Dr John Panneerselvam is a Lecturer in Computer Science within the School of Computing and Mathematical Sciences at the University of Leicester. John joined the University of Leicester in February 2020 and prior to this John worked as a Lecturer in Computing at the University of Derby for a period of three years. John received the PhD degree in the discipline of Computing and an MSc in Advanced Computer Networks from the University of Derby.
John is an active early-career researcher and has research collaborations with several research groups across the globe including Jiangsu University, Tongji University and Anhui University of China, Sathyabama Institute of Science and Technology, India, to name a few. John has generated various forms of research outputs in the fields of Cloud Computing, Peer-to-Peer Computing, Internet of Things, Big Data Analytics, Wireless Sensor Networks, Network Security and Opportunistic Networking. John servers as a reviewer for a number of reputed conferences and journals including IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Sustainable Computing, IEEE Transactions on Cloud Computing, IEEE Access, Future Generation Computer Systems, IEEE Real-time Data Processing for Cloud Computing, IEEE/ACM Utility and Cloud Computing, IEEE/ACM Big Data Computing, Applications and Technologies etc.
- British Computer Society
- Fellow of Higher Education Academy, UK
John largely focuses on energy-efficient datacentres with an analytics approach. Datacentres are addressed to be massive energy consumers and environmental polluters. Whilst the energy implications of Cloud datacentres are being addressed from various research perspectives, John focuses on predicting the future trend and behaviours of workloads at the datacentres, thereby reducing the active server resources to conserve energy. This involves studying large-scale commercial datacentre trace logs involving descriptive, predictive and prescriptive analytics using a range of Machine-Learning, Deep-Learning and Artificial Intelligence techniques.
John also works in the areas of Interdisciplinary Analytics, Scheduling and Resource Management in Distributed Datacentres, Internet of Things applications, and Digital Twins.
Current Research Projects
- Principal Investigator: Towards a thermal digital twin, led by Airbus, funded by European Space Agency, September 2021 - March 2023
- Principal Investigator: Developing novel e-commerce analytics dashboard for customer and product Insight, an Industrial MPhil project with Books2Door, funded by ERDF, January 2022 - December 2023
- Principal Investigator: An IoT enabled smart bin and waste management systems for a sustainable society, funded by Royal Society under the International Exchanges Scheme, March 2022 – March 2024
- Co-Investigator: Predicting relapse in the Ponseti treatment of clubfoot, sponsored by Foxtrot Charity, NHS, Summer 2022
Previous Research Projects
- Principal Investigator, UK-JIANGSU 20-20 Initiative Pump Priming Grant, British Council, 2019
- Consortium member, UK-Jiangsu 20-20 World Class University Initiative, British Council, June 2018 – May 2020
- Academic Lead, Overseas Research and Training Program, Funded by Jiangsu University, China, 2019
- Co-Investigator, A Cloud-based Sustainable Business Model for Effective ICT Provisions in Higher Education, Funded by RCUK NEMODE, 2014
- U. Tariq, H. Ali, L. Liu, J. Panneerselvam, J. Hardy, Energy-Efficient Scheduling of Streaming Applications in VFI-NoC-HMPSoC based Edge Devices, Journal of Ambient Intelligence and Humanized Computing, Dec 2020.
- D. Mumin, L. Shi, L. Liu and J. Panneerselvam, Data-Driven Diffusion Recommendation in Online Social Networks for the Internet of People,IEEE Transactions on Systems, Man, and Cybernetics: Systems, in press, 2020. (Impact Factor: 9.309)
- H. Ali, U. Tariq, M. Hussain, L. Lu, J. Panneerselvam and X. Zhai, ARSH-FATI a Novel Metaheuristic for Cluster Head Selection in Wireless Sensor Networks, IEEE Systems Journal, May 2020, doi: 10.1109/JSYST.2020.2986811
- C. Jiang, Y. Fang, P. Zhao and J. Panneerselvam, Intelligent UAV Identity Authentication and Safety Supervision Based on Behavior Modeling and Prediction, IEEE Transactions on Industrial Informatics, vol. 16(10), pp. 6652 - 6662, October 2020, doi: 10.1109/TII.2020.2966758
- Y. Guo, L. Liu, J. Panneerselvam and R. Zhu, Efficient service discovery in mobile social networks for smart cities, Computing (2020), doi: https://doi.org/10.1007/s00607-020-00824-7
- Y. Wu, F. Tao, L. Liu, J. Gu, J. Panneerselvam, R. Zhu, and M. Shahzad, A Bitcoin Transaction Network Analytic Method for Future Blockchain Forensic Investigation, IEEE Transactions on Network Science and Engineering, doi: 10.1109/TNSE.2020.2970113.
