A scalable Multi-Tier Task Assignment Policy with Minimum Excess Load

Existing task assignment policies designed to schedule highly variable computer workloads are not scalable and they generate large amount of wasted processing. This paper proposes a scalable Multi-Tier Task Assignment Policy with Minimum Excess Load (MTTMEL) that can efficiently schedule tasks with highly variable processing requirements. Unlike existing policies, the proposed policy does not assign all incoming tasks to the first host in the system, rather it assigns incoming tasks to a subset of hosts in the system. The proposed policy has multiple tiers that consist of one or more hosts. The proposed policy scales well and it significantly reduces the amount wasted processing (excess load). For example, the TAGS policy produces 460% more wasted processing compared to MTTMEL under certain workloads. MTTMEL outperforms existing policies under a wide range of workload conditions. It outperforms RANDOM by a factor of 23 and TAGS by a factor of 2.6 under certain scenarios.