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Narasimhan, B.

Reliable Dynamic Source Routing Protocol (RDSRP) for Energy Harvesting Wireless Sensor Networks

Development of India’s First Integrated Expert Urban Flood Forecasting System for Chennai

Abstract Views :263 | PDF Views:71

Authors

Subimal Ghosh ¹, Subhankar Karmakar ², Anamitra Saha ¹, Mohit Prakash Mohanty ³, Shees Ali ¹, Satya Kiran Raju ⁴, Vrinda Krishnakumar ¹, Maneesha Sebastian ¹, Manasa Ranjan Behera ¹, R. Ashrit ⁵, P. L. N. Murty ⁶, K. Srinivas ⁶, B. Narasimhan ⁷, Tune Usha ⁴, M. V. Ramana Murthy ⁴, P. Thiruvengadam ¹, J. Indu ¹, D. Thirumalaivasan ⁸, John P. George ⁵, S. Gedam ⁹, A. B. Inamdar ⁹, B. S. Murty ⁷, P. P. Mujumdar ¹⁰, M. Mohapatra ¹¹, Arun Bhardwaj ¹², Swati Basu ¹², Shailesh Nayak ¹³

Affiliations
1 Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, IN
2 Interdisciplinary Program in Climate Studies, Indian Institute of Technology Bombay, Mumbai 400 076, IN
3 Environmental Science and Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, IN
4 National Centre for Coastal Research, NIOT Campus, Velacherry–Tambaram Main Road, Pallikaranai, Chennai 600 100, IN
5 National Centre for Medium Range Weather Forecasting, Ministry of Earth Sciences, Government of India, A-50, Sector-62, Noida 201 309, IN
6 Indian National Centre for Ocean Information Services, Pragathi Nagar (BO), Nizampet (SO), Hyderabad 500 090, IN
7 Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600 036, IN
8 Institute of Remote Sensing, Anna University, Chennai 600 040, IN
9 Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, IN
10 Department of Civil Engineering, Indian Institute of Science, Bengaluru 560 012, IN
11 India Meteorological Department, New Delhi 110 003, IN
12 Office of the Principal Scientific Adviser to the Government of India, Vigyan Bhavan Annexe, Maulana Azad Road, New Delhi 110 011, IN
13 National Institute of Advanced Studies, Indian Institute of Science Campus, Bengaluru 560 012, IN

Source

Current Science, Vol 117, No 5 (2019), Pagination: 741-745

Abstract

Floods are the most common and recurring natural hazards faced by humans since time immemorial. They pose a severe threat to the population, environment and economy in many places across the world, especially urban areas. Urbanization caused due to increasing migration into the floodplains has substantially increased the trend of devastation due to floods in a developing country like India. In Chennai and the surrounding suburban areas, torrential rainfall associated with low-pressure systems engulfed the city during December 2015, affecting more than 4 million people along with economic damages that cost around 3 billion USD.

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References

Sarkar, A., Paromita Chakraborty, John P. George and Rajagopal, E. N., Report, NMRF/TR/02/2016, 2016; https://www.ncmrwf.gov.in/Reports-eng/NMRF_TR2_ 2016.pdf

Shastri, H., Ghosh, S. and Karmakar, S., J. Geophys. Res. Atmos., 2017, 122(3), 1617–1634.

Thiruvengadam, P., Indu, J. and Ghosh, S., Adv. Water Resour., 2019, 126, 24–39.

Luettich Jr, R. A. and Westerink, J. J., Int. J. Numer. Methods Fluids, 1991, 12(10), 911–928; https://doi.org/10.1002/fld.1650121002.

Mohanty, M. P., Sherly, M. A., Karmakar, S. and Ghosh, S., Water Resour. Manage., 2018, 32(14), 4725–4746.

Constrained Cuckoo Search Optimization Based Protocol for Routing in Cloud Network

Abstract Views :212 | PDF Views:1

Authors

J. Ramkumar ¹, R. Vadivel ², B. Narasimhan ³

Affiliations
1 PG and Research Department of Computer Science, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Bharathiar University, Coimbatore, Tamil Nadu, IN
3 Department of Computer Technology, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, IN

Source

International Journal of Computer Networks and Applications, Vol 8, No 6 (2021), Pagination: 795-803

Abstract

Cloud Computing (CC) is the process of providing on-demand data to the user via the internet. In CC, users don't need to manage data storage and computational power actively. Finding the best route in a cloud network is entirely different from other general networks which it is due to high scalability. Protocols developed for other general networks will never suit or give better performance in cloud networks due to its scalability. This paper proposes a bio-inspired protocol for routing in a cloud network, namely Constrained Cuckoo Search Optimization-based Protocol (CCSOP). The routing strategy of CCSOP is inspired by the natural characteristics of the cuckoo bird towards finding a nest to lay its eggs. Levy Flight concept is applied with different constraints to enhance optimization performance towards finding the best route in a cloud network that minimizes energy consumption. CCSOP is evaluated in Greencloud using benchmark network performance metrics against the current routing protocols. The efficacy of CCSOP is evaluated using benchmark performance measures. CCSOP appears to outperform current cloud network routing protocols in terms of energy consumption.

Keywords

Cuckoo, Cloud, Energy, Flight, Levy, Optimization, Routing, Scalability.

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References

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Enhanced Particle Swarm Optimization based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing (EPSOGPSR) for Underwater Wireless Sensor Networks (UWSNs)

Abstract Views :43 | PDF Views:1

Authors

B. Narasimhan ¹, B. Karthikeyan ²

Affiliations
1 Assistant Professor (SG), Department of Computer Science, Nehru Arts and Science College, Coimbatore, IN
2 Assistant Professor, Department of Information Technology, Nehru Arts and Science College, Coimbatore, IN

Source

International Journal of Advanced Networking and Applications, Vol 15, No 4 (2023), Pagination: 6028 - 6033

Abstract

EPSO-GPSR (Enhanced Particle Swarm Optimization-based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing), a unique strategy designed specifically for WSNs, is presented in this work. Using Enhanced Particle Swarm Optimization (EPSO) to provide load balancing across sensor nodes, the proposed EPSO-GPSR technique reduces energy disparities and increases the operational lifetime of the network. Additionally, it interfaces with the geographic routing protocol Greedy Perimeter Stateless Routing (GPSR) to enable effective data forwarding based on geographic locations, minimizing communication overhead and improving scalability. EPSO-GPSR's efficacy is shown against traditional load balancing and routing methods via comprehensive simulations and performance assessments. The network lifetime, energy efficiency, throughput, packet delivery ratio, and delay have all significantly showed better performance, according to the results. Additionally, the EPSO-GPSR algorithm demonstrates robustness against node failures and issues related to scalability, indicating a significant potential for real-world implementation in various WSN scenarios.

Keywords

Underwater Wireless Sensor Networks, load balancing, network lifetime, throughput, delay, packet delivery ratio, routing, greedy perimeter, stateless routing.

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References

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Author Details

Narasimhan, B.

Reliable Dynamic Source Routing Protocol (RDSRP) for Energy Harvesting Wireless Sensor Networks

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Development of India’s First Integrated Expert Urban Flood Forecasting System for Chennai

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Constrained Cuckoo Search Optimization Based Protocol for Routing in Cloud Network

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Enhanced Particle Swarm Optimization based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing (EPSOGPSR) for Underwater Wireless Sensor Networks (UWSNs)

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