- J. Panneerselvam, L. Liu and N. Antonopoulos, An Approach to Optimise Resource Provision with Energy-awareness in Datacentres by Combating Task Heterogeneity, IEEE Transactions on Emerging Topics on Computing, 2018, doi: 10.1109/TETC.2018.2794328 (Impact Factor: 3.626, Q1)
- B. Yuan, J. Panneerselvam, L. Liu, N. Antonopoulos, An Inductive Content-Augmented Network Embedding Model for Edge Artiﬁcial Intelligence, IEEE Transactions on Industrial Informatics, vol 15(7), pp. 4295-4305, July 2019. (Impact Factor: 5.430, Q1)
- Y. Lu, L. Liu, J. Panneerselvam, B. Yuan, J. Gu and N. Antonopoulos, A GRU-Based Prediction Framework for Intelligent Resource Management at Cloud Data Centres in the Age of 5G, IEEE Transactions on Cognitive Communications and Networking, in press, 2019.
- Y. Lu, L. Liu, J. Panneerselvam, X. Zhai, X. Sun, N. Antonopoulos, A Latency-based Analytic Approach to Forecast Cloud Workload Trend for Sustainable Datacentres, IEEE Transactions on Sustainable Computing, in press, 2019. (Impact Factor: 2.45, Q1)
- U. Tariq, H. Ali, L. Liu, J. Panneerselvam and X. Zhai, Energy-efficient Static Scheduler on VFI based NoC-HMPSoCs for Intelligent Edge Devices in Cyber-Physical Systems, ACM Transactions on Intelligent Systems and Technology, in press, 2019. (Impact Factor: 3.19, Q1)
- D. Miao, L. Liu, R. Xu, J. Panneerselvam, Y. Wu, W. Xu, An Efficient Indexing Model for the Fog Layer of Industrial Internet of Things, IEEE Transactions on Industrial Informatics, vol 14(10), pp. 4487-4496, January 2018. doi: 10.1109/TII.2018.2799598 (Impact Factor: 5.430, Q1)
- L. Shi, L. Liu, Y. Wu, L. Jiang, M. Kazim, H. Ali and J. Panneerselvam, Human-centric Cyber Social Computing Model for Hot Event Detection and Propagation, IEEE Transactions on Computational Social Systems, vol. 6(5), pp. 1042 – 1050, October 2019, doi: 10.1109/TCSS.2019.2913783.
- L. Shi, L. Liu, Y. Wu, L. Jiang, J. Panneerselvam and R. Crole, A Social Sensing Model for Event Detection and User Influence Discovering in Social Media Data Streams, IEEE Transactions on Computational Social Systems, vol. 7(1), pp. 141-150, February 2020, doi: 10.1109/TCSS.2019.2938954
- J. Panneerselvam, L. Liu, Y. Lu and N. Antonopoulos, An Investigation into the Impacts of Task-level Behavioural Heterogeneity upon Energy Efficiency in Cloud Datacentres, Future Generation Computer Systems, vol. 83, pp. 239-249, June 2018, doi: https://doi.org/10.1016/j.future.2017.12.064 (Impact Factor: 4.639, Q1)
- J. Panneerselvam, L. Liu and N. Antonopoulos, InOt-RePCoN: Forecasting User Behavioural trend in Large-Scale Cloud Environments, Future Generation Computer Systems, vol 80, pp. 322-341, March 2018. doi: https://doi.org/10.1016/j.future.2017.05.022 (Impact Factor: 4.639, Q1)
- X. Bai, Z. Zhang, L Liu, Z. Zhai, J. Panneerselvam, L. Ge, Enhancing Localization of Mobile Robots in Distributed Sensor Environments for Reliable Proximity Service Applications, IEEE Access, PP(99):1-1, February 2019. (Impact Factor: 3.557, Q1)
- X. Shen, Q. Chang, L. Liu, J. Panneerselvam, and Zheng-Jun Zha, CCLBR: Congestion Control-Based Load Balanced Routing in Unstructured P2P Systems, IEEE Systems Journal, 12(1), 2018, pp 802 - 813. DOI: 10.1109/JSYST.2016.2558515. (Impact Factor: 4.337, Q1)
- J. Chen, T. Li, J. Panneerselvam, TMEC: A Trust Management Based on Evidence Combination on Attack-Resistant and Collaborative Internet of Vehicles, in press, IEEE Access Journal, in press, 2018. DOI: 10.1109/ACCESS.2018.2876153 2725898 (Impact Factor: 3.557, Q1)
