Sampa Sahoo

@cgu-odisha.ac.in

Associate Professor, CSE Department
C.V.Raman Global University, Bhubaneswar

Sampa Sahoo


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https://researchid.co/sampa44

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Computer Science Applications, Information Systems, Artificial Intelligence
53

Scopus Publications

616

Scholar Citations

14

Scholar h-index

18

Scholar i10-index

Scopus Publications

  • Energy and makespan optimised task mapping in fog enabled IoT application: a hybrid approach
    Niva Tripathy, Sampa Sahoo, Norah Saleh Alghamdi, Wattana Viriyasitavat, Gaurav Dhiman
    Scientific Reports, 2026
    The Internet of Things (IoT) points to billions of connected devices that share data through the Internet. However, the increasing volume of data generated by IoT devices makes remote cloud data centers inefficient for delay-sensitive applications. In this regard, fog computing, which brings computation closer to the data source, plays a significant role in addressing the above issue. However, resource constraints in fog computing demand an effective task-scheduling technique to handle the enormous volume of data. Many researchers have proposed a variety of heuristic and meta-heuristic approaches for effective scheduling; however, there is still scope for improvement. In this paper, we propose EMAPSO (energy makespan-aware PSO). The simultaneous minimization of makespan and energy is presented as a bi-objective optimization problem. The approach also considered the load-balancing factor while assigning a task to a VM in a fog/cloud environment. The proposed algorithm, EMAPSO, is compared to standard PSO, Modified PSO (MPSO), Bird swarm optimization (BSO), and the Bee Life Algorithm (BLA). The experimental results show that the proposed method outperforms the compared algorithms in terms of resource utilization, makespan, and energy consumption.
  • Z-Secure: Chaos-Enhanced Facial Biometric Key Generation for Secure Image Encryption with Anti-Spoofing Protection and Multi-Modal Liveness Detection
    Subhashis Ghosh, Ipsita Giri, Shubhjeet Khan, Gourishankar Mohapatra, Sampa Sahoo
    Proceedings of the 4th IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation Iatmsi 2026, 2026
    Image encryption systems increasingly rely on biometric authentication for security, yet face critical vulnerabilities in key generation, template storage, and spoofing attacks. This paper presents Z-Secure, a novel framework that leverages facial biometric features enhanced with Lorenz attractor chaos theory for robust image encryption. The system extracts 128-dimensional facial encodings using deep convolutional neural networks and applies chaos-based transformations to generate cryptographic keys through PBKDF2 derivation. A multi-modal liveness detection mechanism using MediaPipe Face Mesh with 468 landmarks prevents presentation attacks through eye aspect ratio analysis, head pose estimation, and texture variance measurement. Implementing AES-256-(Cipher Block Chaining))encryption within a zero-knowledge architecture, the system achieves 99.61% NPCR and 33.46% UACI for encrypted images, indicating excellent cryptographic quality. Experimental results demonstrate 47.6% entropy improvement over traditional biometric systems, 96.2% liveness detection accuracy against spoofing attacks, and complete image encryption/decryption within 721ms. The framework provides irreversible template protection, cross-session unlinkability, and user-controlled key revocability, making it suitable for privacy-preserving image security applications.
  • An efficient task offloading approach to reduce energy consumption in fog architecture
    Niva Tripathy, Sampa Sahoo, Suvendu Chandan Nayak, Cheng-Chi Lee
