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 ...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.展开更多
With the rapid development of cloud computing and big data processing, an increasing number of application frameworks are being considered to run in a "cloud way". This development brings about several challenges to...With the rapid development of cloud computing and big data processing, an increasing number of application frameworks are being considered to run in a "cloud way". This development brings about several challenges to the enterprise private cloud computing platform, e.g., being able to run most existing heterogeneous applications, providing scalability and elasticity support for newly emerged frameworks, and most importantly,sharing cluster resources effectively. In this paper, we propose a new service model, namely, Cluster as a Service(Claa S), which is suitable for medium- and small-sized data centers to solve these problems in a relatively easy and general way. The idea behind this model is virtualizing the cluster environment for distributed application frameworks. Most applications can directly run in the virtual cluster environment without any modification, which is a great advantage. Based on lightweight containers, we implement a real system of Claa S named Docklet to prove the feasibility of this service model. Meanwhile, we preliminarily design the definition of applications to make them easy to deploy. Finally, we present several examples and evaluate the entire system.展开更多
基金Acknowledgements This work was supported by the National High-Tech Research and Development Plan of China (2015AA01A202), National Basic Research Program of China (973) (2011CB302604), and the National Natural Science Foundation of China (Grant Nos. 61272154 and 61421091).
文摘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.
基金supported by the National Science and Technology Major Project(No.2016YFB-1000105)the National Natural Science Foundation of China(No.61272154)the Science Fund for Creative Research Groups of China(No.61421091)
文摘With the rapid development of cloud computing and big data processing, an increasing number of application frameworks are being considered to run in a "cloud way". This development brings about several challenges to the enterprise private cloud computing platform, e.g., being able to run most existing heterogeneous applications, providing scalability and elasticity support for newly emerged frameworks, and most importantly,sharing cluster resources effectively. In this paper, we propose a new service model, namely, Cluster as a Service(Claa S), which is suitable for medium- and small-sized data centers to solve these problems in a relatively easy and general way. The idea behind this model is virtualizing the cluster environment for distributed application frameworks. Most applications can directly run in the virtual cluster environment without any modification, which is a great advantage. Based on lightweight containers, we implement a real system of Claa S named Docklet to prove the feasibility of this service model. Meanwhile, we preliminarily design the definition of applications to make them easy to deploy. Finally, we present several examples and evaluate the entire system.