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Frontiers of Computer Science

Front. Comput. Sci.    2017, Vol. 11 Issue (5) : 803-820
Towards application-level elasticity on shared cluster: an actor-based approach
Donggang CAO1,2(), Lianghuan KANG1,2, Hanglong ZHAN1,2, Hong MEI1
1. Key Lab of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing 100871, China
2. Beida (Binhai) Information Research, Tianjin 300450, China
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In current cluster computing, several distributed frameworks are designed to support elasticity for business services adapting to environment fluctuation. However, most existing works support elasticity mainly at the resource level, leaving application level elasticity support problem to domain-specific frameworks and applications. This paper proposes an actor-based general approach to support application-level elasticity for multiple cluster computing frameworks. The actor model offers scalability and decouples language-level concurrency from the runtime environment. By extending actors, a new middle layer called Unisupervisor is designed to “sit” between the resource management layer and application framework layer. Actors in Unisupervisor can automatically distribute and execute tasks over clusters and dynamically scale in/out. Based on Unisupervisor, high-level profiles (MasterSlave, MapReduce, Streaming, Graph, and Pipeline) for diverse cluster computing requirements can be supported. The entire approach is implemented in a prototype system called UniAS. In the evaluation, both benchmarks and real applications are tested and analyzed in a small scale cluster. Results show that UniAS is expressive and efficiently elastic.

Keywords elasticity      elastic scaling      actor programming model      cluster computing      concurrent and parallel processing     
Corresponding Authors: Donggang CAO   
Just Accepted Date: 25 February 2016   Online First Date: 31 October 2016    Issue Date: 26 September 2017
 Cite this article:   
Donggang CAO,Lianghuan KANG,Hanglong ZHAN, et al. Towards application-level elasticity on shared cluster: an actor-based approach[J]. Front. Comput. Sci., 2017, 11(5): 803-820.
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Donggang CAO
Lianghuan KANG
Hanglong ZHAN
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