Evaluation of stochastic flow networks susceptible to demand requirements between multiple sources and multiple destinations

Computer and communication applications such as big data analytics services, social networks, enterprise business and mobile applications often require to simultaneously pass data of different sizes between multiple source and multiple destinations in the network. In practice, the nodes in the commu...

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Bibliographic Details
Published in:International journal of system assurance engineering and management 2019-10, Vol.10 (5), p.1302-1327
Main Authors: Datta, Esha, Goyal, Neeraj Kumar
Format: Article
Language:English
Subjects:
Analytics
Applications programs
Communication networks
Computer simulation
Computing time
Data transmission
Engineering
Engineering Economics
Logistics
Marketing
Mathematical analysis
Mobile computing
Network reliability
Nodes
Organization
Original Article
Quality Control
Quality of service architectures
Reliability
Reliability analysis
Safety and Risk
Social networks
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Summary:Computer and communication applications such as big data analytics services, social networks, enterprise business and mobile applications often require to simultaneously pass data of different sizes between multiple source and multiple destinations in the network. In practice, the nodes in the communication networks are often connected through multiple intermediate links of different types with varying failure probabilities. Failure of intermediate links can adversely affect data transmission between source and destination nodes; thus, they can impact the quality of service. Therefore, reliability evaluation of such networks is of subtle importance in today’s service dependent world. This article presents an efficient method for reliability evaluation of stochastic flow networks that can pass various demands simultaneously from multiple source nodes to multiple destination nodes. The proposed method has three steps: First step obtains the combined minimal cut sets between the given set of source and destination nodes. Second step generates the set of simultaneous upper boundary flows for the varying demands using the combined minimal cut sets. Third step calculates the network unreliability by applying the Sum of Disjoint Product method on the upper boundary flows. The reliability of the network, i.e., the probability that the network can simultaneously pass the set of demands, is calculated as 1-Unreliability. The MATLAB simulation of the proposed method on bench mark networks show that the proposed approach takes less computational time than the existing method.
ISSN:0975-6809
0976-4348
DOI:10.1007/s13198-019-00876-9