Energy Efficient Workflow Scheduling Algorithm for Latency-Sensitive Applications using Cloud-Fog Collaboration Prashant Shukla, Sudhakar Pandey International Symposium on Advanced Networks and Telecommunication Systems Ants, 2023 The objectives of most studies are aimed at employing fog computing (FC) as an effective support to cloud computing (CC) in order to monitor sensor data and their associated necessities via the rapid advancements in Internet of Things (IoT). FC is completely dedicated to IoT sensor systems and delivers CC based computing, networking, and storage services. The cloud-Fog Collaboration (CFC) Environment will be more suitable for real-time IoT data sensing and workflow applications where fast and reliable internet connectivity is available. Workflow Scheduling means efficiently assigning the interdependent tasks to available computing resources. The workflow scheduling techniques play a significant role in minimizing the latency in Heterogeneous Computing systems (HCS). In this paper, we present a novel Hybrid-metaheuristics Multi-objective based Workflow Scheduling Algorithm (HMWSA) by combining Harmony Search (HS) and Genetic Algorithm (GA) for optimizing workflow scheduling in heterogeneous CFC. The proposed minimization objective function takes into account goals like makespan, energy usage, and cost. To preserve the precedence relationship among tasks, a topologically sorted execution sequence is constructed. Extensive testing results show that our proposed approach yields substantially better cost-makespan trade-offs while significantly reducing energy consumption than other existing algorithms.
An Efficient Offloading Technique using DQN for MEC-IoT Networks Prashant Shukla, Sudhakar Pandey, Deepika Agarwal 2023 6th International Conference on Information Systems and Computer Networks Iscon 2023, 2023 In today’s day there are billions of interconnected smart devices present which are called Internet-of-Things (IoT). It contains software, sensors and a bunch of other technologies trying to connect the systems with the purpose of sharing information over the internet. This system is producing massive amounts of data over the internet. This massive amount of data requires an appropriate spectrum to transmit the data to their server. so that it benefits us in an economical way. Machine learning has been successful in fields of speech recognition, graphics, prediction and decision making. Machine learning is used in our research for optimally allocating the resources. Edge computing can be a possible solution for IoT networks because it puts computer capabilities closer to the user. IoT users have recently been created to have more powerful computing abilities, allowing them to run few tasks locally. The article tries to use edge computing with Machine learning for optimal allocation of resources. K-means clustering algorithm is used to cluster the IoT user into different clusters depending on the distance and feature of their user priority. The cluster of higher priority is executed at the edge level while the lower cluster is executed at the local level. The challenge is to provide a long-term solution for the economical, effective resource allocation in the available spectrum with minimum energy usage. A deep Q-network (DQN) based computational offloading technique is also created to gain knowledge of the appropriate computational offload plan. Furthermore, the DQN-based computational offloading technique surpasses the baseline systems. Through the simulation results, it is concluded that the proposed approach outperforms with the state-of-the-art models.
ECO-RL-ECA: Efficient Computation Offloading using Reinforcement Learning in Edge-Cloud Architecture Prashant Shukla, Shivani Gupta, Sudhakar Pandey Ocit 2023 21st International Conference on Information Technology Proceedings, 2023 With the development of numerous delay-sensitive applications, it has become very difficult to perform all the tasks locally because our mobile devices have less computation power. Traditional cloud servers have high computational power and storage, but they’re located far away from IoT devices, so they take extra time and energy for transmission before the execution of tasks. Local devices and cloud servers are not appropriate for these time-sensitive applications. To resolve this real-time issue, the idea of edge computing was developed, where we can offload our task to edge devices that are closer to the user device than a cloud server and hence consume less time and energy to execute the same task. The task can either run locally, on an edge device, or on a cloud server. We modelled our problem from a constrained real space to a finite discrete space using the Markov Decision Process and derived our solutions using reinforcement learning to reduce the execution time for delay-sensitive applications. The proposed method is found to be more effective at reducing execution time.
MOHBA: multi-objective honey badger algorithm for workflow scheduling in heterogeneous cloud–fog-IoT networks P Shukla, D Agrawal, S Pandey, R Mahapatra International Journal of Information Technology 17 (3), 1619-1630 , 2025 2025.0 Citations: 6
PES-DAS: Privacy Enhancing Subset-Data Aggregation Scheme Leveraging Homomorphic Cryptosystem in Fog-Cloud Based IoT Applications P Shukla, S Pandey SN Computer Science 6 (3), 287 , 2025 2025.0 Citations: 1
MOTORS: multi-objective task offloading and resource scheduling algorithm for heterogeneous fog-cloud computing scenario P Shukla, S Pandey The Journal of Supercomputing 80 (15), 22315-22361 , 2024 2024.0 Citations: 22
DE-GWO: A multi-objective workflow scheduling algorithm for heterogeneous fog-cloud environment P Shukla, S Pandey Arabian Journal for Science and Engineering 49 (3), 4419-4444 , 2024 2024.0 Citations: 28
