Chinmaya Kumar Dehury
Lecturer of Distributed Systems, Mobile & Cloud Lab
University of Tartu, Estonia
chinmaya.dehury(at)ut.ee,(at)ymail.com
http://blogchinmaya.blogspot.com
Address:
Institute of Computer Science
University of Tartu
Narva mnt 18 - 3040
Tartu 51009, Estonia
Telephone: +372 737 6419
IEEE Member: 96481829
ACM India Member: 8242857
🚀 PhD Position Alert 🌐
chinmaya(dot)dehury(at)ut(dot)ee

About Me

Publication

Courses

Supervised Dissertations

Research Interest

Project

Team

Professional Activities

Others



Edge computing resources

Call for Papers

International Journal of Network Management (IJNM), Wiley, Special Issue on Learning-driven Ubiquitous Mobile Edge Computing: Network Management Challenges for Future Generation IoT

[[ DEADLINE CLOSED ]] Electronics, MDPI, Special Issue on Artificial Intelligence Technologies and Applications CFP PDF

[[ DEADLINE CLOSED ]] Computer Communications, Elsevier, Special Issue on Ambient Intelligence in Communication, Computation and Networking for Future Internet of Things

Call for Book Chapter

[[ DEADLINE CLOSED ]] Predictive Analytics in Cloud, Fog, and Edge Computing: Perspectives and Practices of Blockchain, IoT, and 5G
[FULL VERSION]

About Me


I am an Assistant Professor of Distributed Systems Group, a member of Mobile & Cloud Lab, Institute of Computer Science, University of Tartu, since Aug 2021. Before this, I joined Mobile & Cloud Lab as a Researcher.

In Fall 2013, I joined Future Ubiquitous Networking (FUN) Lab at Chang Gung University as a Master student under Prof. Prasan Kumar Sahoo. The lab is now changed to Artificial intelligence and Big data Computing (ABC) Lab.
In Fall 2014, I upgrade the Master program to PhD program at the Department of Computer Science and Information Engineering at CGU.

Get my CV from here.

Education


Sept 2013 ~ Jan 2019 : Ph.D. in Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan
Thesis title: Scheduling and Resource Management Algorithms for Cloud Computing.
Supervisor: Prof. Prasan Kumar Sahoo
Aug 2010 ~ July 2013 : Master in Computer Application, Biju Patnaik University of Technology (BPUT), Odisha, India
Thesis title: Implementation of Radix sort in binary number system.
Supervisor: Dr. Rudramohan Tripathy
Aug 2006 ~ June 2009 : Bachelor in computer Application, Sambalpur University, Odisha , India

Honours & Awards


Publication

Courses

1. DevOps: Automating Software Delivery and Operations (LTAT.06.015)

2022/23 spring , 2021/22 spring , 2020/21 spring

2. Scheduling in Distributed Systems: Theory and Practices (LTAT.06.024)

2022/23 spring

3. Cloud Computing (LTAT.06.008)

2022/23 spring , 2021/22 spring , 2020/21 spring , 2019/20 spring

4. Mobile and Cloud Computing Seminar (MTAT.03.280)

2022/23 spring , 2022/23 fall , 2021/22 spring , 2021/22 fall , 2020/21 spring , 2020/21 fall , 2019/20 spring , 2019/20 fall