    Computers and Electrical Engineering, 2025
  • An efficient camouflaged image segmentation with modified UNet and attention techniques
    Isha Padhy, Prabhat Dansena, Sampa Sahoo, Rahul Priyadarshi
    Scientific Reports, 2025
    Camouflaged object segmentation (COS) is a challenging task in computer vision where the objective is to recognize and precisely separate objects that blend in with their environment. Traditional models, including the standard UNet architecture, struggle with this task due to ambiguous object boundaries, texture similarity between object and background, and over-segmentation or under-segmentation caused by redundant skip connections. CAMO-UNet addresses these issues by including residual blocks which improve feature learning by easing the gradient flow and enabling deeper architectures. The attention mechanism focuses on 'what' is important, 'where' important features are located in the spatial domain and captures long-range dependencies across the image. The Depth-aware triangular cyclic learning rate (CLR) dynamically adjusts learning rates at different network depths to enhance training efficiency. CAMO-UNet achieved 93.8% accuracy on benchmark datasets and outperformed state-of-the-art models like SINet, BGNet, PFNet, etc., in metrics including S-measure, F-measure, MAE, and accuracy.
  • Camouflaged object detection using hybrid-deep learning model
    Isha Padhy, Teja Sai Chenna Malleswar Rao J, Venkata Koti Reddy CH, Priyadarshi Kanungo, Sampa Sahoo
    Multimedia Tools and Applications, 2025
  • Comparative Analysis of Geographical Distance Methods: Haversine, Spherical Law of Cosines, Vincenty, Karney, and Great Elliptic Distance
    Tanishq Vats, Satyam Kumar, Ujjwal Kumar Sinha, Sampa Sahoo
    2025 IEEE 4th World Conference on Applied Intelligence and Computing Aic 2025, 2025
    Accurate geodesic distance calculations are essential for navigation, geospatial services, and edge computing. This study compares five methods—Haversine, Spherical Law of Cosines, Vincenty, Karney, and Great Elliptic Distance—on accuracy, computational time, and memory usage using 10,000 random coordinate pairs. Vincenty and Karney achieved zero error but required higher computation times (5.54 s and 4.11s), while Haversine and Cosine were fastest (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{0}. \mathbf{3 s}$</tex>) with minor errors (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\tilde{\mathbf{0}}. 16 \%$</tex> MAPE). Great Elliptic offered balanced performance (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{0}. \mathbf{1 8} \boldsymbol{\%}$</tex> MAPE). The findings reveal trade-offs between precision and efficiency, guiding the selection of methods for edge server deployment.
  • U-Net: A Binary Segmentation Architecture for Building Localization in Structural Health Monitoring using the xBD Dataset
    Sakshi Suwarna, Sampa Sahoo, Tanisha, Sanchali Srivastava, Khushi Raj Das, Surendra Kumar Panda
    3rd International Conference on Microwave Optical and Communication Engineering Icmoce 2025, 2025
    Structural Health Monitoring (SHM) is essential in disaster scenarios, providing critical support for building localization, accurate damage assessment, and effective classification of damage severity. SHM refers to the process of monitoring and tracking the condition of engineering structures over a period of time to detect damages, deterioration or potential failures. Localization in such scenarios aids in identifying the buildings and generating ground truth. Traditional techniques of damage assessment are often manual and increases the labor cost due to onsite inspection. This paper aims to propose a methodology based on