NDLI: A fast estimation of shortest path distance for power-law network predominant cloud service

Content Provider	IEEE Xplore Digital Library
Author	Jin Liu Chunming Rong Ganseng Zhao
Copyright Year	2012
Description	Author affiliation: State Key Lab. of Software Engineering Computer School, Wuhan University Wuhan, China (Jin Liu) \|\| CIPSI University of Stavanger Stavanger, Norway (Chunming Rong) \|\| School of Computer Science South China Normal University Guangzhou, China (Ganseng Zhao)
Abstract	The estimation of the shortest path between two vertices in a network graphs is an important issue for many applications in the real world, which may be road networks, social collaboration networks, biological networks and so forth. The short response time, the less space cost and the high accuracy are three critical evaluation metrics in the approximate calculation of the shortest path. To achieve a quick and accurate calculation of an approximate shortest path distance, the typical method that takes a non-trivial approach calculates the distance between every pair of vertices in advance and records the calculation results with an n×n matrix, where n is the number of vertexes in the network graph. Unfortunately, it hard for this method function because it is difficult to sustain the huge amount of storage space and time consuming preprocessing for the big size of the network graph in practice. Unlike many efforts that have been made to minimize the costs of time and space in enhancing the accuracy of the shortest path calculation, this paper proposes an estimation scheme of the shortest path calculation for power-law graphs, due to the fact that many networks in the real applications are power-law networks. The theoretical analysis indicates that the schema is successfully optimized so that the query time can be an approximation constant and the calculation result of the approximate shortest path distance is almost 2 to 3 times as long as the actual shortest path distance between a pair of vertices. A simulation experiment also validates the analysis and demonstrates the feasibility of the proposed scheme.
Starting Page	480
Ending Page	487
File Size	882574
Page Count	8
File Format	PDF
ISBN	9781467345118
e-ISBN	9781467345101
e-ISBN	9781467345095
DOI	10.1109/CloudCom.2012.6427603
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-03
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Cloud computing Conferences Distance Calculation Estimation Approximation algorithms Educational institutions Approximation methods Power-law Network Shortest Path
Content Type	Text
Resource Type	Article

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