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A Self-Organized Load-Balancing Algorithm for Overlay-Based Decentralized Service Networks | IEEE Conference Publication | IEEE Xplore

A Self-Organized Load-Balancing Algorithm for Overlay-Based Decentralized Service Networks


Abstract:

A service network with decentralized ownership is a system where nodes offering a variety of services are administered by different organizations -- or even by a set of i...Show More

Abstract:

A service network with decentralized ownership is a system where nodes offering a variety of services are administered by different organizations -- or even by a set of individuals. In such a context, nodes hosting services can dynamically enter and exit the system without prior notice, and there is no centralized point of control. If one wants to build into such a system the ability to direct incoming requests for the various hosted services to those nodes that can efficiently fulfill them, one option is to introduce in the system an entity that serves as a gateway to accept service requests, and is an intermediary to re-direct requests as needed. That implies that this intermediary is able to acquire and maintain accurate and up-to-date information on where it can direct incoming requests. Another option, which is the one we pursue in this paper, is to build the system as an overlay network, in which the nodes hosting instances of each of many different types of services can self-organize as "virtual clusters", and efficiently load-balance incoming requests amongst themselves. We describe our design and evaluation of a decentralized computing framework of this kind. We leverage a resilient peer-to-peer overlay that automatically re-configures its topology, responding to the number of different service types executing on the peer nodes, the dynamics of the participation of those nodes (peer churn), and the traffic coming into the system for the various services.
Date of Conference: 03-07 October 2011
Date Added to IEEE Xplore: 31 October 2011
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Conference Location: Ann Arbor, MI, USA
Citations are not available for this document.

I. Introduction

The provisioning of distributed computational services has followed a constant trend towards increasing degrees of virtualization. The original client/server model led to the evolution of dedicated clusters, followed by grids, and then by large-scale data centers able to host a multitude of diverse applications on virtual machines. That trajectory has now led to cloud computing, with its promise of opaque, elastic, and on-demand allocation of computational resources, and its computing-as-a-utility model.

Cites in Papers - |

Cites in Papers - IEEE (5)

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1.
Mridula Dhingra, Neha Gupta, "Failure Node Reduction Algorithm to Enhance Fault Tolerance Capability of Cloud Nodes", 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN), pp.165-168, 2020.
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Daniel J. Dubois, Yosuke Bando, Konosuke Watanabe, Henry Holtzman, "Lightweight Self-organizing Reconfiguration of Opportunistic Infrastructure-mode WiFi Networks", 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, pp.247-256, 2013.
5.
Paul L. Snyder, Giuseppe Valetto, Jose Luis Fernandez-Marquez, Giovanna Di Marzo Serugendo, "Augmenting the Repertoire of Design Patterns for Self-Organized Software by Reverse Engineering a Bio-Inspired P2P System", 2012 IEEE Sixth International Conference on Self-Adaptive and Self-Organizing Systems, pp.199-204, 2012.

Cites in Papers - Other Publishers (5)

1.
Jiangtao Zhang, Hejiao Huang, Xuan Wang, "Resource provision algorithms in cloud computing: A survey", Journal of Network and Computer Applications, vol.64, pp.23, 2016.
2.
Heng Qi, Yang Li, Keqiu Li, Milos Stojmenovic, "An exchanged folded hypercube-based topology structure for interconnection networks", Concurrency and Computation: Practice and Experience, vol.27, no.16, pp.4194, 2015.
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Luciano Baresi, Sam Guinea, Panteha Saeedi, Assurances for Self-Adaptive Systems, vol.7740, pp.214, 2013.
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Paul L. Snyder, Giuseppe Valetto, Bio-Inspired Models of Networks, Information, and Computing Systems, vol.103, pp.252, 2012.
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Paul L. Snyder, Yusuf Osmanlioglu, Giuseppe Valetto, Bio-Inspired Models of Networks, Information, and Computing Systems, vol.103, pp.99, 2012.

References

References is not available for this document.