Using Peer-to-Peer Systems for Data Management

2011 ◽  
pp. 66-78
Author(s):  
Dinesh C. Verma

This chapter describes a peer-to-peer approach for managing data backup and recovery in an enterprise environment. Data management systems in enterprises constitute a significant portion of the total cost of management of data in enterprise systems. Maintaining data with a high degree of availability and reliability is typically done by having a centralized backup system that maintains backup copies of data. The maintenance of a large dedicated backup server for data management requires a highly scalable network and storage infrastructure, leading to a major expense center within the enterprise. With the current trends in workstation disk storage, an alternative peer-to-peer paradigm for data management can offer an approach that provides equivalent performance at a fraction of the cost of the centralized backup system. The author hopes that the contents of the chapter would lead to the development of more solutions that harness the power of peer-to-peer networks.

2009 ◽  
Vol 3 (4) ◽  
pp. 294-322 ◽  
Author(s):  
Ramazan S. Aygün ◽  
Yi Ma ◽  
Kemal Akkaya ◽  
Glenn Cox ◽  
Ali Bicak

2009 ◽  
Vol 19 (01) ◽  
pp. 57-71
Author(s):  
HARRIS PAPADAKIS ◽  
PARASKEVI FRAGOPOULOU ◽  
EVANGELOS P. MARKATOS ◽  
MARIOS D. DIKAIAKOS ◽  
ALEXANDROS LABRINIDIS

Unstructured peer-to-peer (P2P) networks suffer from the increased volume of traffic produced by flooding. Methods such as random walks or dynamic querying managed to limit the traffic at the cost of reduced network coverage. In this paper, we propose a partitioning method of the unstructured overlay network into a relative small number of distinct subnetworks. The partitioning is driven by the categorization of keywords based on a uniform hash function. The method proposed in this paper is easy to implement and results in significant benefit for the blind flood method. Each search is restricted to a certain partition of the initial overlay network and as a result it is much more targeted. Last but not least, the search accuracy is not sacrificed to the least since all related content is searched. The benefit of the proposed method is demonstrated with extensive simulation results, which show that the overhead for the implementation and maintenance of this system is minimal compared to the resulted benefit in traffic reduction.


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