Sumit Kumar (Member, IEEE) received a PhD degree in the area of edge computing enabled Internet of Things from the Indian Institute of Technology (BHU) Varanasi, India, in 2022. He is currently working as an assistant professor with the Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology (NIT), Jalandhar, India. Before joining NIT Jalandhar, he worked as an assistant professor (2016–2017) with GLA Mathura, India, and as an assistant professor (2023–2024) with Galgotias University, Greater Noida, India. His research areas include cloud computing, edge computing, IoT, wireless sensor networks, game theory, and reinforcement learning.
EDUCATION
PhDEdge Computing Enabled IoTs(Indian Institute of Technology (IIT) Varanasi )
M.TechComputer Science and Engineering(National Institute of Technology (NIT) Hamirpur )
B.TechComputer Science and Engineering(Uttar Pradesh Technical University)
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Computational Theory and Mathematics
16
Scopus Publications
223
Scholar Citations
8
Scholar h-index
7
Scholar i10-index
Scopus Publications
Graph Coarsening using Game Theoretic Approach Transactions on Machine Learning Research, 2026
Energy consumption minimisation at edge node using approach in predicting sensor parameters in WSNs Vipin Maurya, Sumit Kumar, Sonali Raj, Ruchir Gupta Scientific Reports, 2025 Owing to limited storage and battery power, wireless sensor nodes often face challenges in maintaining long-term energy sustainability. To address this, only a subset of sensors remains active to monitor different sensor parameters while others get predicted to minimize sensor node energy consumption. In prediction, not all active parameters are equally important, as low-correlated parameters increase computational complexity and decrease accuracy. Researchers use highly correlated active parameters, though existing solutions often use polynomial time and don't ensure optimal parameter set. This paper proposes a cross-correlation-based parameter selection [Formula: see text] approach, ensuring the selected parameter set is stable and Pareto-optimal. Simulations are performed on nine publicly available datasets of environmental data collected from different places and at different sampling intervals to validate the effectiveness of the [Formula: see text] approach. It has been observed that [Formula: see text] approach selects a subset of active parameters faster than existing approaches and reduces energy consumption at the edge node ranges from [Formula: see text] - [Formula: see text] in the prediction of sleep sensor parameters on various datasets.
Resource Optimization in Edge Networks with Game Theory Model Sandhya Thakur, Sumit Kumar Proceedings of 2025 International Conference on Signal Processing Computation Electronics Power and Telecommunication Iconscept 2025, 2025 The Rapid development of edge computing provides decentralized computational platform which minimize delays and improve bandwidth efficiency. Edge computing is increasingly important in today’s dynamic application ecosystem, where edge servers are deployed by firms to deliver a smoother experience to users. To stay competitive, application providers aim to use edge servers as cost effectively as possible. Application providers require a cost effective solution for employing edge infrastructure. This paper introduces a Multi Agent Edge Selection Game (MAES Game), game theory based solution that presents the resource optimization problem at the network edge as a potential game. The MAES Game provides a stable solution, as the application provider will necessarily converge to at least one Pure Nash equilibrium (PNE). Furthermore, the analysis shows that the Price of Stability (PoS) of the MAES Game is bounded by O(log m), ensuring near-optimal cost efficiency in equilibrium.
A Game-Theoretic Approach for Users of Edge Computing: QoS-Aware and Cost-Efficient Prachi Bangade, Sumit Kumar Proceedings of 2025 International Conference on Signal Processing Computation Electronics Power and Telecommunication Iconscept 2025, 2025 In edge computing, numerous independent users, driven by self-interest, collectively shape the system’s behavior. From the user’s perspective, the main priority is obtaining excellent service at the lowest possible price, whereas the system’s goal is to effectively allocate users to make the best use of its server resources. This letter introduces the Edge Server Selection Protocol (ESSP). ESSP effectively balances the interplay between user cost and Quality of Service (QoS), ensuring an equitable load distribution across servers in a competitive, multi-provider environment. ESSP enables users to optimize their individual objectives and rapidly attain a pure Nash equilibrium (PNE). The protocol breaks the problem down into smaller subproblems using distance-2 graph coloring, which speeds up convergence. We confirm that at least one PNE exists and assess its efficacy.