image segmentation which includes UNet, a Deep Neural Network(DNN) based architecture with a ResNet-50 encoder and custom decoder. It is used to detect and localize buildings from the predicted masks and classify them as Building Detected(1) and No Building(0) based on the probability scores. The proposed approach has achieved a test accuracy of 0.9727 and an Intersection over Union (IoU) score of 0.6289 and a Dice Coefficient score of 0.7721 on all 11 disaster types present in the xBD dataset. The proposed model is further compared with other segmentation architectures like Fully Convolutional Networks (FCNs) and Attention U-Net based on IoU and Dice Coefficient scores. The proposed model shows better performance as compared to the existing models.
  • A learning automata based edge resource allocation approach for IoT-enabled smart cities
    Sampa Sahoo, Kshira Sagar Sahoo, Bibhudatta Sahoo, Amir H. Gandomi
    Digital Communications and Networks, 2024
    The development of the Internet of Things (IoT) technology leading to a new era of smart applications such as smart transportation, buildings, and smart homes. Moreover, these applications act as the building blocks of IoT-enabled smart cities. The high volume and high velocity of data generated by various smart city applications are sent to flexible and efficient cloud computing resources for processing. However, there is a high computation latency due to the presence of a remote cloud server. Edge computing, which brings the computation close to the data source is introduced to overcome this problem. In an IoT-enabled smart city environment, one of the main concerns is to consume the least amount of energy while executing tasks that satisfy the delay constraint. An efficient resource allocation at the edge is helpful to address this issue. In this paper, an energy and delay minimization problem in a smart city environment is formulated as a bi-objective edge resource allocation problem. First, we presented a three-layer network architecture for IoT-enabled smart cities. Then, we designed a learning automata-based edge resource allocation approach considering the three-layer network architecture to solve the said bi-objective minimization problem. Learning Automata (LA) is a reinforcement-based adaptive decision-maker that helps to find the best task and edge resource mapping. An extensive set of simulations is performed to demonstrate the applicability and effectiveness of the LA-based approach in the IoT-enabled smart city environment.
  • Cloud computing for a secure smart city beyond 5G
    Manoj Kumar Patra, Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    Secure and Intelligent Iot Enabled Smart Cities, 2024
    As the evolution of technology ushers in an era beyond 5G, integrating cloud computing into the landscape of smart cities becomes paramount. This chapter delves into the foundational concept of cloud computing and elucidates its pivotal role in shaping the future of secure and connected smart cities. With its on-demand services, scalability, and cost-effectiveness, cloud computing emerges as a key enabler for handling the intricate demands of urban environments. The chapter begins by defining cloud computing and providing an overview of its essential characteristics. It then pivots to the dynamic context of smart cities, where an intricate web of internet of things (IoT) devices, sensors, and urban systems generate copious amounts of data. Cloud computing offers a robust solution for storing, processing, and analyzing this data, empowering smart cities with real-time insights and informed decision-making capabilities. This chapter explores the synergy between cloud computing and 5G networks, emphasizing the importance of