Improving the Local Disk Cover Algorithm for Placing Relay Nodes in a Wireless Sensor Network

Author(s):  
Shuo-Han Chen ◽  
Yen-Ting Chen ◽  
Yu-Pei Liang ◽  
Yong-Ching Lin ◽  
Heng-Yin Chen ◽  
...  
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.


2016 ◽  
Vol 13 (10) ◽  
pp. 6711-6718
Author(s):  
G Srinivasan ◽  
S Murugappan

In wireless sensor network (WSN), the existing error recovery mechanisms do not concentrate on physical aspects such as error correction and coding. Also a complete balance needs to be maintained among the performance and energy tradeoff in order to prevent communication overhead. In this paper, we propose a relay assisted effective loss recovery technique for WSN. In this technique, the relay nodes among the source and destination node is selected based on the parameters such as channel state information and combined score using a decentralized partially observable Markov decision process. The combined score for each sensor is defined involving the parameters such as queue length, link bandwidth, MAC contention and residual energy. Then the low density parity check (LDPC) codes are used to encode and decode for performing error recovery. By simulation results, we show that the proposed technique reduces the number of errors and also reduces the computational complexity while selecting the node for retransmission of packets at the destination without fail. Also the decision making can be done locally with low overhead.


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