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    PublicationOpen Access
    Task Scheduling Problem in Fog Computing Environment with improved Memetic algorithm
    (Faculty of Engineering, 2026-03) Thang, D.V; Artem, V; Muthanna, A; Vorozheikina, O; Koucheryavy, A
    The task scheduling problem in fog computing is one of the key challenges in the development of fog computing within next-generation communication networks. Addressing this challenge requires balancing processing performance with resource constraints while meeting network conditions. Given the distributed and heterogeneous nature, as well as the dynamic topology, optimally allocating tasks to fog nodes is a complex issue. To contribute to solving this problem, we propose a task scheduling method based on an improved Memetic algorithm. The proposed method leverages the strengths of evolutionary algorithms and local search, while incorporating a task restructuring mechanism, to enhance allocation efficiency and task processing in the fog computing environment. Simulation experiments demonstrate that the proposed method outperforms genetic algorithms, Round-Robin, Greedy methods, and the Ant Colony Optimization algorithm in terms of efficiency. This study provides a fresh, simpler approach that aligns with network conditions while still achieving the desired performance.
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    PublicationEmbargo
    Collabcrew—an intelligent tool for dynamic task allocation within a software development team
    (IEEE, 2017-12-06) Samath, S; Udalagama, D; Kurukulasooriya, H; Premarathne, D; Thelijjagoda, S
    Currently in the IT industry, the people factor has become very critical when determining the quality of a software project. It is highly important that the correct person performs the relevant task and proper human resource allocation happens within the software project team to obtain successful outcome. This often needs critical thinking, regular team meetings and discussions. Typically a software project manager needs to be highly experienced with the team for this purpose and can be really complex and time consuming with the limited project schedules. This research work introduces a task management tool - CollabCrew specially designed for the software development teams which dynamically allocate tasks based on the skills and previous work done by the team members. This uses historical data from its' own repository or from an external source to find useful information of the previous work done by the project team members to automatically allocate them for new tasks. This proposed system will be containing an Extract, Transform and Load (ETL) tool which will extract data from different data sources, a prediction model to predict the aptness of each team member for a given task and a peer review mining and summarization component to provide a viable way to extract features from peer reviews. Then based on the result, the task allocation component will do the allocations in the most optimal and the feasible way for the project. Even though there are several commercially available task management tools, none has an intelligent component to automatically delegate work within the team. The scope of this work extends beyond the IT domain and a similar procedure can be adopted to develop a task allocation framework in other fields as well.