A Cost-Aware Fair Allocation Mechanism for Multi-Resource Servers

We propose a cost-aware measure to establish fair-sharing of multi-resource/heterogeneous servers among multiple users. Each server attributes a virtual cost to the total allocated resources to each user, and strives to allocate resources to users attaining the minimum virtual cost. With the new mechanism, called per-server virtual cost fairness (PS-VCF), users do not envy the cost-allotments of each other. We develop a distributed implementation for the proposed mechanism which is also adapted to apply resource-throttling on a per-server basis. We employ numerical experiments using real-world traces to show the effectiveness of PS-VCF in reducing servers’ operational costs.

[1]  Alexandru Iosup,et al.  Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters , 2015, 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.

[2]  Benjamin Hindman,et al.  Dominant Resource Fairness: Fair Allocation of Multiple Resource Types , 2011, NSDI.

[3]  Feng Zhao,et al.  Virtual machine power metering and provisioning , 2010, SoCC '10.

[4]  Jerome A. Rolia,et al.  Workload Analysis and Demand Prediction of Enterprise Data Center Applications , 2007, 2007 IEEE 10th International Symposium on Workload Characterization.

[5]  Ioannis Lambadaris,et al.  A Cost-Efficient and Fair Multi-Resource Allocation Mechanism for Self-Organizing Servers , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[6]  Mung Chiang,et al.  Multiresource allocation: fairness-efficiency tradeoffs in a unifying framework , 2013, TNET.

[7]  Baochun Li,et al.  Multi-resource Fair Sharing for Datacenter Jobs with Placement Constraints , 2016, SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.

[8]  Ioannis Lambadaris,et al.  An Efficient and Fair Multi-Resource Allocation Mechanism for Heterogeneous Servers , 2017, IEEE Transactions on Parallel and Distributed Systems.

[9]  Wei Wang,et al.  Multi-Resource Fair Allocation in Heterogeneous Cloud Computing Systems , 2015, IEEE Transactions on Parallel and Distributed Systems.

[10]  Eric J. Friedman,et al.  Strategyproof allocation of discrete jobs on multiple machines , 2014, EC.