A Distributed Load Balancing Technique for Multitenant Edge Servers With Bottleneck Resources Sumit Kumar, Vipin Maurya, Ruchir Gupta IEEE Transactions on Reliability, 2024 The popularity of edge computing has risen due to the widespread use of online services on IoT and mobile devices. This technology provides geographically distributed edge servers to reduce delays, energy consumption, and bandwidth requirements. However, edge computing faces challenges due to limited computing resources on edge servers and the dynamic density of IoT and mobile device users. In this article, we propose a distributed edge resource allocation approach that can accommodate the dynamic user population on the limited computing resources of edge servers. Our proposed approach aims to balance the loads of edge servers to maximize resource utilization by moving users from overloaded edge servers to underutilized ones. This way, edge computing resources can serve the maximum number of users. In addition, the proposed approach identifies bottleneck resources on edge servers to maintain the quality of service (QoS) provided by the edge servers. Thus, this approach ensures that users' experience remains consistent and meets the required QoS standards. We also validate the performance of the proposed algorithm by simulating it and simulation results show that the approach achieves its objectives and improves the efficiency of edge computing resources compared to state-of-the-art approaches.
A Technique for Faster Convergence of Game-Theoretic Approaches for Edge Computing Resource Allocation Sumit Kumar, Antriksh Goswami, Sonia Kukreja, Vibhav Prakash Singh, Ruchir Gupta IEEE Transactions on Services Computing, 2024 This article addresses the Edge User Allocation (EUA) problem in edge computing, where the appropriate mapping from users to edge servers (ESs) is crucial for optimizing performance metrics. Game theory is one of the powerful tools used in edge computing for user allocation to edge resources and task offloading. However, this approach takes longer to converge to Pure Nash Equilibrium (PNE), which is called a stable optimal solution. In this article, we propose a grouping technique for ESs, enabling parallel execution of game-theoretic approaches to achieve faster convergence at the PNE. Our contributions include the grouping method, the introduction of parallel Best Response (BR) dynamics for rapid convergence, and proof that the parallel BR dynamics will eventually halt at PNE. We also provide empirical evidence demonstrating its efficiency compared to traditional BR dynamics. This research enhances the scalability and effectiveness of game-theoretic approaches in resolving the EUA problem, offering practical solutions for edge computing scenarios.
A Cost-Effective and QoS-Aware User Allocation Approach for Edge Computing Enabled IoT Sumit Kumar, Antriksh Goswami, Ruchir Gupta, Satya P. Singh, Aime Lay-Ekuakille IEEE Internet of Things Journal, 2023 In edge computing, the app vendors hire resources from edge servers and allocate them to app users to overcome the challenge of the limited computing capacities of their IoT devices. An app vendor intends to provide app services to the maximum number of users with the least number of edge servers in order to make efficient use of edge resources while reducing overall system costs. However, when an edge server has to serve more app users than its capacity, the Quality of Service (QoS) deteriorates. Thus, establishing a tradeoff between cost and QoS is a critical challenge in the process of allocating edge computing resources to users. It is referred to as the app user allocation (AUA) problem. To solve the AUA problem, we propose a distributed game-theoretic approach that finds a pure Nash equilibrium (PNE) as the optimal stable solution. We first model the AUA problem as a constrained optimization problem and then introduce a user allocation game (UAGame) to solve it. This UAGame employs a distributed edge server allocation (ESA) algorithm to reach PNE. The time complexity of the ESA algorithm is reduced by the edge server clustering. It has also been shown that the UAGame is a potential game, and therefore the ESA algorithm is guaranteed to converge at PNE. The performance of the ESA algorithm has also been studied theoretically and validated numerically.
