On-line fair allocations based on bottlenecks and global priorities

System bottlenecks, namely those resources which are subjected to high contention, constrain system performance. Hence effective resource management should be done by focusing on the bottleneck resources and allocating them to the most deserving clients. It has been shown that for any combination of entitlements and requests a fair allocation of bottleneck resources can be found, using an off-line algorithm that is given full information in advance regarding the needs of each client. We extend this result to the on-line case with no prior information. To this end we introduce a simple greedy algorithm. In essence, when a scheduling decision needs to be made, this algorithm selects the client that has the largest minimal gap between its entitlement and its current allocation among all the bottleneck resources. Importantly, this algorithm takes a global view of the system, and assigns each client a single priority based on his usage of all the resources; this single priority is then used to make coordinated scheduling decisions on all the resources. Extensive simulations show that this algorithm achieves fair allocations according to the desired entitlements for a wide range of conditions, without using any prior information regarding resource requirements. It also follows shifting usage patterns, including situations where the bottlenecks change with time.