- M. Wang, L. Shi, L. Liu, M. Ahmed, J. Panneerselvam, Hybrid Recommendation based QoS Prediction for Sensor Services, International Journal of Distributed Sensor Networks, 14 (5), 2018, pp 1-10. DOI: 10.1177/1550147718774012 (Impact Factor: 1.787)
- J. Panneerselvam, L. Liu, N. Antonopoulos and J. Hardy, Analysis, Modelling and Characterisation of Zombie Servers in Large-Scale Cloud Datacentres, IEEE Access Journal, vol 5, pp. 15040-15054, July 2017. doi: 10.1109/ACCESS.2017.2725898 (Impact Factor: 3.557, Q1)
- X. Bai, L. Liu, M. Cao, J. Panneerselvam, Q. Sun, H. Wang, Collaborative Actuation of Wireless Sensor and Actuator Networks for the Agriculture Industry, IEEE Access, Vol 5, 2017, pp 13286 - 13296. DOI: 10.1109/ACCESS.2017.2725342 (Impact Factor: 3.557, Q1)
- J. Panneerselvam, J. Hardy, L. Liu, N. Antonopoulos, B. Yuan, Mobilouds: An Energy Efficient MCC Collaborative Framework with Extended Mobile Participation for Next Generation Networks, IEEE Access Journal, vol 4, pp. 9129 – 9144, September 2016. doi: 10.1109/ACCESS.2016.2602321 (Impact Factor: 3.557, Q1)
- V. Rajinikanth, N. Dey, R. Kumar, J. Panneerselvam and N. S. M. Raja, Fetal Head Periphery Extraction from Ultrasound Image using Jaya Algorithm and Chan-Vese Segmentation, Procedia Computer Science, pp. 66-73, vol. 152, 2019.
- Y. Lu, J. Panneerselvam, L. Liu, Y. Wu, RVLBPNN: A Workload Forecasting Model for Smart Cloud Computing, Journal of Scientific Programming, September 2016. doi: http://dx.doi.org/10.1155/2016/5635673 (Impact Factor: 1.344)
- J. Li, J. Zhao, Y. Li, L. Cui, B. Li, L. Liu, J. Panneerselvam, iMIG: Towards an Adaptive Live Migration Method for KVM Virtual Machines, The Computer Journal, Oxford University Press, Vol 58(6), 2015, pp 1227-1242. DOI: 10.1093/comjnl/bxu065 (Impact Factor: 0.792)
- X. Shen, L. Liu, P. Gu, Z. Jiang, J. Chen, J. Panneerselvam, Achieving Dynamic Load Balancing through Mobile Agents in Small World P2P Networks, Computer Networks, Elsevier, Vol 75, pp. 134-148, 2014. DOI: 10.1016/j.comnet.2014.05.003 (Impact Factor: 2.522)
- J. Panneerselvam, A. Atojoko, K. Smith, L. Liu, N. Antonopoulos, A Critical Review of the Routing Protocols in Opportunistic Networks, Industrial Networks and Intelligent Systems, Vol 14(1), December 2014. DOI: 10.4108/inis.1.1.e6
- J. Panneerselvam, L. Liu and Yao Lu, Datacentre Event Analysis for Knowledge Discovery in Large-Scale Cloud Environments, Cloud Computing, Computer Communications and Networks, 2017. doi: 10.1007/978-3-319-54645-2_14
- J. Panneerselvam, L. Liu, R. Hill, An Introduction to Big Data, Application of Big Data for National Security, Butterworth-Heinemann, pp 113-139. ISBN: 9780128019672, February 2015.
- J. Panneerselvam, L. Liu, R. Hill, Requirements and Challenges for Big Data Architectures, Application of Big Data for National Security, Butterworth-Heinemann, pp 113-139. ISBN: 9780128019672, February 2015.
- T. Holding, J. Panneerselvam, L. Liu, Migrating to Public Cloud: From a Security Perspective, Guide to Security Assurance for Cloud Computing, Springer, pp. 31-50, March 2016.
- V. Rajinikanth, H. Lin, J. Panneerselvam and N.S.M. Raja, Examination of Retinal Anatomical Structures – A Study with Spider Monkey Optimization Algorithm, Applied Nature Inspired Computing: Algorithms and Case Studies, pp. 177-197, Springer, 2020.
- P. Mrozek, J. Panneerselvam and O. Bagdasar, Efficient Resampling for Fraud Detection During Anonymised Credit Card Transactions with Unbalanced Datasets, 6th International Symposium on Real-time Data Processing for Cloud Computing (RTDPCC 2020), Leicester, December 2020, in press.
