Work place: CSED, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India
E-mail: shashank12@mnnit.ac.in
Website:
Research Interests: Computer systems and computational processes, Network Architecture, Network Security, Data Structures and Algorithms, Combinatorial Optimization
Biography
Shashank Srivastava obtained his Ph.D. degree at Indian Institute of Information Technology Allahabad, India in 2014. He is currently working as Assistant Professor in the Department of CSE, Motilal Nehru National Institute of Technology Allahabad, 211004, India. He possesses an experience of more than six years in the field of teaching and research. He has published various research papers in the area of Network and security. At present he is guiding five Ph.D. students in the field of Software Defined Networking (SDN), Named Data Networking (NDN), Network flow optimization and security. He is having the Membership of IEEE, ACM, CSI and CRSI (Cryptographic Research Society of India). His areas of expertise are SDN, NDN, information security, and future internet technologies.
By Ashutosh Kumar Singh Naveen Kumar Shashank Srivastava
DOI: https://doi.org/10.5815/ijcnis.2019.02.05, Pub. Date: 8 Feb. 2019
SDN (software defined networks) is a programmable network architecture that divides the forwarding plane and control plane. It can centrally manage the network through a software program, i.e., controller. Multiple controllers are required to manage the current software defined WAN. Placing multiple controllers in a network is known as controller placement problem (CPP). Only one controller is not capable to handle the scalability and reliability issues. To tackle these issues, multiple controllers are required. Efficient deployment of controllers in SDN is used to improve the performance and reliability of the network. To the best of our knowledge, this is the first attempt to minimize the total average latency of reliable SDN along with the implementation of TLBO and PSO algorithms to solve CPP. Our experimental results show that TLBO outperforms PSO for publicly available topologies.
[...] Read more.By Ashutosh Kumar Singh Saurabh Shashank Srivastava
DOI: https://doi.org/10.5815/ijisa.2018.12.01, Pub. Date: 8 Dec. 2018
A new and simple optimization algorithm known as Varna-based Optimization (VBO) is introduced in this paper for solving optimization problems. It is inspired by the human-society structure and human behavior. Varna (a Sanskrit word, which means Class) is decided by people’s Karma (a Sanskrit word, which means Action), not by their birth. The performance of the proposed method is examined by experimenting it on six unconstrained, and five constrained benchmark functions having different characteristics. Its results are compared with other well-known optimization methods (PSO, TLBO, and Jaya) for multi-dimensional numeric problems. Our experimental results show that the VBO outperforms other optimization algorithms and have proved the better effectiveness of the proposed algorithm.
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