Caching Techniques in Edge Computing and Challenges Sumit Kumar, Yajnaseni Dash 2023 3rd International Conference on Advancement in Electronics and Communication Engineering Aece 2023, 2023 Edge computing, a distributed computing concept, brings data processing and storage closer to endpoints or edge devices. Caching methods are crucial in edge computing environments for optimizing performance and minimizing latency and enable faster response times, efficient bandwidth utilization, and enhanced scalability. Edge computing uses caching techniques strategically based on user behaviour studies and access patterns to boost scalability and reduce network congestion. Caching techniques increase the efficacy and performance of edge computing. The parameters that influence efficacy include cache management strategies, network conditions, application features, and data access patterns. This paper presents a brief overview of the caching technologies utilized in edge computing and their challenges.
Graph Coarsening using Game Theoretic Approach S Raj, M Kumar, S Kumar, R Gupta, AK Jaiswal Transactions on Machine Learning Research , 2026 2026
A Game-Theoretic Approach for Users of Edge Computing: QoS-Aware and Cost-Efficient P Bangade, S Kumar 2025 International Conference on Signal Processing, Computation, Electronics … , 2025 2025
Resource Optimization in Edge Networks with Game Theory Model S Thakur, S Kumar 2025 International Conference on Signal Processing, Computation, Electronics … , 2025 2025
Energy consumption minimisation at edge node using approach in predicting sensor parameters in WSNs V Maurya, S Kumar, S Raj, R Gupta Scientific Reports 15 (1), 37422 , 2025 2025
A Technique for Faster Convergence of Game-Theoretic Approaches for Edge Computing Resource Allocation S Kumar, A Goswami, S Kukreja, VP Singh, R Gupta IEEE Transactions on Services Computing 17 (6), 3110-3121 , 2024 2024 Citations: 3
A distributed load balancing technique for multitenant edge servers with bottleneck resources S Kumar, V Maurya, R Gupta IEEE Transactions on Reliability 73 (2), 1147-1159 , 2023 2023 Citations: 18
Caching techniques in edge computing and challenges S Kumar, Y Dash 2023 3rd International Conference on Advancement in Electronics … , 2023 2023 Citations: 11
Qos driven cost-efficient resource allocation in edge computing: A distributed game theoretic approach S Kumar, A Sharma, R Gupta Journal of Computational Science 72, 102106 , 2023 2023 Citations: 9
A cost-effective and QoS-aware user allocation approach for edge computing enabled IoT S Kumar, A Goswami, R Gupta, SP Singh, A Lay-Ekuakille IEEE Internet of Things Journal 10 (2), 1696-1710 , 2022 2022 Citations: 20
Resource allocation in edge computing: A game-theoretic perspective S Kumar, R Gupta, K Lakshmanan 2022 IEEE Global Conference on Computing, Power and Communication … , 2022 2022 Citations: 3
Multicasting: A Game-Theoretic Method for Constructing an Efficient Multicast Tree S Kumar, R Gupta, K Lakshmanan 2022 4th International Conference on Inventive Research in Computing … , 2022 2022 Citations: 1
A game-theoretic approach for increasing resource utilization in edge computing enabled internet of things S Kumar, R Gupta, K Lakshmanan, V Maurya IEEE Access 10, 57974-57989 , 2022 2022 Citations: 29
A game-theoretic approach for cost-effective multicast routing in the Internet of Things S Kumar, A Goswami, R Gupta, SP Singh, A Lay-Ekuakille IEEE Internet of Things Journal 9 (18), 18041-18053 , 2022 2022 Citations: 27
The design of a secure key management system in vehicular ad hoc networks KK Chauhan, S Kumar, S Kumar 2017 conference on information and communication technology (CICT), 1-6 , 2017 2017 Citations: 16
