Self Scheduling Based on Hexagonal Chebysev Gaussian and Discrete Time Organized Mapping in Cloud

Cloud Computing (CC) has become an appealing computing criterion in both academic and business establishments. Fault tolerance is the key challenge faced by the CSP to provide guaranteed service to its users. Prior works proposed various algorithms for guaranteeing fault tolerance using job scheduling by assigning deadlines via time sliding (TS) and bandwidth scaling (BS). Job scheduling has proven to be an effective method to reduce fault occurrence and to address scalable user requests by balancing the incoming load. This paper proposes Hexagonal Chebyshev Gaussian and Discrete Time Organized Map-based (HCG-DTOM) job scheduling method which is an adaptive fault tolerance method based on Self organizing map. The HCG-DTOM method involves four steps. They are Hexagonal Lattice Structure Initialization model that performs initialization of cloud users, jobs to be assigned, virtual machines and job scheduler. Second, the virtual manager checks resource availability for a given set of input jobs using Chebyshev Discriminant Competitive model. Third, scheduling is performed by the job scheduler via Gaussian Neighbourhood Cooperative model. Finally, the resources are updated with the corresponding jobs for the appropriate cloud users are performed using the Discrete Time Adaptation model.