A resource occupancy ratio-oriented load balancing task scheduling mechanism for Flink

Author:

Dai Qinglong1,Qin Guangjun1,Li Jianwu2,Zhao Jun3,Cai Jifan1

Affiliation:

1. Smart City College, Beijing Union University, Beijing, P. R. China

2. Advanced Technology Reseach Institute, Beijing Institute of Technology, Beijing, P. R. China

3. Institute of Big Data and Artificial Intelligence, Chinatelecom Research Institute, Beijing, P. R. China

Abstract

Flink is regarded as a promising distributed data processing engine for unifying bounded data and unbounded data. Unbalanced workloads upon multiple workers/task managers/servers in the Flink bring congestion, which will lead to the quality of service (QoS) decreasing. The balanced load distribution could efficiently improve QoS. Besides, existing works are lagging behind the current Flink version. To distribute workloads upon workers evenly, a resource-oriented load balancing task scheduling (RoLBTS) mechanism for Flink is proposed. The capacities of CPU, memory, and bandwidth are taken into consideration. Based on the barrel principle, the memory, and the bandwidth are respectively selected to model the resource occupancy ratio of the physical node and that of the physical link. On the based of modeled resource occupancy ratio, the data processing of load-balancing resource usage in Flink is formulated as a quadratic programming problem. Based on the self-recursive calling, a RoLBTS algorithm for scheduling task-needed resources is presented. Trough the numerical simulation, the superiority of our work is evaluated in terms of resource score, the number of possible scheduling solutions, and resource usage ratio.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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1. Flink Task Scheduling Based on LBGA;2023 4th International Conference on Information Science, Parallel and Distributed Systems (ISPDS);2023-07-14

2. A two-tier coordinated load balancing strategy over skewed data streams;The Journal of Supercomputing;2023-06-18

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