Energy efficient scheduling algorithm with interference reduction for wireless sensor networks S Kumar, A Sharma, SS Raghuvanshi 2011 International Conference on Computational Intelligence and … , 2011 2011 Citations: 7
Event Based Energy Efficient Routing Protocol for Wireless Sensor Networks (WSNs) S Kumar, P Gupta, S Chauhan International Conference on Advanced Computing, Communication and Networks … , 2011 2011
A survey on scheduling algorithms for wireless sensor networks S Kumar, S Chauhan International Journal of Computer Applications 20 (5), 7-13 , 2011 2011 Citations: 79
MOST CITED SCHOLAR PUBLICATIONS
A survey on scheduling algorithms for wireless sensor networks S Kumar, S Chauhan International Journal of Computer Applications 20 (5), 7-13 , 2011 2011 Citations: 79
A game-theoretic approach for increasing resource utilization in edge computing enabled internet of things S Kumar, R Gupta, K Lakshmanan, V Maurya IEEE Access 10, 57974-57989 , 2022 2022 Citations: 29
A game-theoretic approach for cost-effective multicast routing in the Internet of Things S Kumar, A Goswami, R Gupta, SP Singh, A Lay-Ekuakille IEEE Internet of Things Journal 9 (18), 18041-18053 , 2022 2022 Citations: 27
A cost-effective and QoS-aware user allocation approach for edge computing enabled IoT S Kumar, A Goswami, R Gupta, SP Singh, A Lay-Ekuakille IEEE Internet of Things Journal 10 (2), 1696-1710 , 2022 2022 Citations: 20
A distributed load balancing technique for multitenant edge servers with bottleneck resources S Kumar, V Maurya, R Gupta IEEE Transactions on Reliability 73 (2), 1147-1159 , 2023 2023 Citations: 18
The design of a secure key management system in vehicular ad hoc networks KK Chauhan, S Kumar, S Kumar 2017 conference on information and communication technology (CICT), 1-6 , 2017 2017 Citations: 16
Caching techniques in edge computing and challenges S Kumar, Y Dash 2023 3rd International Conference on Advancement in Electronics … , 2023 2023 Citations: 11
Qos driven cost-efficient resource allocation in edge computing: A distributed game theoretic approach S Kumar, A Sharma, R Gupta Journal of Computational Science 72, 102106 , 2023 2023 Citations: 9
Energy efficient scheduling algorithm with interference reduction for wireless sensor networks S Kumar, A Sharma, SS Raghuvanshi 2011 International Conference on Computational Intelligence and … , 2011 2011 Citations: 7
A Technique for Faster Convergence of Game-Theoretic Approaches for Edge Computing Resource Allocation S Kumar, A Goswami, S Kukreja, VP Singh, R Gupta IEEE Transactions on Services Computing 17 (6), 3110-3121 , 2024 2024 Citations: 3
Resource allocation in edge computing: A game-theoretic perspective S Kumar, R Gupta, K Lakshmanan 2022 IEEE Global Conference on Computing, Power and Communication … , 2022 2022 Citations: 3
Multicasting: A Game-Theoretic Method for Constructing an Efficient Multicast Tree S Kumar, R Gupta, K Lakshmanan 2022 4th International Conference on Inventive Research in Computing … , 2022 2022 Citations: 1
Graph Coarsening using Game Theoretic Approach S Raj, M Kumar, S Kumar, R Gupta, AK Jaiswal Transactions on Machine Learning Research , 2026 2026
A Game-Theoretic Approach for Users of Edge Computing: QoS-Aware and Cost-Efficient P Bangade, S Kumar 2025 International Conference on Signal Processing, Computation, Electronics … , 2025 2025
Resource Optimization in Edge Networks with Game Theory Model S Thakur, S Kumar 2025 International Conference on Signal Processing, Computation, Electronics … , 2025 2025
Energy consumption minimisation at edge node using approach in predicting sensor parameters in WSNs V Maurya, S Kumar, S Raj, R Gupta Scientific Reports 15 (1), 37422 , 2025 2025
Event Based Energy Efficient Routing Protocol for Wireless Sensor Networks (WSNs) S Kumar, P Gupta, S Chauhan International Conference on Advanced Computing, Communication and Networks … , 2011 2011
