Browsing by Author "Kouidri, Chaimaa"

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    Data-Intensive Scientific Workflow Scheduling Based on Genetic Algorithm in Cloud Computing
    (University of Eloued جامعة الوادي, 2022-01-24) Kouidri, Siham; Kouidri, Chaimaa
    Cloud Computing is increasingly recognized as a new way to use ondemand, computing, storage and network services in a transparent and efficient way. Cloud Computing environment consists of large customers requesting for cloud resources. Nowadays, task scheduling problem and data placement are the current research topic in cloud computing. In this work, a new technique for task scheduling and data placement are proposed based on genetic algorithm to fulfill a final goal such as minimizing total workflow response time. the scheduling of scientific workflows is considered to be an NP-complete problem, i.e. a problem not solvable within polynomial time with current resources The performance of this proposed algorithm has been evaluated using CloudSim toolkit, Simulation results show the effectiveness of the proposed algorithm in comparison with well-known algorithms such as genetic algorithm with Random data placement.
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    Theoretical Model of Traffic Signal Timing Optimisation Improved On ant colony Optimisation and Symbiotic Organism Search
    (University of Eloued جامعة الوادي, 2022-01-24) Kouidri, Chaimaa; Mahi, Faiza; Bouiadjra, Rochdi Bachir
    Due to the increasing in the number of vehicules on a daily basis, road congestion is becoming a key challenge. Therefore, it becomes essential to develop a signal optimization method for multi-intersections. In this paper, the proposed model is capable of minimizing waiting time of vehicule.an hybrid meta-heuristic algorithm (Ant Colony, Symbiotic Organism Search) is employed to solve the model. We proposed a hybridization of two bio inspired methods, the first based on the use of ant colony to determine the critical path, the critical path is the input of the next step. The second step is based on the minimization of vehicles with the metaheuristic SOS. The main focus of this study is on improving the quality of solutions for the traffic light optimization problem to minimize the waiting time of all the vehicles within a certain time period.