- A. Ayorinde, J. Panneerselvam, L. Liu and D. Miao, Topic clustering using induced squared correlation thresholding with dimension reduction, 10th IEEE International Conference on Sustainable Computing and Communications (SustainCom-2020), Exeter, December 2020, in press.
- U. Tariq, H. Ali, J. Panneerselvam, J. Hardy, L. Liu, Energy-aware Multimedia Applications Scheduling on VFI-NoC-MPSoC using as Edge-devices in IoT, 10th IEEE International Conference in Big Data and Cloud Computing, Exeter, December 2020, in press.
- J. Chen, L. Shi, L. Liu, A-O. Ayorinde, R. Zhu, J. Panneerselvam, User Interest Communities Influence Maximization in a Competitive Environment, 16th International Conference on Mobility, Sensing and Networking (MSN 2020), Tokyo, December 2020, in press.
- B. Yuan, A. Anjum, J. Panneerselvam and L. Liu, Exploring Network Embedding for Efficient Message Routing in Opportunistic Mobile Social Networks, International Conference on Data Mining Workshops (ICDMW), November 2019, doi: 10.1109/ICDMW.2019.00077, IEEE Press.
- O. Alofe, K. Fatema, J. Panneerselvam and F. Kurugollu, Saving Victims in Moving Vehicles: an IoT based prediction model aided solution, 2nd IEEE Middle East and North Africa COMMunications Conference (MENACOM), November 2019, IEEE Press.
- M. Shahzad, J. Panneerselvam, L. Liu and X. Zhai, Data Aggregation Challenges in Fog Computing, Proceedings of the 5th IEEE Smart World Congress, August 2019, in press, IEEE Press.
- H. Ali, U. Tariq, L. Liu, J. Panneerselvam, X. Zhai, Energy Optimization of Streaming Applications in IoT on NoC based Heterogeneous MPSoCs using Re-timing and DVFS, The 16th IEEE International Conference on Advanced and Trusted Computing, Leicester, 2019, in press. IEEE Press.
- H. Wang, J. Panneerselvam, L. Liu, Y. Lu, Xiaojun Zhai, Haider Ali, Cloud Workload Analytics for Real-Time Prediction of User Request Patterns, Proceeding of 4th IEEE International Conference on Data Science and Systems, Exeter UK, 28-30 June 2018, in press. IEEE Press. (Best Paper Award)
- J. Panneerselvam, L. Liu and N. Antonopoulos, Characterisation of Hidden Periodicity in Large Scale Datacentre Environments, IEEE Int. Conf. Green Computing and Communications, Exeter, June 2017. IEEE Press. pp 496-503, DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.79
- R. Xu, D. Miao, L. Liu and J. Panneerselvam, An Optimal Travel Route Plan for Yangzhou Based on the Improved Floyd Algorithm, Proceedings of 10th IEEE International Conference on Cyber, Physical and Social Computing, 2017. pp 168 – 177. IEEE Press DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.30
- Y. Fan, J. Panneerselvam and L. Liu, The Cost Function and Improvement Strategies of Service Quality of University Library under New Information Environments, Proceedings of 10th IEEE International Conference on Cyber, Physical and Social Computing, 2017. pp 208-215. IEEE Press DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.36.
- X. Bai, M. Cao, L. Liu, J. Panneerselvam, Qiao Sun, Efficient Estimation and Control of WSANs for the Greenhouse Environment, Proceedings of 9th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2016), Shanghai, China, Decemer 2016, pp. 369 – 374. IEEE Press. DOI: 10.1145/2996890.3007853
- J. Panneerselvam, L. Liu, N. Antonopoulos, M. Trovati, Latency-Aware Empirical Analysis of the Workloads for Reducing Excess Energy Consumptions at Cloud Datacentres, 2016 IEEE Symposium on Service-Oriented System Engineering (SOSE), Oxford, March 2016. pp. 119 - 125. IEEE Press. DOI: 10.1109/SOSE.2016.60
- X. Sun, Y. Wu, L Liu, J. Panneerselvam, Efficient Event Detection in Social Media Data Streams, Proceedings of 13th IEEE International Conference on Dependable, Autonomic and Secure Computing (IEEE DASC 2015). pp 1711 – 1717. IEEE Press. DOI: 10.1109/CIT/IUCC/DASC/PICOM.2015.258
- K. Vilius, L. Liu, J. Panneerselvam, T. Stimpson, A Critical Analysis of the Efficiencies of Emerging Wireless Security Standards Against Network Attacks, Proceeding of International Conference on Intelligent Networking and Collaborative Systems, Taipei, 2-4 Sept. 2015. DOI: 10.1109/INCoS.2015.56
