A Fair and Effective Scheduling Algorithm for Multi-Agent Systems

With the rapid increase of global connectivity, various types of distributed computer systems are being implemented to process information located in all parts of the world. Some distributed computing systems such as multi-agent systems require the same task to be applied to many individual instances of data located on disparate nodes. In such an environment, however, some agents may finish earlier than the others, due to the difference in the volume of data to be processed on a node and/or competition with other users' agents running on the same node. In this case, the time taken to complete the task depends on the slowest agent. Most of the existing scheduling algorithms hardly consider the status of the whole system for this type of application. In this paper, we propose and evaluate a fair and effective scheduling algorithm for multi-agent systems based on the processing status of each agent, the CPU power of each node, and the computational demand of each user. Simulation experiments show excellent performance of our scheduling algorithm.