Supervised Dissertations

Master Thesis
  1. Jeyhun Abbasov, Master’s Degree (2023), (sup) Chinmaya Kumar Dehury, “Resource Optimization with DRL-driven Real Time Service Placement Strategy in Edge-Cloud Continuum”, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)(Code)
  2. Volodymyr Chernetskyi, Master’s Degree (2023), (sup) Chinmaya Kumar Dehury, “Container-Based Microservice Placement Optimization in Cloud”, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)
  3. Iwada Eja Bassey, Master’s Degree (2023), (sup) Chinmaya Kumar Dehury; Mubashar Iqbal, “Blockchain in Edge - Cloud Computing Continuum”, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)(Code)
  4. Artjom Valdas, Master’s Degree (2023), (sup) Chinmaya Kumar Dehury; Pelle Jakovits, “ML-TOSCA: ML Pipeline Modelling and Orchestration Using TOSCA”, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)(Code)
  5. Mehdi Hatamian, Master’s Degree (2022), (sup) Chinmaya Kumar Dehury, “Predicting Location-Based Green Energy Availability in Smart Buildings”, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)(Code)
  6. Manish Gupta, Master’s Degree (2022), (sup) Chinmaya Kumar Dehury; Pelle Jakovits, Google Dataflow Orchestration Using TOSCA in the Hybrid Cloud, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)
  7. Tek Raj Chhetri, Master’s Degree (2020), (sup) Chinmaya Kumar Dehury; Artjom Lind; Satish Narayana Srirama, “Towards AI for Cloud Services Reliability Using Combined Metrics”, University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)
Bachelor Thesis
  1. Richard Aljaste, Bachelor Degree (2023), (sup) Chinmaya Kumar Dehury, "Vegetable Visual Quality Evaluation System Based on Artificial Intelligence", University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details) (PDF)
  2. Mathias Are, Bachelor Degree (2022), (sup) Chinmaya Kumar Dehury, "Monitoring of the Microservice Architecture: Ridango Case Study", University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details) (PDF)
  3. Edgar Selihov, Bachelor Degree (2022), (sup) Chinmaya Kumar Dehury, "CloudTraceBucket: Cloud Trace Visualization and Management Platform", University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details) (PDF)
  4. Markus Aksli, Bachelor Degree (2022), (sup) Chinmaya Kumar Dehury, Ulrich Nobisrath, Martin Jeret, "Barriers And Solutions In CI/CD Implementation for Unity Game Development", University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details) (PDF)
  5. Martin Posselt Munck, Bachelor Degree (2021), (sup) Chinmaya Kumar Dehury, "Minimizing the Energy Consumption for Heating: Airforced Systems OÜ Case Study", University of Tartu, Faculty of Science and Technology, Institute of Computer Science, Closed Defense, (Details) (PDF-abstract)
  6. Enrih Sinilaid, Bachelor Degree (2021), (sup) Chinmaya Kumar Dehury, "Monitoring and Controlling Smart Home Appliances Using IoT Devices", University of Tartu, Faculty of Science and Technology, Institute of Computer Science, (Details)(pdf)

Research Interest

Edge - Cloud Computing: My research mainly focused on Virtual Network Embedding (VNE) problem, where I have studied the optimization problem of resource utilization research issue. I focus on the application of different mathematical tools such as graph theory, Hidden Markov Model (HMM) to improve the embedding solution. Besides I focus on resource allocation, network-aware resource scheduling, resource-intensive job scheduling, virtual resource migration cost analysis, server load balancing, power management, fault tolerance analysis.
Edge Intelligence: Integration of fog and cloud computing. Computation offloading to Cloud, job migration between cloud and fog computing. Edge Intelligence, Cluster Edge Intelligence (CEI), Edge intelligence with Blockchain (#Blockchain-lite, #Blockchain@Edge)
Internet of Things: In conjunction with cloud computing, I am focusing on the combination of IoT world and the cloud environment. latency-aware job scheduling, bandwidth-aware job scheduling, IoT service management in cloud are some of the research issues I have studied.
Application of AI in Edge-Cloud computing: AI enabled Cloud resource management, resource demand prediction in cloud, , Pre-VNE based on workload prediction. pro-active AI enabled resource failure prediction in Fog and Cloud.
Smart Environment = Smart home + Smart building + smart city


Projects

--- Open complete list of projects ---

Intelligence discoverability and observability in edge infrastructure

It is predicted by Gartner that 50% of the enterprise-generated data will be created and processed in the edge infrastructure comprised of ever-increasing billions of edge devices. Instead of implementing the intelligence in the cloud environment giving the full responsibility to manage a large number of edge devices, a minimal and required intelligence is imposed on the edge devices, enabling the edge intelligence that works in a master-worker approach. The major problem with this approach is that an edge device relies mostly on the data collected by the onboard sensors and the built-in or cloud-instructed intelligence, resulting in little scope for cooperation and collaboration among peers and hence no device-to-device knowledge transfer. read more....

