{"id":340334,"date":"2016-12-21T16:13:52","date_gmt":"2016-12-22T00:13:52","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=340334"},"modified":"2018-10-16T20:32:04","modified_gmt":"2018-10-17T03:32:04","slug":"autonomous-resource-selection-decentralized-utility-computing","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/autonomous-resource-selection-decentralized-utility-computing\/","title":{"rendered":"Autonomous Resource Selection for Decentralized Utility Computing"},"content":{"rendered":"

Many large-scale utility computing infrastructures comprise heterogeneous hardware and software resources. This raises the need for scalable resource selection services, which identify resources that match application requirements, and can potentially be assigned to these applications. <\/p>\n

We present a fully decentralized resource selection algorithm by which resources autonomously select themselves when their attributes match a query. An application specifies what it expects from a resource by means of a conjunction of (attribute, value-range) pairs, which are matched against the attribute values of resources. We show that our solution scales in the number of resources as well as in the number of attributes, while being relatively insensitive to churn and other membership changes such as node failures. <\/p>\n","protected":false},"excerpt":{"rendered":"

Many large-scale utility computing infrastructures comprise heterogeneous hardware and software resources. This raises the need for scalable resource selection services, which identify resources that match application requirements, and can potentially be assigned to these applications. We present a fully decentralized resource selection algorithm by which resources autonomously select themselves when their attributes match a query. 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