Dynamic scope of control in decentralized job scheduling

Each job scheduling agent in large decentralized load balancing systems generally has a set of remote hosts (i.e., its scope of control) to consider for offloading when the local load is too high. Typically, each agent´s scope of control includes all the hosts in the system. The potential performance benefits of limiting the size of each agent´s scope of control are investigated. The larger the scope of control, the less often state information can lower the quality of load balancing decisions. The smaller the scope of control, the less opportunity an agent has for finding a lightly loaded host for offloading. Agents adaptively modify their scope of control over time based on feedback regarding the success of load balancing decisions and act as a self-organizing system to efficiently share available processing power