Team

------ coming soon ------

Professional Activities

Guest Editor

- Journal of King Saud University - Computer and Information Sciences, SI - Learning-driven Data Fabric Trends and Challenges for Cloud-to-Thing Continuum (submit your article) (more info)
- Wiley International Journal of Network Management (IJNM), SI on Intelligent Ubiquitous Mobile Edge Network Management more info


- [CLOSED] Electronics, MDPI, Special Issue on Artificial Intelligence Technologies and Applications   (pdf)
- [CLOSED] Wiley International Journal of Network Management (IJNM) - SI: Learning-driven Ubiquitous Mobile Edge Computing: Network Management Challenges for Future Generation IoT ( CFP )
- [CLOSED] Computer Communications - SI title: Ambient Intelligence in Communication, Computation and Networking for Future Internet of Things

Journal/Conference Reviewer





Session Chair

- FMEC 2023, Estonia
- 2019: The 21st International Conference on Information Integration and Web-based Applications & Services (iiWAS2019), Germany

Track Chair

- FMEC 2023 (easychair)

PC Member

- AICCSA 2021 2022 2023 (easychair)
- BDA 2021 2022 Microsoft CMT
- PCDS 2024
- ScalCom 2022 2023

Committee Member

- Data Science Week 2023 (World Conference on Data Science & Statistics)

Technical Committee (TPC) Member

- The Third Intelligent Cybersecurity Conference (ICSC2023)
- IEEE R10 HTC (Humanitarian Technology Conference) 2023 [EDAS]
- International Conference on Electronic Information Technology and Computer Science, China

Other Academic Activities

- PhD Attestation Committee member, Chair of Distributed System, Institute of Computer Science, University of Tartu, Since 2024
- Doctoral Progress Committee (DPC) member at L. D. College of Engineering, Gujarat Technological University (GTU), Since 2023
- Member of Admission committee of the second level of higher education (MS), ICS, UT, 2023/24

Invited Talks/Workshops/Training programs

- Resource Person, Hands-on workshop on “Standards Compliant Dynamic Deployment of Fog Computing Applications”, SERB CRG Project, School of Computer and Information Sciences, University of Hyderabad, India, 6th Jan 2024
- Invited Lecture, “Harmonizing Diversity across Edge-Cloud Computing Continuum”, School of Computer and Information Sciences, University of Hyderabad, 21st July 2023 11:00 AM-1:00 PM, Online and Offline, Host: IEEE Hyderabad Section
- Invited Lecture, International Workshop on Edge Computing, “Harmonizing Diversity across Edge-Cloud Computing Continuum”, College of Smart Computing, COER University, 25 July 2023, 2 hours.
- Invited Lecture, International Workshop on Edge Computing, “Mastering Git: Unlocking the Power of Version Control for Seamless Collaboration”, College of Smart Computing, COER University, 26 July 2023, 2 hours.
- Keynote Speaker, Guest of Honor, TEQIP Sponsored Training Program on “Fundamentals of Openstack and Containers in Cloud Technology”, Poojya Doddappa Appa (PDA) College of Engineering, Kalaburagi, Karnataka, 23 March 2021
- Resource person, TEQIP Sponsored Training Program on “Fundamentals of Openstack and Containers in Cloud Technology”, Poojya Doddappa Appa (PDA) College of Engineering, Kalaburagi, Karnataka, 23-25 March 2021

Members

- Memeber of Research Data Alliance (RDA)
- IEEE Membership - Since Jan 2020
- IEEE Young Professionals - Since Jan 2021
- IEEE Computer Society Technical Community on Cloud Computing - Since Jan 2021
- IEEE Internet of Things Community - since Jan 2023
- IEEE Computer Society Technical Community on Security and Privacy - Since Jan 2021
- ACM India Member - Since Nov 2020

Professional Badges


- First teaching excellence training for academic staff, Conducted by European Network on Teaching Excellence (E-NOTE), 2022 (PDF)

Webinars

- Webinar on RADON Data Pipeline: Automating data movement in cloud (organised by me)
    (advt link) (Github repo) (Recorded video) (Extended demo video)

Important Links (complete list)