Download Databases, Information Systems, and Peer-to-Peer Computing: by Bo Xu, Ouri Wolfson (auth.), Wee Siong Ng, Beng-Chin Ooi, PDF

By Bo Xu, Ouri Wolfson (auth.), Wee Siong Ng, Beng-Chin Ooi, Aris M. Ouksel, Claudio Sartori (eds.)

Peer-to-peer (P2P) computing gives you to o?er interesting new chances in d- tributed details processing and database applied sciences. the belief of this promise lies essentially within the availability of more suitable companies similar to based methods for classifying and registering shared details, veri?cation and certi?cation of data, content-distributed schemes and caliber of c- tent, security measures, details discovery and accessibility, interoperation and composition of energetic info companies, and ?nally market-based me- anisms to permit cooperative and non-cooperative details exchanges. The P2P paradigm lends itself to developing large-scale advanced, adaptive, - tonomous and heterogeneous database and data platforms, endowed with truly speci?ed and di?erential functions to barter, cut price, coordinate, and self-organize the data exchanges in large-scale networks. This imaginative and prescient could have an intensive impression at the constitution of complicated organisations (business, scienti?c, or another way) and at the emergence and the formation of social c- munities, and on how the data is equipped and processed. The P2P details paradigm evidently encompasses static and instant connectivity, and static and cellular architectures. instant connectivity c- bined with the more and more small and robust cellular units and sensors pose new demanding situations to in addition to possibilities for the database neighborhood. Inf- mation turns into ubiquitous, hugely dispensed and available at any place and at any time over hugely dynamic, volatile networks with very critical constraints at the details administration and processing capabilities.

Show description

Read Online or Download Databases, Information Systems, and Peer-to-Peer Computing: Second International Workshop, DBISP2P 2004, Toronto, Canada, August 29-30, 2004, Revised Selected Papers PDF

Similar international_1 books

Welcoming linguistic diversity in early childhood classrooms : learning from international schools

Academics in multilingual study rooms were operating for a few years to enhance their repertoire of how to handle the desires of very young ones who input institution now not talking the language of guide. The paintings of twenty-two professional academics and directors in foreign colleges around the globe, this e-book encompasses a wealth of knowledge for school room lecturers, allowing them to stand a brand new tuition 12 months with self assurance, and for directors to appreciate extra truly what's all in favour of the instructing of childrens who don't but comprehend the school’s language.

Additional info for Databases, Information Systems, and Peer-to-Peer Computing: Second International Workshop, DBISP2P 2004, Toronto, Canada, August 29-30, 2004, Revised Selected Papers

Example text

1 Query Routing A query q may be posed at any peer n. Our goal is to route the query q through peers that give a large number of results for q. Ideally, we would like to visit only those peers that provide the most results. To maximize P eerRecall, we use a greedy query routing heuristic: each peer that receives a query propagates it through those of its links whose routing indexes indicate that they lead to peers that provide the largest number of results. The routing of a query stops either when a predefined number of peers is visited or when a satisfactory number of results is located.

As: de (H(n1 ), H(n2 )) = Σi=0 Let us define as l l Hi (n1 ) − Σi=0 Hi (n2 ) pref (l) = Σi=0 (4) b−1 de (H(n1 ), H(n2 )) = Σl=0 |pref (l)| (5) then Let a query qk = {x: a ≤ x ≤ a + k ∗ d, where d is equal to the range of each bucket and 0 ≤ k ≤ b}. Given that a is chosen uniformly at random from the domain of x, then the difference in the results is equal to: |hresults(H(n1 ), qk )/S(H(n1 )) − hresults(H(n2 ), qk )/S(H(n2 ))| = b−1 Σj=0 |pref (j + k) − pref (j − 1)| (6) where pref (j) = 0 for j ≥ b − 1 and j < 0.

Petrakis, G. Koloniari, and E. 2 500 1000 number of peers 1500 Fig. 7. Varying the number of nodes Next, we examine how our algorithms perform with a larger number of peers. We vary the size of the network from 500 to 1500. Radius is set to 2 and we use 2 short links and queries with range = 2. As shown in Fig. 7, P eerRecall remains nearly constant for both histogram distance metrics and outperforms the random join and the random networks. 5 Related Work Many recent research efforts focus on organizing peers in clusters based on their content.

Download PDF sample

Rated 4.36 of 5 – based on 33 votes