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A Randomized Algorithm for Load Balancing in Containerized Cloud

机译:容器化云中负载均衡的随机算法

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Cloud computing is one of the highly discussed topics in the field of Internet and communication technology. It is responsible for the on-demand provision of computing resources, mainly data and computing power to the end-users. More than one server works together in a cloud network. So, the incoming request for resources must be distributed among all servers in the network for better performance. The process of efficiently distributing incoming tasks and sharing the workload among a group of servers is called load balancing. In this paper, we propose a randomized algorithm for load balancing in a containerized cloud. The approach we have used is called Balls into Bins via Local Search. In our algorithm, we have considered tasks as balls and servers as bins. First, we construct a fully connected undirected graph of nodes(server) and then convert it to a minimum edge weight graph to reduce the network cost. Our experimental result shows that the load is distributed among all servers almost equally. The difference between the highest and lowest workload in the network is minimized.
机译:云计算是Internet和通信技术领域中讨论最多的主题之一。它负责按需提供计算资源,主要是为最终用户提供数据和计算能力。一台以上的服务器在云网络中协同工作。因此,对于资源的传入请求必须在网络中的所有服务器之间分配,以实现更好的性能。在一组服务器之间有效地分配传入任务并共享工作负载的过程称为负载平衡。在本文中,我们提出了一种用于在容器化云中进行负载平衡的随机算法。我们使用的方法称为“通过本地搜索将球装进垃圾箱”。在我们的算法中,我们已将任务视为球,将服务器视为箱。首先,我们构造一个完全连接的节点(服务器)无向图,然后将其转换为最小边缘权重图,以降低网络成本。我们的实验结果表明,负载几乎平均分布在所有服务器之间。网络中最高和最低工作负载之间的差异已最小化。

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