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Bio-inspired Based Task Scheduling in Cloud Computing

  • Marwa Gamal
  • Rawya Rizk
  • Hani Mahdi
  • Basem Elhady
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 801)

Abstract

Cloud computing meets numerous challenges at increasing number of users because the demand of resources sharing and usage are increased rapidly. Therefore, load balancing between resources is an important field for scheduling tasks to achieve better performance. In this chapter, a Hybrid Artificial Bee and Ant Colony optimization (H_BAC) load balancing algorithm is proposed. It depends on joining the important behavior of Ant Colony Optimization (ACO) such as discovering good solutions rapidly and Artificial Bee Colony (ABC) algorithm such as collective interaction of bees and sharing information by waggle dancing. The performance of the proposed algorithm is compared with ACO, ABC, and an existing hybrid algorithm. The simulation results show that H_BAC improves execution time, response time, makespan, resource utilization and standard deviation. This improvement reaches about 40% in the execution time and response time and 30% in the makespan over the other algorithms.

Keywords

Ant colony optimization Artificial bee colony Bio-inspired systems Cloud computing Load balancing 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Marwa Gamal
    • 1
  • Rawya Rizk
    • 2
  • Hani Mahdi
    • 3
  • Basem Elhady
    • 1
  1. 1.Electrical Engineering DepartmentSuez Canal UniversityIsmailiaEgypt
  2. 2.Electrical Engineering DepartmentPort Said UniversityPort SaidEgypt
  3. 3.Computers and Systems Engineering DepartmentAin Shams UniversityCairoEgypt

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