TY  - JOUR
AB  - Purpose– Expert Cloud as a new class of Cloud computing systems enables its users to request the skill, knowledge and expertise of people by employing internet infrastructures and Cloud computing concepts without any information of their location. Job scheduling is one of the most important issue in Expert Cloud and impacts on its efficiency and customer satisfaction. The purpose of this paper is to propose an applicable method based on genetic algorithm for job scheduling in Expert Cloud. Design/methodology/approach– Because of the nature of the scheduling issue as a NP-Hard problem and the success of genetic algorithm in optimization and NP-Hard problems, the authors used a genetic algorithm to schedule the jobs on human resources in Expert Cloud. In this method, chromosome or candidate solutions are represented by a vector; fitness function is calculated based on response time; one point crossover and swap mutation are also used. Findings– The results indicate that the proposed method can schedule the received jobs in appropriate time with high accuracy in comparison to common methods (First Come First Served, Shortest Process Next and Highest Response Ratio Next). Also the proposed method has better performance in term of total execution time, service+wait time, failure rate and Human Resource utilization rate in comparison to common methods. Originality/value– In this paper the job scheduling issue in Expert Cloud is pointed out and the approach to resolve the problem is applied into a practical example.
VL  - 43
IS  - 8
SN  - 0368-492X
DO  - 10.1108/K-02-2013-0018
UR  - https://doi.org/10.1108/K-02-2013-0018
AU  - Jafari Navimipour Nima
AU  - Masoud Rahmani Amir
AU  - Habibizad Navin Ahmad
AU  - Hosseinzadeh Mehdi
ED  - Dr Mourad Oussalah and Professor Ali Hessami
PY  - 2014
Y1  - 2014/01/01
TI  - Job scheduling in the Expert Cloud based on genetic algorithms
T2  - Kybernetes
PB  - Emerald Group Publishing Limited
SP  - 1262
EP  - 1275
Y2  - 2024/04/23
ER  -