Abstract
Cloud computing is an emerging trend in the IT industry that provides new opportunities to control costs associated with the creation and maintenance of applications. Of prevalent issues in cloud computing, load balancing is a primary one as it has a significant impact on efficiency and plays a leading role in improved management. In this paper, by using a heuristic search technique called the bee colony algorithm, tasks are balanced on a virtual machine such that their waiting time in the queue is minimized. In the proposed model, the cloud is partitioned into several sectors with many nodes as resources of distributed computing. Furthermore, the indices of speed and cost are considered to prioritize virtual machines. The results of a simulation show that the proposed model outperforms prevalent algorithms as it balances the prioritization of tasks on the virtual machine as well as the entire cloud system and minimizes the waiting times of tasks in the queue. It also reduces the completion time of tasks in comparison with the HBB-LB, WRR, and FCFS algorithms.
Highlights
Cloud computing provides ways of presenting IT services in a similar manner to public utility companies
Load balancing in cloud computing environments, inspired by the algorithm that mirrors the foodfinding behavior of honey bees (HBB-LB), is used
The cloud is partitioned into several sectors and a load balancing method is used in the smaller sectors
Summary
Cloud computing provides ways of presenting IT services in a similar manner to public utility companies. The advantage of static load balancing is its simple implementation and low overhead, as there is no need to permanently monitor nodes to assess the efficiency of the system These algorithms work well when there are small changes in loads in virtual machines. They are not appropriate for cloud and grid computing environments because the load on the network is variable at every point of time in such environments. The second category of load balancing and resource management techniques consists of algorithms of dynamic load balancing. In these algorithms, the distribution of load among nodes changes, and they use the given information to make decisions about load distribution. The third category consists of hybrid algorithms, which involve the hybrid use of static and dynamic algorithms, and switch between them when necessary
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