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The rapid growth of networking technologies resulted in the execution of an extensive data-centric task, which needs the critical quality of service by cloud data centers. The task scheduling problem is difficult to attain an optimal solution, so we use the Squirrel Search Algorithm to approximate the optimal solution. Traditional scheduling algorithms attempt to reduce execution time without taking into account the energetic cost and security issues. In this scheme, a fuzzy-based task scheduling (SAEA) algorithm is developed which closely combines energy cost, makespan, degree of imbalance, and security levels for multi-objective optimization scheduling problems. In addition, SAEA tries to find a high-quality knowledge base that accurately describes the fuzzy system by parallel squirrels search algorithm (PSSA). The automatic design of a fuzzy rule-based system is currently attracting the interest due to the inherently …