{'fraction_non_alphanumeric': 0.044035228182546036, 'fraction_numerical': 0.009607686148919135, 'mean_word_length': 5.868131868131868, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An Enhanced Firefly Algorithm for Time ‎‎Shared Grid Task ‎Scheduling‎

ABSTRACT Grid computing is a computational paradigm that emerged to ‎‎handle the increasing demand for ‎computational resources. Several metaheuristics methods ‎‎have been applied ‎to tackle the grid task scheduling problem. ‎‎These metaheuristics generally generate good but not optimal ‎‎task ‎schedules. The aim of this paper is to design and ‎‎implement a grid task scheduling mechanism to map clients’ tasks to ‎‎ ‎available resources in order to finish the submitted tasks ‎‎within the optimal execution time. The paper proposes ‎an ‎‎enhanced time shared metaheuristics mechanism based on ‎‎Firefly Algorithm to ‎‎improve the grid job scheduling process. The proposed mechanism utilizes the Smallest Position ‎Value (SPV) technique to handle the scheduling problem as ‎permutations. Experiments using ‎‎simulations and real workload traces were ‎conducted to study ‎‎the performance of the proposed enhanced time shared ‎‎metaheuristic scheduling mechanism. ‎Empirical results revealed ‎‎that the proposed timed shared ‎metaheuristic algorithm can efficiently reduce the makespan time to 1851 compared with 3482, 3185 for Tabu search and genetic algorithm, respectively.