to determine strengths and weaknesses of the two optimization models enabling us to make recommendations for their use in different application domains. © The Author(s).

AB - A service ecosystem is a virtual space ideally distributed across networks and geographical areas where vast numbers of services and other digital entities can coexist and converge to form ad-hoc solutions. In this paper we present experimental results showing the performance of two optimization models in service ecosystem. We describe the two models and how they operate under service ecosystem conditions. We emulate service ecosystem conditions in a multi-site federated Cloud and test the two models under different scenarios. The experimental results help us to determine strengths and weaknesses of the two optimization models enabling us to make recommendations for their use in different application domains. © The Author(s).

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DO - 10.1007/978-3-642-38082-2_10

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VL - 7858

SP - 115

EP - 126

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.

PB - Springer Nature

CY - Heidelberg

T2 - 2013 Annual Future Internet Assembly, FIA 2013

Y2 - 1 July 2013

ER -

Optimizing service ecosystems in the cloud

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