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

Abstract

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, navigation, weapon controlling, weather forecasting etc., involve big data analysis collected from sensors, all at a very high-speed with reliable results. This requires a large number of parallel processors connected with a 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 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-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

Optimizing Wireless Sensor Networks through Ant Colony-Based Localized Mesh Topology

“…2,[19][20][21][22][23][24] Industrial problems that have to do with real-time monitoring, environmental data collection for the monitoring of climates and the detection of pollutants for disaster recovery are rendered solvable. [21][22][23]31,32 As far as precision agriculture is concerned, the solution enables optimal precision irrigation, crop monitoring and soil monitoring for multi-faceted solutions. In addition, industrial applications such as asset tracking for predictive programmed maintenance and process optimization to reduce downtimes.…”

“…In the academic field, the systems can be used to improve wireless communication through network optimization and bio-inspired system design. [5][6][7][8][9][10]31,32 As per the motivations mentioned above, the investigations in this paper will add to the academic spectrum on network scalability, energy conservation, and versatility. It is because it promotes other areas such as computer science, electrical engineering, and telecommunications to explore new ways for developing new applications that inspire innovation.…”