high-speed connectivity and low latency in the smart city paradigm. The integration of edge computing further enriches the smart city infrastructure, enabling rapid local processing and reducing latency for time-sensitive applications. Security, a paramount concern in smart city environments, is addressed as the chapter delves into the challenges and solutions provided by cloud computing. The role of cloud platforms in safeguarding citizen data, managing cyber-physical threats, and ensuring compliance with regulatory frameworks is thoroughly examined. This chapter also explores emerging trends, such as the integration of artificial intelligence and blockchain technologies, offering a glimpse into the future of cloud computing in the smart city landscape. In conclusion, this chapter not only defines the synergy between cloud computing and smart cities but also provides a comprehensive understanding of how cloud computing, in the context of 5G and beyond, is instrumental in fostering secure, connected, and resilient urban environments.
  • Energy Aware Effective Task Offloading Mechanism in Fog Computing
    Niva Tripathy, Sampa Sahoo
    Communications in Computer and Information Science, 2024
  • Multiclass Classification of Camouflage Images Using Combined WLD and LPQ Feature Set Using a ANN Classifier
    Isha Padhy, Priyadarshi Kanungo, Sampa Sahoo
    Lecture Notes in Electrical Engineering, 2024
  • Fake News Detection Using Passive Aggressive Classifier (PAC) & Neural Network: A Hybrid Approach
    Om Prakash Mohanta, Gourav Swain, Kumar Ashutosh, Arpit Padhy, Sampa Sahoo
    2024 IEEE International Conference on Smart Power Control and Renewable Energy Icspcre 2024, 2024
  • Energy Aware Task Scheduling in IoT Based Fog Environment
    Niva Tripathy, Sampa Sahoo, Suvendu Chandan Nayak
    Ocit 2023 21st International Conference on Information Technology Proceedings, 2023
  • A YCbCr Model Based Shadow Detection and Removal Approach On Camouflaged Images
    Isha Padhy, Priyadarshi Kanungo, Sampa Sahoo
    Proceedings 2022 Oits International Conference on Information Technology Ocit 2022, 2022
  • Serverless Implementation of Data Wizard Application using Azure Kubernetes Service and Docker
    Kishor Kumar Sethy, Debabrata Singh, Anil Kumar Biswal, Sampa Sahoo
    Proceedings of 2022 1st IEEE International Conference on Industrial Electronics Developments and Applications Icidea 2022, 2022
  • Modeling Internet of Things-Based Solution for Evading Congestion and Blockage in Waterways
    Madhuri Rao, Narendra Kumar Kamila, Sampa Sahoo, Kulamala Vinod Kumar
    Smart Innovation Systems and Technologies, 2022
  • Design of An Authentication Scheme for Cloud-Based IoT Applications*
    Sampa Sahoo, Shreeya Swagatika Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    IETE Technical Review Institution of Electronics and Telecommunication Engineers India, 2022
  • Queuing Theory-Based Analysis of Berth Allocation and Management in Paradip Port for Container Ships
    Madhuri Rao, Narendra Kumar Kamila, Kulamala Vinod Kumar, Debahuti Mishra, Sampa Sahoo
    Lecture Notes in Electrical Engineering, 2022
  • A Learning Automata-Based Scheduling for Deadline Sensitive Task in the Cloud
    Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    IEEE Transactions on Services Computing, 2021
  • An Auction based Edge Resource Allocation Mechanism for IoT-enabled Smart Cities
    Sampa Sahoo, Kshira Sagar Sahoo, Bibhudatta Sahoo, Amir H. Gandomi
    2020 IEEE Symposium Series on Computational Intelligence Ssci 2020, 2020
  • Energy-Efficient Service Allocation Techniques in Cloud: A Survey
    Sambit Kumar Mishra, Sampa Sahoo, Bibhudatta Sahoo, Sanjay Kumar Jena
