S
Sambit Kumar Mishra
Researcher at Siksha O Anusandhan University
Publications - 67
Citations - 1187
Sambit Kumar Mishra is an academic researcher from Siksha O Anusandhan University. The author has contributed to research in topics: Cloud computing & Computer science. The author has an hindex of 13, co-authored 54 publications receiving 780 citations. Previous affiliations of Sambit Kumar Mishra include SRM University & National Institute of Technology, Rourkela.
Papers
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Proceedings ArticleDOI
Cloud Computing Features, Issues, and Challenges: A Big Picture
TL;DR: This paper discusses the cloud computing architecture and the numerous services it offered, and identifies several security issues in cloud computing based on its service layer and highlights the available platforms for cloud research and development.
Journal ArticleDOI
Load balancing in cloud computing: A big picture
TL;DR: A taxonomy for the load balancing algorithms in the cloud is presented and a brief explanation of considered performance parameters in the literature and their effects is presented in this paper.
Journal ArticleDOI
Sustainable Service Allocation Using a Metaheuristic Technique in a Fog Server for Industrial Applications
TL;DR: This paper proposes a meta heuristic-based service allocation framework using three metaheuristic techniques, such as particle swarm optimization (PSO), binary PSO, and bat algorithm that allow us to deal with the heterogeneity of resources in the fog computing environment.
Journal ArticleDOI
An adaptive task allocation technique for green cloud computing
Sambit Kumar Mishra,Deepak Puthal,Bibhudatta Sahoo,Sanjay Kumar Jena,Mohammad S. Obaidat,Mohammad S. Obaidat +5 more
TL;DR: This paper has studied the energy consumption in cloud environment based on varieties of services and achieved the provisions to promote green cloud computing and proposed an adaptive task allocation algorithm for the heterogeneous cloud environment.
Journal ArticleDOI
Energy-efficient VM-placement in cloud data center
Sambit Kumar Mishra,Deepak Puthal,Bibhudatta Sahoo,Prem Prakash Jayaraman,Song Jun,Albert Y. Zomaya,Rajiv Ranjan,Rajiv Ranjan +7 more
TL;DR: The proposed algorithm reduces the energy consumption by depreciating the number of active PMs, while also minimizes the makespan and task rejection rate and demonstrates the effectiveness of the proposed algorithm over some existing standard algorithms.