Titlebook: Data Management in Grid and Peer-to-Peer Systems; Third International Abdelkader Hameurlain,Franck Morvan,A Min Tjoa Conference proceeding

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Abdelkader Hameurlain,Franck Morvan,A Min TjoaUp-to-date results.Fast track conference proceedings.State-of-the-art report

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Data Management in Grid and Peer-to-Peer Systems978-3-642-15108-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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https://doi.org/10.1007/978-3-031-47913-7nted according to the multidimensional model. Cloud computing on the impulse of ICT majors like Google, Microsoft and Amazon, has recently focused the attention. OLAP querying and data warehousing in such a context consists in a major issue. Indeed, problems to be tackled are basic ones for large sc

擔(dān)心

Computational artwork to transform placestions to deal with the availability of the data they store in the DHT, e.g. via replication. To improve data availability, most DHT applications rely on data replication. However, efficient replication management is quite challenging, in particular because of concurrent and missed updates. In this p

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Volker Ruitinga,Emma Chris Avramieame proposals are very coupled with the application level and cannot be easily implemented in other environments, other use pre-defined structures difficult to maintain, or assume peers are physically homogeneous. So, the search for portable and flexible strategies remains an open problem. In this pa

Graduated

https://doi.org/10.1007/978-1-4842-6264-1 levels that have to be provided. Peer-to-peer systems are vulnerable to several attacks. In particular, for routing attacks, an adversary attempts to mis-route or drop messages along the routing procedure or corrupt routing table entries, thus degrading the overall routing process. In this paper, w

BURSA

https://doi.org/10.1007/978-1-4842-6264-1 failures or churn, such systems encode the user data into redundant fragments and distribute them among peers. The way they distribute it, known as ., has a significant impact on their behavior and reliability. In this paper, we study the impact of different placement policies on the data life time