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DSc Thesis (in progress)
DSc Thesis (in progress)
Dynamic Distributed Local Service Provisioning for Future Digital Healthcare
Dynamic Distributed Local Service Provisioning for Future Digital Healthcare
Emerging services based on IoT, AI/ML/DL, and 5G will significantly transform healthcare. Medical IoT systems generate massive data, traditionally processed in centralized cloud data centers, causing high network load, latency, and security concerns. These issues are critical for applications such as remote monitoring, remote surgery, and other mission‑critical medical services that require ultra‑low latency and high reliability. Processing data closer to patients can reduce delay and improve resilience. At the same time, medical data must be securely analyzed to ensure accurate diagnosis while protecting patient privacy. Therefore, healthcare systems need resource‑ and energy‑efficient, scalable, and dynamic end‑to‑end service provisioning models that support secure data processing and high Quality of Service (QoS).
Publications
Publications
E. Harjula et al., "Decentralized IoT Edge Nanoservice Architecture for Future Gadget-Free Computing," in IEEE Access, vol. 7, pp. 119856-119872, 2019, doi: 10.1109/ACCESS.2019.2936714.
J. Islam, T. Kumar, I. Kovacevic and E. Harjula, "Resource-Aware Dynamic Service Deployment for Local IoT Edge Computing: Healthcare Use Case," in IEEE Access, vol. 9, pp. 115868-115884, 2021, doi: 10.1109/ACCESS.2021.3102867.
J. Islam, E. Harjula, T. Kumar, P. Karhula and M. Ylianttila, "Docker Enabled Virtualized Nanoservices for Local IoT Edge Networks," 2019 IEEE Conference on Standards for Communications and Networking (CSCN), Granada, Spain, 2019, pp. 1-7, doi: 10.1109/CSCN.2019.8931321.
Isosalo, A., Islam, J., Mustonen, H., Räinä, E., Inkinen, S. I., Brix, M., Kumar, T., Reponen, J., Nieminen, M. T., & Harjula, E. (2023). Local edge computing for radiological image reconstruction and computer-assisted detection: A feasibility study. Finnish Journal of EHealth and EWelfare, 15(1), 52–66. https://doi.org/10.23996/fjhw.122647.
H. F. Shahid, J. Islam, I. Ahmad and E. Harjula, "Optimizing Resource-Aware Service Orchestration in Edge-Cloud Continuum," 2025 IEEE Intelligent Mobile Computing (MobileCloud), Tucson, AZ, USA, 2025, pp. 44-50, doi: 10.1109/MobileCloud66020.2025.00011.
J. Islam et al., "Distributed Service Orchestration in Edge-Cloud Continuum for Digital Healthcare," in IEEE Transactions on Parallel and Distributed Systems (submitted).
A. Taher et al., "An Edge–Cloud Service Orchestration Platform for Cone-Beam CT Image Denoising," in Communications in Computer and Information Science (accepted).
MSc Thesis
MSc Thesis
Container-based microservice architecture for local IoT services
Container-based microservice architecture for local IoT services
Edge services are needed to save networking and computational resources on higher tiers, enable operation during network problems, and to help limiting private data propagation to higher tiers if the function needing it can be handled locally. MEC at access network level provides most of these features but cannot help when access network is down. Local services, in addition, help alleviating the MEC load and limit the data propagation even more, on local level. This thesis focuses on the local IoT service provisioning. Local service provisioning is subject to several requirements, related to resource/energy-efficiency, performance and reliability.
This thesis introduces a novel way to design and implement a Docker container-based micro-service system for gadget-free future IoT (Internet of Things) network. It introduces a use case scenario and proposes few possible required micro-services as of solution to the scenario. Some of these services deployed on different virtual platforms along with software components that can process sensor data providing storage capacity to make decisions based on their algorithm and business logic while few other services deployed with gateway components to connect rest of the devices to the system of solution. It also includes a state-of-the-art study for design, implementation, and evaluation as a Proof-of-Concept (PoC) based on container-based microservices with Docker. The used IoT devices are Raspberry Pi embedded computers along with an Ubuntu machine with a rich set of features and interfaces, capable of running virtualized services.
This thesis evaluates the solution based on practical implementation. In addition, the thesis also discusses the benefits and drawbacks of the system with respect to the empirical solution. The output of the thesis shows that the virtualized microservices could be efficiently utilized at the local and resource constrained IoT using Dockers. This validates that the approach taken in this thesis is feasible for providing such services and functionalities to the micro and nanoservice architecture. Finally, this thesis proposes numerous improvements for future iterations.
Keywords: Virtualization, Containerization, Docker, IoT, Orchestration, Microservices.
Publications
Publications
J. Islam, E. Harjula, T. Kumar, P. Karhula and M. Ylianttila, "Docker Enabled Virtualized Nanoservices for Local IoT Edge Networks," 2019 IEEE Conference on Standards for Communications and Networking (CSCN), Granada, Spain, 2019, pp. 1-7, doi: 10.1109/CSCN.2019.8931321.
Islam, J., 2019. Container-based microservice architecture for local IoT services (Master's thesis, J. Islam), Available at: https://oulurepo.oulu.fi/handle/10024/14739 (Accessed: 2 June 2026).
BSc Thesis
BSc Thesis
Fuzzy based energy efficient multiple cluster head selection routing protocol for wireless sensor networks
Fuzzy based energy efficient multiple cluster head selection routing protocol for wireless sensor networks
The Wireless Sensor Network (WSN) is made up with small batteries powered sensor devices with limited energy resources within it. These sensor nodes are used to monitor physical or environmental conditions and to pass their data through the wireless network to the main location. One of the crucial issues in wireless sensor network is to create a more energy efficient system. Clustering is one kind of mechanism in Wireless Sensor Networks to prolong the network lifetime and to reduce network energy consumption. In this paper, we propose a new routing protocol called Fuzzy Based Energy Efficient Multiple Cluster Head Selection Routing Protocol (FEMCHRP) for Wireless Sensor Network. The routing process involves the Clustering of nodes and the selection of Cluster Head (CH) nodes of these clusters which sends all the information to the Cluster Head Leader (CHL). After that, the cluster head leaders send aggregated data to the Base Station (BS). The selection of cluster heads and cluster head leaders is performed by using fuzzy logic and the data transmission process is performed by shortest energy path which is selected applying Dijkstra Algorithm. The simulation results of this research are compared with other protocols BCDCP, CELRP and ECHERP to evaluate the performance of the proposed routing protocol. The evaluation concludes that the proposed routing protocol is better in prolonging network lifetime and balancing energy consumption.
Keywords: Fuzzy logic, Wireless Sensor Network, Cluster Head Leader, Shortest Energy Path, Dijkstra Algorithm.
Publication
Publication
S. Rana, A. N. Bahar, N. Islam, and J. Islam, “Fuzzy Based Energy Efficient Multiple Cluster Head Selection Routing Protocol for Wireless Sensor Networks,” IJCNIS, vol. 7, no. 4, pp. 54–61, Mar. 2015, doi: 10.5815/ijcnis.2015.04.07.
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