A case study on IVR applications' provisioning as cloud computing services

Belqasmi, Fatna; Azar, Christian; Glitho, Roch; Soualhia, Mbarka; Kara, Nadjia

doi:10.1109/mnet.2014.6724104

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Cited by 3 publications

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“…In reference [6], the authors designed a multi-objective integrated ant colony optimization scheduling algorithm. In order to measure the uncertainty, the concept of entropy is used to update the pheromone of ant colony algorithm, an improved algorithm to accelerate the convergence rate of the solution set.…”

Section: Introductionmentioning

confidence: 99%

Research on Task Scheduling Convergence Non-Dominated Sorting Method in Cloud Computing

Liang¹,

Zheng²,

Guo-lv³

2015

IJGDC

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Section: Introductionmentioning

confidence: 99%

Research on Task Scheduling Convergence Non-Dominated Sorting Method in Cloud Computing

Liang¹,

Zheng²,

Guo-lv³

2015

IJGDC

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Automatic Policy Based Web Service Integration Using Ontology

Tiroumalmouroughane¹,

Thambidurai²

2016

Proceedings of the International Conference on Informatics and Analytics

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Genetic-based algorithms for resource management in virtualized IVR applications

et al. 2014

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Interactive Voice Response (IVR) is a technology that allows automatic human-computer interactions, via a telephone keypad or voice commands. The systems are widely used in many industries, including telecommunications and banking. Virtualization is a potential technology that can enable the easy development of IVR applications and their deployment on the cloud. IVR virtualization will enable efficient resource usage by allowing IVR applications to share different IVR substrate components such as the key detector, the voice recorder and the dialog manager. Resource management is part and parcel of IVR virtualization and poses a challenge in virtualized environments where both processing and network constraints must be considered. Considering several objectives to optimize the resource usage makes it even more challenging. This paper proposes IVR virtualization task scheduling and computational resource sharing (among different IVR applications) strategies based on genetic algorithms, in which different objectives are optimized. The algorithms used by both strategies are simulated and the performance measured and analyzed.

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A case study on IVR applications' provisioning as cloud computing services

Cited by 3 publications

References 11 publications

Research on Task Scheduling Convergence Non-Dominated Sorting Method in Cloud Computing

Research on Task Scheduling Convergence Non-Dominated Sorting Method in Cloud Computing

Automatic Policy Based Web Service Integration Using Ontology

Genetic-based algorithms for resource management in virtualized IVR applications

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