    IETE Technical Review Institution of Electronics and Telecommunication Engineers India, 2020
  • Modified Grey Wolf Optimization(GWO) based Accident Deterrence in Internet of Things (IoT) enabled Mining Industry
    Deepak Majhi, Madhuri Rao, Sampa Sahoo, Shiba Prasad Dash, Durga Prasad Mohapatra
    2020 International Conference on Computer Science Engineering and Applications Iccsea 2020, 2020
  • Priority queue based real-time task scheduling in virtualized cloud environment
    Pratyush Jagaty, Sampa Sahoo, Dimple Patel, Bibhudatta Sahoo
    2020 7th International Conference on Signal Processing and Integrated Networks Spin 2020, 2020
  • An Interoperable ECC based Authentication and Key Agreement Scheme for IoT Environment
    Asit Sahoo, Shreeya Swagatika Sahoo, Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    2020 International Conference on Communication Systems and Networks Comsnets 2020, 2020
  • Game theoretic approach for real-time task scheduling in cloud computing environment
    Manoj Kumar Patra, Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    Proceedings 2019 International Conference on Information Technology Icit 2019, 2019
  • Metaheuristic Techniques for Controller Placement in Software-Defined Networks
    Sagarika Mohanty, Prateekshya Priyadarshini, Sampa Sahoo, Bibhudatta Sahoo, Srinivas Sethi
    IEEE Region 10 Annual International Conference Proceedings TENCON, 2019
  • Toward secure software-defined networks against distributed denial of service attack
    Kshira Sagar Sahoo, Sanjaya Kumar Panda, Sampa Sahoo, Bibhudatta Sahoo, Ratnakar Dash
    Journal of Supercomputing, 2019
  • An eigenvalue-based edge infrastructure for cloud-based CDN
    Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    International Journal of Communication Systems, 2019
  • A Lightweight Authentication Scheme for Cloud-Centric IoT Applications
    Sampa Sahoo, Shreeya Swagatika Sahoo, Prasenjit Maiti, Bibhudatta Sahoo, Ashok Kumar Turuk
    2019 6th International Conference on Signal Processing and Integrated Networks Spin 2019, 2019
  • QoS-aware Service Provisioning in Heterogeneous Fog computing supporting IoT Applications
    Prasenjit Maiti, Hemant Kumar Apat, Mohammed Altowayti, Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    Proceedings International Conference on Vision Towards Emerging Trends in Communication and Networking Vitecon 2019, 2019
  • Secure Big Data Computing in Cloud: An Overview
    Sambit Kumar Mishra, Sampa Sahoo, Bibhudatta Sahoo
    Encyclopedia of Big Data Technologies, 2019
  • Allocation of energy-efficient task in cloud using DVFS
    Sambit Kumar Mishra, Md Akram Khan, Sampa Sahoo, Bibhudatta Sahoo
    International Journal of Computational Science and Engineering, 2019
  • Co-resident Attack in Cloud Computing: An Overview
    Sampa Sahoo, Sambit Kumar Mishra, Bibhudatta Sahoo, Ashok Kumar Turuk
    Encyclopedia of Big Data Technologies, 2019
  • Resource allocation for video transcoding in the multimedia cloud
    Sampa Sahoo, Ipsita Parida, Sambit Kumar Mishra, Bibhdatta Sahoo, Ashok Kumar Turuk
    Advances in Intelligent Systems and Computing, 2019
  • TCA: A Multi Constraint Real-Time Task Scheduling Algorithm for Heterogeneous Cloud Environment
    Sampa Sahoo, Sahil Kumar Sahu, Tanmay Kumar Rath, Bibhudatta Sahoo, Ashok Kumar Turuk
    Proceedings 2018 International Conference on Information Technology Icit 2018, 2018
  • MCSA: A Multi-constraint Scheduling Algorithm for Real-time Task in Virtualized Cloud
    Sampa Sahoo, Ankit Pattanayak, Kshira Sagar Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    Indicon 2018 15th IEEE India Council International Conference, 2018
  • An Energy-Efficient Scheduling Framework for Cloud Using Learning Automata
    Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    2018 9th International Conference on Computing Communication and Networking Technologies Icccnt 2018, 2018
  • Poster: A learning automata-based DDoS attack defense mechanism in software defined networks
    Kshira Sagar Sahoo, Mayank Tiwary, Sampa Sahoo, Rohit Nambiar, Bibhudatta Sahoo, Ratnakar Dash
    Proceedings of the Annual International Conference on Mobile Computing and Networking MOBICOM, 2018
  • Video delivery services in media cloud with abandonment: An analytical approach
    Sampa Sahoo, Maneesha Nidhi, Kshira Sagar Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    11th IEEE International Conference on Advanced Networks and Telecommunications Systems Ants 2017, 2018
  • Video Transcoding Services in Cloud Computing Environment
    Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    Studies in Big Data, 2018
  • Energy efficient routing in software defined networking by efficient traffic rule monitoring techniques
    Journal of Advanced Research in Dynamical and Control Systems, 2018
  • Improving Energy Usage in Cloud Computing Using DVFS
    Sambit Kumar Mishra, Priti Paramita Parida, Sampa Sahoo, Bibhudatta Sahoo, Sanjay Kumar Jena
    Advances in Intelligent Systems and Computing, 2018
  • On the placement of controllers for designing a wide area software defined networks
    Kshira Sagar Sahoo, Sampa Sahoo, Anamay Sarkar, Bibhudatta Sahoo, Ratnakar Dash
    IEEE Region 10 Annual International Conference Proceedings TENCON, 2017
  • Evaluating performance of the Non-linear data structure for job queuing in the cloud environment
    Sampa Sahoo, Sambit Kumar Mishra, Devang Swami, Md Akram Khan, Bibhudatta Sahoo
    2017 2nd International Conference for Convergence in Technology I2ct 2017, 2017
  • RT-PUSH: A VM fault detector for deadline-based tasks in cloud
    Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk
    ACM International Conference Proceeding Series, 2017
  • Deadline-constraint services in cloud with heterogeneous servers
    Sampa Sahoo, Sambit Kumar Mishra, Bibhudatta Sahoo, Deepak Puthal, Mohammad S. Obaidat
    IEEE Cits 2017 2017 International Conference on Computer Information and Telecommunication Systems, 2017
  • Storing and analyzing streaming data: A big data challenge
    Big Data Analytics Tools and Technology for Effective Planning, 2017
  • Real time task execution in cloud using mapreduce framework
    Sampa Sahoo, Bibhudatta Sahoo, Ashok Kumar Turuk, Sambit Kumar Mishra
    Resource Management and Efficiency in Cloud Computing Environments, 2016
  • Network virtualization: Network resource management in cloud
    Kshira Sagar Sahoo, Bibhudatta Sahoo, Ratnakar Dash, Mayank Tiwary, Sampa Sahoo
    Resource Management and Efficiency in Cloud Computing Environments, 2016
  • Execution of real time task on cloud environment
    Sampa Sahoo, Syed Nawaz, Sambit Kumar Mishra, Bibhudatta Sahoo
    12th IEEE International Conference Electronics Energy Environment Communication Computer Control E3 C3 Indicon 2015, 2016
  • Improving energy consumption in cloud
    Sambit Kumar Mishra, Reenu Deswal, Sampa Sahoo, Bibhudatta Sahoo
    12th IEEE International Conference Electronics Energy Environment Communication Computer Control E3 C3 Indicon 2015, 2016
  • Navigation of autonomous mobile robot using different activation functions of wavelet neural network
    Pratap kumar Panigrahi, Sampa Sahoo
    2014 International Conference for Convergence of Technology I2ct 2014, 2014
  • Path planning and control of autonomous robotic agent using Mamdani based fuzzy logic controller and ARDUINO UNO micro controller
    Pratap Kumar Panigrahi, Sampa Sahoo
    Advances in Intelligent Systems and Computing, 2014

