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Users of cloud computing platforms pose different types of demands formultiple resources on servers (physical or virtual machines). Besidesdifferences in their resource capacities, servers may be additionallyheterogeneous in their ability to service users - certain users' tasks may onlybe serviced by a subset of the servers. We identify important shortcomings inexisting multi-resource fair allocation mechanisms - Dominant Resource Fairness(DRF) and its follow up work - when used in such environments. We develop a newfair allocation mechanism called Per-Server Dominant-Share Fairness (PS-DSF)which we show offers all desirable sharing properties that DRF is able to offerin the case of a single "resource pool" (i.e., if the resources of all serverswere pooled together into one hypothetical server). We evaluate the performanceof PS-DSF through simulations. Our evaluation shows the enhanced efficiency ofPS-DSF compared to the existing allocation mechanisms. We argue how ourproposed allocation mechanism is applicable in cloud computing networks andespecially large scale data-centers.

Per-Server Dominant-Share Fairness (PS-DSF): A Multi-Resource Fair Allocation Mechanism for Heterogeneous Servers