Reliable Gamma-Interconnection Network for Data Analysis in Sensor Networks: Design and Performance Evaluation

In today’s era of high speed 5G internet all electronic sensor networks are connected through IoT. Bank transactions are digitized, people can access any data through their mobile phones, organizations and companies handle their projects through online meetings etc. Military and medical surveillance, navy navigation, weapon controlling, weather forecasting etc. involve big data analysis collected from sensors, that too at a very high speed with reliable results. This requires large number of parallel processors connected with huge Bank of memory modules to store big data. Reliable interconnection network is needed to connect these large number of parallel processors and memory modules efficiently hence Multistage Interconnection Networks (MINs) come into play, as they provide highly reliable communication for big data transfer between processors and memory modules whenever required. In this manuscript a new network named Reliable Gamma-interconnection Network (RGN) is introduced which possesses multiple paths between processors and memory modules with two totally disjoint path availability. It provides high reliability and minimum path distance between source node to destination node than other gamma networks known, with the minimum hardware complexity. Reliability estimation and evaluation of RGN has been presented in this paper and comparison of results achieved with other gamma networks has been done for validation purpose.