Towards a Load Balancing in a three-level cloud computing network

TLDR

Cloud computing has rapidly evolved as a distributed, virtualized service model that leverages network bandwidth and low‑power hosts to deliver scalable, reliable computing resources. The study proposes a two‑phase scheduling algorithm designed for a three‑level cloud computing network. The algorithm merges Opportunistic Load Balancing with Load Balance Min‑Min scheduling to improve execution efficiency while preserving system load balance.

Abstract

Network bandwidth and hardware technology are developing rapidly, resulting in the vigorous development of the Internet. A new concept, cloud computing, uses low-power hosts to achieve high reliability. The cloud computing, an Internet-based development in which dynamically scalable and often virtualized resources are provided as a service over the Internet has become a significant issue. The cloud computing refers to a class of systems and applications that employ distributed resources to perform a function in a decentralized manner. Cloud computing is to utilize the computing resources (service nodes) on the network to facilitate the execution of complicated tasks that require large-scale computation. Thus, the selecting nodes for executing a task in the cloud computing must be considered, and to exploit the effectiveness of the resources, they have to be properly selected according to the properties of the task. However, in this study, a two-phase scheduling algorithm under a three-level cloud computing network is advanced. The proposed scheduling algorithm combines OLB (Opportunistic Load Balancing) and LBMM (Load Balance Min-Min) scheduling algorithms that can utilize more better executing efficiency and maintain the load balancing of system.