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A Plantar Inclinometer Based Approach to Fall Detection in Open Environments Read chapter Read first chapter

2016 | OriginalPaper | Chapter

An Adaptive Multi Agent Service Discovery for Peer to Peer Cloud Services

Authors : Moses Olaifa, Sunday Ojo, Tranos Zuva

Published in: Emerging Trends and Advanced Technologies for Computational Intelligence

Publisher: Springer International Publishing

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Abstract

Cloud computing is evolving into a popular platform that enables on-demand provisioning of computing resources to a growing population of clients. Core to the provisioning of service in the cloud is the discovery of these services in an efficient and timely manner. Centralized and hierarchical approaches to service discovery have exhibited bottlenecks as network load increases and limitation in scalability. Efforts have been made in combining cloud systems and Peer to peer P2P systems to address the problem encountered in the conventional service discovery approaches but not without a new set of challenges ranging from network flooding to poor performance in dynamic networks. This paper presents an efficient and scalable approach for semantic cloud service discovery in a P2P cloud environment. The approach is based on Learning Automata LA and Ant Colony Optimization ACO. The ability of ACO to adapt to changes in real time makes it a better choice in dynamic environments such as cloud. We evaluate this approach against the some existing P2P service discovery approaches, the proposed mechanism showed an improved performance.

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Metadata
Title
An Adaptive Multi Agent Service Discovery for Peer to Peer Cloud Services
Authors
Moses Olaifa
Sunday Ojo
Tranos Zuva
Copyright Year
2016
Book
Emerging Trends and Advanced Technologies for Computational Intelligence

Print ISBN: 978-3-319-33351-9

Electronic ISBN: 978-3-319-33353-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-33353-3_8

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