Optimizing Task Scheduling in Cloud Computing: A Hybrid Approach Integrating Bandwidth Awareness and Bar System Model for Enhanced Efficiency
Keywords:
Cloud Computing, Task scheduling, Optimization, Enhanced EfficiencyAbstract
The emergence of the cloud computing era has led to the development of new technologies and the increasing complexity of task scheduling in the cloud. One of the biggest challenges in the management of this platform is the allocation of the appropriate resources to the tasks. In order to improve the performance of the cloud computing environment, various algorithms have been proposed.Existing algorithms suffer from their own issues. In this paper, we present a hybrid model that takes into account the various factors that affect the task's prioritization. The suggested method is based on the Bandwidth-Aware Task Scheduling model with the addition of the Bar system model.The proposed algorithm employs a minimum lease policy and an overload pre-emptively within a data center to address the issue of overrunning virtual machines. Different tests are performed on the hybrid model to evaluate its efficiency. The results of these tests proved the model's effectiveness.
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