An online resource-aware leader election algorithm based on Kubernetes load balancing

An online resource-aware leader election algorithm based on Kubernetes load balancing

연구 분야: Software Development

학회: CCF Transactions on High Performance Computing

Kubernetes is a well-known distributed system for managing containers. It is essential to elect a leader among the replicas to maintain data consistency and coordinate tasks when deploying certain stateful services in a cluster. There are already many leader election algorithms used in distributed systems, but the cost of implementing these algorithms in a Kubernetes cluster is exorbitantly expensive. The existing leader election algorithms in Kubernetes do not take into account the state of the nodes in the election process for distributing the leader, resulting in unbalanced utilization of the cluster and hindering overall cluster performance. This paper proposes an online, resource-aware leader election algorithm to address the aforementioned issues. The algorithm dynamically retrieves the status of cluster nodes to influence the distribution of leaders, ensuring a more balanced allocation of leadership across nodes. This approach helps optimize cluster performance and load balancing. Through experimental comparisons, the algorithm achieves a minimum improvement of 82% in load balancing effectiveness compared to the default and existing improved leader election algorithms, using the coefficient of variation to validate the results.