Computing Networks: From Cluster to Cloud Computing by Pascale Vicat-Blanc, Brice Goglin, Romaric Guillier,

By Pascale Vicat-Blanc, Brice Goglin, Romaric Guillier, Sebastien Soudan

Computing Networks explores the center of the hot allotted computing infrastructures we're utilizing at the present time: the networking structures of clusters, grids and clouds. It is helping community designers and distributed-application builders and clients to raised comprehend the applied sciences, specificities, constraints and merits of those various infrastructures communique structures. Cloud Computing will provide the chance for hundreds of thousands of clients to approach facts every time, at any place, whereas being green. for you to convey this rising site visitors in a well timed, most economical, energy-efficient, and trustworthy demeanour over long-distance networks, a number of concerns comparable to caliber of carrier, defense, metrology, network-resource scheduling and virtualization are being investigated for the reason that 15 years.

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In research grids, virtual private links are supplied by national research and education networks, such as France’s National Telecommunication Network for Technology, Education and Research (RENATER) for Grid5000, or the pan-European data communications network, GEANT, for EGI. In order to profit as much as possible from these infrastructures, it is necessary to share the network between the different grid users while providing an abundant bandwidth for each application. Whether over the Internet or a private network, the critical issue is sharing the capacity of the site’s link to the wide-area network.

Today MapReduce can be used on a large-sized server cluster to sort a petabyte of data in only a few hours. Parallelism also offers the possibility of supporting server or storage breakdowns during the operation: if a mapper or a reducer fails, the job can be transferred to another processor. The distribution, Map and the Reduce functions of MapReduce are defined in relation to data structured in (key, value) pairs. info Utilization of Network Computing Technologies 43 a different domain: Map(k1, v1) −→ list(k2, v2).

Org. 5. org. info Utilization of Network Computing Technologies 61 clusters or grids composed of rare and/or powerful resources, whether interconnected to each other or not. Furthermore, we have shown that applications being run on these computing infrastructures have different requirements in terms of the performance criteria of communications. In the next chapter, we provide a more precise analysis of the place and constraints of the network within these infrastructures and we present the challenges posed to network technologies to enable computing networks to reach their full potential and their users to receive the greatest benefit from them.

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