Performance enhancement in Wireless Sensor Network using hexagonal topology

Author(s):  
Brisheket Suman Tripathi ◽  
Manoj Kumar Shukla ◽  
Mohit Kumar Srivastava
2020 ◽  
Vol 23 (3) ◽  
pp. 260-266
Author(s):  
Waseem M. Jassim ◽  
Ammar E. Abdelkareem

In the last two decades, underwater acoustic sensor networks have begun to be used for commercial and non-commercial purposes. In this paper, the focus will be on improving the monitoring performance system of oil pipelines. Linear wireless sensor networks are a model of underwater applications for which many solutions have been developed through several research studies in previous years for data collection research. In underwater environments, there are certain inherent limitations, like large propagation delays, high error rate, limited bandwidth capacity, and communication with short-range. Many deployment algorithms and routing algorithms have been used in this field. In this work a new hierarchical network model proposed with improvement to Smart Redirect or Jump algorithm (SRJ). This improved algorithm is used in an underwater linear wireless sensor network for data transfer to reduce the complexity in routing algorithm for relay nodes which boost delay in communication.  This work is implemented using OMNeT++ and MATLAB based on their integration. The results obtained based on throughput, energy consumption, and end to the end delay.


Author(s):  
Duy-Hung Ha ◽  
Duy-Binh Ha ◽  
Van-Truong Truong ◽  
Van-Duc Phan ◽  
Q. S. Vu

In this paper, we investigate a relaying wireless sensor network (WSN) with the non-orthogonal multiple access (NOMA) and sensor node selection schemes over Rayleigh fading. Precisely, the system consists of two sensor clusters, a sink node, and an amplify-and-forward (AF) relay. These sensors applying the NOMA and sensor node selection schemes transmit the sensing data from the sensor clusters via the relay to the sink. We derived the expressions of outage probability and throughput for two sensor nodes. We also provide numerical results to examine the behavior of the system. Finally, we verify the validity of our analysis by using the Monte-Carlo simulation.


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