SIR Epidemic Model derived from Spatial Correlation for Worm Propagation in Event-driven Wireless Sensor Network
Sunil K Chaudhary1, Rajeev K Shakya2, Atul Kumar3
1Sunil Kumar Chaudhary*, Dept of EE, Galgotias College of Engineering and Technology Affiliated with Dr. A. P.J. Abdul Kalam Technical University, UP, India.
2Rajeev K Shakya*, Dept of EEE, Galgotias College of Engineering and technology affiliated with Dr.A.P.J. Abdul Kalam Technical University, UP, India.
3Atul Kumar, Dept of ECE, Galgotias College of Engineering and Technology Affiliated with Dr.A.P.J. Abdul Kalam Technical University, UP, India.
Manuscript received on December 18, 2019. | Revised Manuscript received on December 26, 2019. | Manuscript published on January 10, 2020. | PP: 1091-1097 | Volume-9 Issue-3, January 2020. | Retrieval Number: C7974019320/2020©BEIESP| DOI: 10.35940/ijitee.C7974.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An event or a physical activity triggers many nodes for sensing the environment in wireless sensor networks for event monitoring applications. These triggered nodes then transmit the sensed data to the control center. To study the virus propagation behavior in event-driven WSNs, sensor coverage which is a quality of service parameter, can be considered in epidemic model design to get more insight. Existing epidemic models have global characteristics when it is considered a realistic behavior of WSNs. In this paper, a comparative analysis is carried out for spatial correlation feature found in sensor nodes based on sensing range. It is extended version of our recent work. We present analysis using Susceptible-Infectious-Recovered (SIR) epidemic model with and without spatial correlation feature. Firstly, we show that the correlated nodes are occurred due to sensing ability for event monitoring applications. These nodes are responsible for transmitting correlated information when an event occurs in the field. A detailed comparative analysis with recent existing SIR epidemic models is presented with results and discussions. A comparison based on basic reproduction number is also discussed. Our Results show the impact of spatial correlation in the behavior of virus spread with time. Comparative study shows the effective use of our model is in designing prevention mechanisms for infection control. It can also be used to study the virus spreading behavior for event-driven scenarios in WSNs.
Keywords: Spatial Correlation, Comparative Study, Epidemic Model Design Analysis, Warm Propagation
Scope of the Article: Energy harvesting and transfer for wireless sensor networks