RECENT SCHOLAR PUBLICATIONS

  • Energy and makespan optimised task mapping in fog enabled IoT application: a hybrid approach
    N Tripathy, S Sahoo, NS Alghamdi, W Viriyasitavat, G Dhiman
    Scientific Reports , 2026
    2026
    Citations: 2
  • An efficient task offloading approach to reduce energy consumption in fog architecture
    N Tripathy, S Sahoo, SC Nayak, CC Lee
    Computers and Electrical Engineering 128, 110648 , 2025
    2025
    Citations: 5
  • Camouflaged object detection using hybrid-deep learning model
    I Padhy, VKR CH, P Kanungo, S Sahoo
    Multimedia Tools and Applications 84 (26), 31771-31791 , 2025
    2025
    Citations: 4
  • Comparative Analysis of Geographical Distance Methods: Haversine, Spherical Law of Cosines, Vincenty, Karney, and Great Elliptic Distance
    T Vats, S Kumar, UK Sinha, S Sahoo
    2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC … , 2025
    2025
    Citations: 1
  • An efficient camouflaged image segmentation with modified UNet and attention techniques
    I Padhy, P Dansena, S Sahoo, R Priyadarshi
    Scientific Reports 15 (1), 21086 , 2025
    2025
    Citations: 2
  • U-Net: A Binary Segmentation Architecture for Building Localization in Structural Health Monitoring using the xBD Dataset
    S Suwarna, S Sahoo, S Srivastava, KR Das, SK Panda
    2025 International Conference on Microwave, Optical, and Communication … , 2025
    2025
    Citations: 1
  • A learning automata based edge resource allocation approach for IoT-enabled smart cities
    S Sahoo, KS Sahoo, B Sahoo, AH Gandomi
    Digital Communications and Networks 10 (5), 1258-1266 , 2024
    2024
    Citations: 11
  • Fake News Detection Using Passive Aggressive Classifier (PAC) & Neural Network: A Hybrid Approach
    OP Mohanta, G Swain, K Ashutosh, A Padhy, S Sahoo
    2024 IEEE International Conference on Smart Power Control and Renewable … , 2024
    2024
  • Cloud computing for a secure smart city beyond 5G
    MK Patra, S Sahoo, B Sahoo, AK Turuk
    Secure and Intelligent IoT-Enabled Smart Cities, 91-116 , 2024
    2024
    Citations: 6
  • Energy Aware Task Scheduling in IoT Based Fog Environment
    N Tripathy, S Sahoo, SC Nayak
    2023 OITS International Conference on Information Technology (OCIT), 886-891 , 2023
    2023
  • Energy Aware Effective Task Offloading Mechanism in Fog Computing
    N Tripathy, S Sahoo
    International Conference on Computing, Communication and Learning, 272-284 , 2023
    2023
    Citations: 3
  • Multiclass classification of camouflage images using combined wld and lpq feature set using a ann classifier
    I Padhy, P Kanungo, S Sahoo
    International Conference on Advances in Signal Processing And Communication … , 2023
    2023
    Citations: 1
  • A YCBCR model based shadow detection and removal approach on camouflaged images
    I Padhy, P Kanungo, S Sahoo
    2022 OITS International Conference on Information Technology (OCIT), 574-579 , 2022
    2022
    Citations: 3
  • Modeling Internet of Things-Based Solution for Evading Congestion and Blockage in Waterways
    M Rao, NK Kamila, S Sahoo, KV Kumar
    Biologically Inspired Techniques in Many Criteria Decision Making … , 2022
    2022
  • Queuing Theory-Based Analysis of Berth Allocation and Management in Paradip Port for Container Ships
    M Rao, NK Kamila, KV Kumar, D Mishra, S Sahoo
    Electronic Systems and Intelligent Computing: Proceedings of ESIC 2021, 433-440 , 2022
    2022
    Citations: 1
  • Design of An Authentication Scheme for Cloud-Based IoT Applications
    S Sahoo, S Swagatika Sahoo, B Sahoo, A Kumar Turuk
    IETE Technical Review 39 (2), 343-356 , 2022
    2022
    Citations: 4
  • Cloud-Edge Centric Service Provisioning in Smart City Using Internet of Things
    MK Patra, S Sahoo, B Sahoo, AK Turuk
    Advances in Parallel & Distributed Processing, and Applications: Proceedings … , 2021
    2021
    Citations: 4
  • An auction based edge resource allocation mechanism for IoT-enabled smart cities
    S Sahoo, KS Sahoo, B Sahoo, AH Gandomi
    2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1280-1286 , 2020
    2020
    Citations: 16
  • Energy-efficient service allocation techniques in cloud: A survey
    SK Mishra, S Sahoo, B Sahoo, SK Jena
    IETE Technical Review 37 (4), 339-352 , 2020
    2020
    Citations: 29
  • Modified Grey Wolf Optimization (GWO) based Accident Deterrence in Internet of Things (IoT) enabled Mining Industry
    D Majhi, M Rao, S Sahoo, SP Dash, DP Mohapatra
    2020 International Conference on Computer Science, Engineering and … , 2020
    2020
    Citations: 7