- F. Tao, J. Panneerselvam, T. Holding, L. Liu, A Cloud-based Sustainable Business Model for Effective ICT Provision in Higher Education, 7TH IEEE Int. Sym. Service Oriented System Engineering, San Francisco, pp. 222-228, March 2015. IEEE Press. DOI: 10.1109/SOSE.2015.9
- J. Panneerselvam, L. Liu, N. Antonopoulos, Y. Bo, Workload Analysis for the Scope of User Demand Prediction Model Evaluation in Cloud Environments, Proc of IEEE/ACM Int. Conf. Utility and Cloud Computing, pp 883-889, December 2014. IEEE Press. DOI: 10.1109/UCC.2014.144
- F. Hou, X. Mao, W. Wu, L. Liu and J. Panneerselvam, A Cloud-Oriented Services Self-Management Approach Based on Multi-Agent System Technique, Proceeding of 7th IEEE International Conference on Utility and Cloud Computing (UCC 2014), London, December 2014, pp. 261-268. IEEE Press. DOI: 10.1109/UCC.2014.35
- R. Xu, L. Liu, J. Panneerselvam, User Experience Evaluation of Chinese Travel App Software, Proceedings of The 14th IEEE International Conference on Computer and Information Technology (CIT 2014), Xi’an, China, September 2014, pp. 610-615. IEEE Press. DOI: 10.1109/CIT.2014.109
- H. Al Jabry, L. Liu, Y. Zhu, J. Panneerselvam, A Critical Evaluation of the Performance of Virtualization Technologies, Proceedings of CHINACOM, Maoming, China, August 2014, pp. 606-611. IEEE Press. DOI: 10.1109/CHINACOM.2014.7054367
- J. Panneerselvam, L. Liu, R. Hill, Y. Zhan, W. Liu, An Investigation of the Effect of Cloud Computing on Network Management, Proceedings of 9th IEEE International Conference on Embedded Software and Systems (ICESS), Liverpool, UK, June 2012. pp. 1794-1799. IEEE Press. DOI: 10.1109/HPCC.2012.270
- J. Panneerselvam, S. Sotiriadis, N. Bessis and N. Antonopoulos, Securing authentication and trusted migration of weblets in the cloud with reduced traffic, IEEE 3rd International Conference on Emerging Intellifgent Data and Web Technologies, September 2012, pp. 316- 319, IEEE Press, DOI: 10.1109/EIDWT.2012.20
Current PhD Supervision
- Anthony Miller - Lada Diabetes Classification by Combining Genetic and Conventional Risk Factors
- Ayodeji Ayorinde - Detecting Bursty Events Using Supervised Learning Approach
- Zekun Sun - Intelligent Resource Management Model for Green Cloud Computing
- Jiayan Gu - A Novel Multi-level Service Index Model for Large-scale Distributed Service Repositories in Edge Computing
Please feel free to get in touch, if you would like to pursue a PhD or MPhil degree in the areas of Cloud Computing, Distributed Computing, Machine-Learning and Artificial Intelligence applications.
- Computes Society and Professionalism - Level 6
Foundations of Cybersecurity - Level 6 and Level 7
Creating Software Applications - Level 0
Please feel to submit your article. Submission currently open, with a deadline of 31st of August 2022.
- Invited Talk: Artificial Intelligence for Space Workshop, Space Park Leicester, June 2022
- Panel member: AI and Sustainability, 41st SGAI International Conference on Artificial Intelligence, Cambridge, UK, December 2021
- Best Paper Award 10th IEEE International Conference on Big Data and cloud Computing (IEEE BDCloud 2020)
- Keynote: AICTE sponsored STTP-III Programme at AMET University, India, December 2020
- Invited Talk: Indian Institute of Information Technology Design and Manufacturing, India, January 2020
- Invited Talk: Anhui University Anhui Province China December, November 2020
- Keynote: Races 2019, Sathyabama Institute of Science and Technology, India, November 2019
- Invited Talk: Babes-Bolyai University Cluj-Napoca Romania, May 2019
- Invited Talk: Jiangsu University Jiangsu Province China December 2018, 2019
- Invited Talk: Anhui University Anhui Province China December 2018, 2019
- Best Paper Award 4th IEEE International Conference on Data Science and Systems (IEEE DSS 2018)
- Invited Talk: Nanjing Agricultural University Jiangsu Province China December 2018
PhD in Computing University of Derby UK 2018
PGCert in Teaching in Higher Education University of Derby UK 2018
MSc Advanced Computer Networks University of Derby 2013
BE Electronics and Communication Engineering Thangavelu Engineering College India 2011