Energy efficient workflow scheduling algorithm for latency-sensitive applications using cloud-fog collaboration P Shukla, S Pandey 2023 IEEE International Conference on Advanced Networks and … , 2023 2023.0 Citations: 5
ECO-RL-ECA: efficient computation offloading using reinforcement learning in edge-cloud architecture P Shukla, S Gupta, S Pandey 2023 OITS International Conference on Information Technology (OCIT), 605-610 , 2023 2023.0 Citations: 5
FDA-TO-FCA: Flow Direction Algorithm-Based Task Offloading in Fog-Cloud Architecture P Shukla, S Pandey, S Gupta, D Agrawal International Conference on Smart Systems: Innovations in Computing, 359-371 , 2023 2023.0
MAA: multi-objective artificial algae algorithm for workflow scheduling in heterogeneous fog-cloud environment: P. Shukla and S. Pandey P Shukla, S Pandey The Journal of Supercomputing 79 (10), 11218-11260 , 2023 2023.0 Citations: 35
FAT-ETO: Fuzzy-AHP-TOPSIS-Based efficient task offloading algorithm for scientific workflows in heterogeneous fog–cloud environment P Shukla, S Pandey, P Hatwar, A Pant Proceedings of the national academy of sciences, india section a: physical … , 2023 2023.0 Citations: 24
An efficient offloading technique using DQN for MEC-IoT networks P Shukla, S Pandey, D Agarwal 2023 6th International Conference on Information Systems and Computer … , 2023 2023.0 Citations: 13
An efficient group-based neighbor discovery for wireless sensor networks S Pandey, P Shukla, A Tripathi 2021 Third International Conference on Intelligent Communication … , 2021 2021.0 Citations: 5
Birthday Protocol for Efficient Node Deployment and Neighbour Discovery in Wireless Sensor Network S Pandey, P Shukla, D Kalwani 2021 Third International Conference on Intelligent Communication … , 2021 2021.0
Security issues, challenges and solutions for wireless sensor networks (WSN): a review P Shukla Research Journal of Engineering and Technology 11 (2), 62-68 , 2020 2020.0 Citations: 1
Statistical Based Fault Node Detection Algorithms For Wireless Sensor Networks PS RR Panda International Conference on Telecommunication, Power Analysis and Computing … , 2017 2017.0
Neighbor co-ordination based fault node detection algorithm for distributed wireless sensor networks P Shukla, RR Panda International Journal of Engineering Research & Technology 6 (9), 261-265 , 2017 2017.0 Citations: 2
Task Offloading in Edge Computing using Reinforcement Learning PS S Gupta, S Pandey 7th International Conference on Microelectronics, Computing & Communication … , 0
MOST CITED SCHOLAR PUBLICATIONS
MAA: multi-objective artificial algae algorithm for workflow scheduling in heterogeneous fog-cloud environment: P. Shukla and S. Pandey P Shukla, S Pandey The Journal of Supercomputing 79 (10), 11218-11260 , 2023 2023.0 Citations: 35
DE-GWO: A multi-objective workflow scheduling algorithm for heterogeneous fog-cloud environment P Shukla, S Pandey Arabian Journal for Science and Engineering 49 (3), 4419-4444 , 2024 2024.0 Citations: 28
FAT-ETO: Fuzzy-AHP-TOPSIS-Based efficient task offloading algorithm for scientific workflows in heterogeneous fog–cloud environment P Shukla, S Pandey, P Hatwar, A Pant Proceedings of the national academy of sciences, india section a: physical … , 2023 2023.0 Citations: 24
MOTORS: multi-objective task offloading and resource scheduling algorithm for heterogeneous fog-cloud computing scenario P Shukla, S Pandey The Journal of Supercomputing 80 (15), 22315-22361 , 2024 2024.0 Citations: 22
An efficient offloading technique using DQN for MEC-IoT networks P Shukla, S Pandey, D Agarwal 2023 6th International Conference on Information Systems and Computer … , 2023 2023.0 Citations: 13
MOHBA: multi-objective honey badger algorithm for workflow scheduling in heterogeneous cloud–fog-IoT networks P Shukla, D Agrawal, S Pandey, R Mahapatra International Journal of Information Technology 17 (3), 1619-1630 , 2025 2025.0 Citations: 6
Energy efficient workflow scheduling algorithm for latency-sensitive applications using cloud-fog collaboration P Shukla, S Pandey 2023 IEEE International Conference on Advanced Networks and … , 2023 2023.0 Citations: 5
ECO-RL-ECA: efficient computation offloading using reinforcement learning in edge-cloud architecture P Shukla, S Gupta, S Pandey 2023 OITS International Conference on Information Technology (OCIT), 605-610 , 2023 2023.0 Citations: 5
An efficient group-based neighbor discovery for wireless sensor networks S Pandey, P Shukla, A Tripathi 2021 Third International Conference on Intelligent Communication … , 2021 2021.0 Citations: 5
Neighbor co-ordination based fault node detection algorithm for distributed wireless sensor networks P Shukla, RR Panda International Journal of Engineering Research & Technology 6 (9), 261-265 , 2017 2017.0 Citations: 2
PES-DAS: Privacy Enhancing Subset-Data Aggregation Scheme Leveraging Homomorphic Cryptosystem in Fog-Cloud Based IoT Applications P Shukla, S Pandey SN Computer Science 6 (3), 287 , 2025 2025.0 Citations: 1
Security issues, challenges and solutions for wireless sensor networks (WSN): a review P Shukla Research Journal of Engineering and Technology 11 (2), 62-68 , 2020 2020.0 Citations: 1
FDA-TO-FCA: Flow Direction Algorithm-Based Task Offloading in Fog-Cloud Architecture P Shukla, S Pandey, S Gupta, D Agrawal International Conference on Smart Systems: Innovations in Computing, 359-371 , 2023 2023.0
Birthday Protocol for Efficient Node Deployment and Neighbour Discovery in Wireless Sensor Network S Pandey, P Shukla, D Kalwani 2021 Third International Conference on Intelligent Communication … , 2021 2021.0
Statistical Based Fault Node Detection Algorithms For Wireless Sensor Networks PS RR Panda International Conference on Telecommunication, Power Analysis and Computing … , 2017 2017.0
Task Offloading in Edge Computing using Reinforcement Learning PS S Gupta, S Pandey 7th International Conference on Microelectronics, Computing & Communication … , 0