MOST CITED SCHOLAR PUBLICATIONS

  • Toward secure software-defined networks against distributed denial of service attack: KS Sahoo et al.
    KS Sahoo, SK Panda, S Sahoo, B Sahoo, R Dash
    The Journal of Supercomputing 75 (8), 4829-4874 , 2019
    2019
    Citations: 83
  • On the placement of controllers for designing a wide area software defined networks
    KS Sahoo, S Sahoo, A Sarkar, B Sahoo, R Dash
    TENCON 2017-2017 IEEE Region 10 Conference, 3123-3128 , 2017
    2017
    Citations: 52
  • A learning automata-based scheduling for deadline sensitive task in the cloud
    S Sahoo, B Sahoo, AK Turuk
    IEEE Transactions on Services Computing 14 (6), 1662-1674 , 2019
    2019
    Citations: 49
  • Execution of real time task on cloud environment
    S Sahoo, S Nawaz, SK Mishra, B Sahoo
    2015 Annual IEEE India Conference (INDICON), 1-5 , 2015
    2015
    Citations: 36
  • NAVIGATION OF AUTONOMOUS MOBILE ROBOT USING DIFFERENT ACTIVATION FUNCTIONS OF WAVELET NEURAL NETWORK
    P K PANIGRAHI ,S SAHOO
    International conference on convergence of Technology-2014 , 2014
    2014
    Citations: 34
  • Energy-efficient service allocation techniques in cloud: A survey
    SK Mishra, S Sahoo, B Sahoo, SK Jena
    IETE Technical Review 37 (4), 339-352 , 2020
    2020
    Citations: 29
  • Software defined network: the next generation internet technology
    KS Sahoo, SK Mishra, S Sahoo, B Sahoo
    Modern Education and Computer Science Press , 2017
    2017
    Citations: 29
  • Allocation of energy-efficient task in cloud using DVFS
    SK Mishra, MA Khan, S Sahoo, B Sahoo
    International Journal of Computational Science and Engineering 18 (2), 154-163 , 2019
    2019
    Citations: 25
  • Game theoretic approach for real-time task scheduling in cloud computing environment
    MK Patra, S Sahoo, B Sahoo, AK Turuk
    2019 International Conference on Information Technology (ICIT), 454-459 , 2019
    2019
    Citations: 23
  • Improving energy consumption in cloud
    SK Mishra, R Deswal, S Sahoo, B Sahoo
    2015 Annual IEEE India Conference (INDICON), 1-6 , 2015
    2015
    Citations: 22
  • Improving energy usage in cloud computing using DVFS
    SK Mishra, PP Parida, S Sahoo, B Sahoo, SK Jena
    Progress in Advanced Computing and Intelligent Engineering: Proceedings of … , 2018
    2018
    Citations: 20
  • Metaheuristic techniques for controller placement in Software-Defined networks
    S Mohanty, P Priyadarshini, S Sahoo, B Sahoo, S Sethi
    TENCON 2019-2019 IEEE Region 10 Conference (TENCON), 897-902 , 2019
    2019
    Citations: 17
  • An auction based edge resource allocation mechanism for IoT-enabled smart cities
    S Sahoo, KS Sahoo, B Sahoo, AH Gandomi
    2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1280-1286 , 2020
    2020
    Citations: 16
  • An energy-efficient scheduling framework for cloud using learning automata
    S Sahoo, B Sahoo, AK Turuk
    2018 9th International Conference on Computing, Communication and Networking … , 2018
    2018
    Citations: 16
  • A learning automata-based DDoS attack defense mechanism in software defined networks
    KS Sahoo, M Tiwary, S Sahoo, R Nambiar, B Sahoo, R Dash
    Proceedings of the 24th annual international conference on mobile computing … , 2018
    2018
    Citations: 14
  • A lightweight authentication scheme for cloud-centric IoT applications
    S Sahoo, SS Sahoo, P Maiti, B Sahoo, AK Turuk
    2019 6th International Conference on Signal Processing and Integrated … , 2019
    2019
    Citations: 13
  • A learning automata based edge resource allocation approach for IoT-enabled smart cities
    S Sahoo, KS Sahoo, B Sahoo, AH Gandomi
    Digital Communications and Networks 10 (5), 1258-1266 , 2024
    2024
    Citations: 11
  • Real time task execution in cloud using mapreduce framework
    S Sahoo, B Sahoo, AK Turuk, SK Mishra
    Resource management and efficiency in cloud computing environments, 190-209 , 2017
    2017
    Citations: 10
  • Analyzing controller placement in software defined networks
    KS Sahoo, S Sahoo, SK Mishra, S Mohanty, B Sahoo
    International Journal of Computer Applications 975, 8887 , 2016
    2016
    Citations: 8
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