DocumentCode :
721202
Title :
Adaptive probabilistic Skip Graph
Author :
Goyal, Amit ; Batra, Shalini
Author_Institution :
Comput. Sci. & Eng. Dept., Thapar Univ., Patiala, India
fYear :
2015
fDate :
12-13 June 2015
Firstpage :
953
Lastpage :
957
Abstract :
The exponential growth in the number of users on internet has lead to the invention of variants of the algorithms and data structures traditionally used in peer to peer networks. Many data structures like adjacency matrix, skip webs, hash tables, skip lists and skip graphs have been proposed to represent the peer to peer networks. This paper explores usage of one of these data structures, skip graph, a variant of skip list for peer to peer networks. The existing algorithm for searching in skip graph has O(log n) time complexity which can be further decreased by using the proposed approach named as Adaptive Probabilistic Skip Graph (APSG). Modifications have been proposed in the scenario where a node is repeatedly being queried by a certain node and it has been experimentally verified that, in such scenarios, the search time is reduced to O(1). The major focus has been on optimizing the search algorithm by adding probability vector in the basic structure of the skip graph node.
Keywords :
Internet; computational complexity; data structures; graph theory; peer-to-peer computing; probability; vectors; APSG; Internet; adaptive probabilistic skip graph; adjacency matrix; data structures; hash tables; peer to peer networks; probability vector; skip lists; skip webs; time complexity; Complexity theory; Data structures; Fault tolerance; Peer-to-peer computing; Probabilistic logic; Peer to Peer Networks; Probabilistic Data Structure; Skip Graphs; Skip Lists;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advance Computing Conference (IACC), 2015 IEEE International
Conference_Location :
Banglore
Print_ISBN :
978-1-4799-8046-8
Type :
conf
DOI :
10.1109/IADCC.2015.7154845
Filename :
7154845
Link To Document :
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