By Elias Sinderson, Vish Magapu, Ronald Mak (auth.), Hans-Arno Jacobsen (eds.)
Middleware platforms compriseprogrammingmodels, abstractions,protocols,and prone to facilitate the layout, the improvement, the combination, and the - ployment of dispensed functions in heterogeneous computing environments. Conceptually, the time period “middleware” refers to a layer of software program above the networking substrate and the working process and lower than the (distributed) software. In perform those obstacles aren't transparent minimize, with middleware performance entering into and out of those layers. distant conversation, p- lish/subscribe, messaging, and (distributed) transaction represent examples of universal middleware abstractions and providers. Middleware researchencompasses, builds on and extends a large spectrum of innovations, suggestions and concepts from a vast variety of ?elds, together with progr- ming languages, dispensed platforms, working platforms, networking, and knowledge administration. Following the luck of the previous meetings during this sequence within the Lake D- trict, united kingdom (1998), in Palisades, new york (2000), in Heidelberg, Germany (2001), and in Rio de Janeiro, Brazil (2003), the fifth overseas Middleware convention in Toronto, Canada aimed to be the premiere convention for middleware examine and know-how in 2004. The large scope of the convention integrated the layout, the implementation, the deployment, and the overview of allotted platforms systems and architectures for rising computing environments. The conf- ence gave an summary of study on middleware for peer-to-peer computing, middleware for mobility, middleware for replication and transactions, on p- lish/subscribesystems,onroutingprotocolsandoverlaynetworks,onapplication servers, source administration, and software program engineering, and on internet prone. This yr, the technical software of Middleware drew from 194 submitted papers, between which thirteen have been explicitly submitted as work-in-progress papers.
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Additional resources for Middleware 2004: ACM/IFIP/USENIX International Middleware Conference, Toronto, Canada, October 18-22, 2004. Proceedings
L. Adamic, R. Lukose, A. Puniyani, and B. Huberman. Search in power-law networks. Phys. Rev. E, 64:46135–46143, 2001. 2. R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. , 1999. 3. B. Bhattacharjee. Efficient peer-to-peer searches using result-caching. In Proc. IPTPS, 2003. A Content Model for Evaluating Peer-to-Peer Searching Techniques 37 4. B. Cahoon, K. S. McKinley, and Z. Lu. Evaluating the performance of distributed architectures for information retrieval using a variety of workloads.
Statistic Distributions. First, we asked whether the MDS statistics differed for real and random maps. The query-degree distributions for the maps are shown in Figure 3. As the figure shows, queries in the Gnutella-Random map have an average query degree clustered around the mean degree, while the distribution of the query degrees in the Gnutella-Real map is much more skewed. The random assignment of edges naturally leads to a Gaussian degree distribution. Because our SynthMap algorithm gen- 32 Brian F.
Finally, we use a synthetic model generated from World Wide Web documents and queries to compare the performance of several search algorithms that have been reported in the literature. Keywords: peer-to-peer search, simulation, modeling, performance evaluation 1 Introduction A flurry of recent research activity has centered on peer-to-peer search networks and their applications to a variety of tasks. A consensus has emerged that initial protocols (such as Gnutella’s flooding protocol) are not scalable enough, and this has spurred a great deal of interest in developing new search protocols and strategies.