Euro-Par 2012: Parallel Processing Workshops: BDMC, CGWS, by Alexandru Costan, Ciprian Dobre (auth.), Ioannis
By Alexandru Costan, Ciprian Dobre (auth.), Ioannis Caragiannis, Michael Alexander, Rosa Maria Badia, Mario Cannataro, Alexandru Costan, Marco Danelutto, Frédéric Desprez, Bettina Krammer, Julio Sahuquillo, Stephen L. Scott, Josef Weidendorfer (eds.)
This ebook constitutes completely refereed post-conference lawsuits of the workshops of the 18th foreign convention on Parallel Computing, Euro-Par 2012, held in Rhodes Islands, Greece, in August 2012. The papers of those 10 workshops BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, right, UCHPC, VHPC specialize in advertising and development of all facets of parallel and disbursed computing.
Read Online or Download Euro-Par 2012: Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Rhodes Islands, Greece, August 27-31, 2012. Revised Selected Papers PDF
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Extra info for Euro-Par 2012: Parallel Processing Workshops: BDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Rhodes Islands, Greece, August 27-31, 2012. Revised Selected Papers
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Yet as core architectures are connected to PoPs, they do not have control of traﬃc throughout ISP until the end-customer that undermines QoS guarantees enforcement. Interoperable CDNs in edge network have emerged to tackle directly these issues. Network service providers look forward to (i) take advantage of their infrastructure, (ii) deploy their own datacenters, and (iii) deliver content as close as possible to end-customer. The aim is to be able to oﬀer diﬀerentiated QoS guarantees to regular customers .
Even with the smallest cache storage percentage of 1%, a non-collaborative LRU caching approach performs much better than uniform replication. 92TB. In order to gather more information about the advantages of using noncollaborative caching for distributing popular content instead of uniform replication, we have evaluated and plotted in Figure 6 the throughput, ﬂows, and violations results sampled per second. We selected results from LRU caching with local cache size of 1% of the node storage capacity, and uniform replication with 20 replicas.