Name
Abstract | ||
|---|---|---|
The emergence of the cloud computing paradigm has greatly enabled innovative service models, such as Platform as a Service (PaaS), and distributed computing frameworks, such as Map Reduce. However, most existing cloud systems fail to distinguish users with different preferences, or jobs of different natures. Consequently, they are unable to provide service differentiation, leading to inefficient allocations of cloud resources. Moreover, contentions on the resources exacerbate this inefficiency, when prioritizing crucial jobs is necessary, but impossible. Motivated by this, we propose Abacus, a generic resource management framework addressing this problem. Abacus interacts with users through an auction mechanism, which allows users to specify their priorities using budgets, and job characteristics via utility functions. Based on this information, Abacus computes the optimal allocation and scheduling of resources. Meanwhile, the auction mechanism in Abacus possesses important properties including incentive compatibility (i.e., the users' best strategy is to simply bid their true budgets and job utilities) and monotonicity (i.e., users are motivated to increase their budgets in order to receive better services). In addition, when the user is unclear about her utility function, Abacus automatically learns this function based on statistics of her previous jobs. An extensive set of experiments, running on Hadoop, demonstrate the high performance and other desirable properties of Abacus. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IC2E.2013.43 | IC2E |
Keywords | Field | DocType |
generic resource management framework,distributed computing frameworks,cloud,cloud resource,service differentiation,scheduling,better service,paas,statistics,job characteristics,map reduce,monotonicity,existing cloud system,utility function,innovative service model,platform as a service,utility functions,resource allocation,resource scheduling,auction-based approach,auction,incentive compatibility,cloud service differentiation,budgets,cloud resource allocation,abacus,electronic commerce,cloud computing paradigm,cloud computing,auction mechanism,abacus interacts,innovative service models,hadoop,different nature,different preference,bandwidth,optimization,job shop scheduling,resource management,computational modeling | Resource management,Cloud resources,Incentive compatibility,Abacus (architecture),Computer science,Scheduling (computing),Inefficiency,Resource allocation,Cloud computing,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4673-6473-7 | 11 | 0.62 |
References | Authors | |
20 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenjie Zhang | 1 | 1288 | 61.63 |
| Richard T. B. Ma | 2 | 620 | 51.15 |
| Jianbing Ding | 3 | 68 | 4.72 |
| Yin Yang | 4 | 1003 | 52.10 |