Abstract
Determining termination in dynamic environments is hard due to node joining and leaving. In previous studies on termination detection, some structures, such as spanning tree or computational tree, are used. In this work, we present an unstructured termination detection algorithm, which uses a gossip based scheme to cope with scalability and fault-tolerance issues. This approach allows the algorithm not to maintain specific structures even when nodes join and leave during runtime. These dynamic behaviors are prevalent in cloud computing environments and little attention has been paid by existing approaches. To measure the complexity of our proposed algorithm, a new metric, self-centered message complexity is used. Our evaluation over scalable settings shows that an unstructured approach has a significant merit to solve scalability and fault-tolerance problems with lower message complexity over existing algorithms.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea goverment (MEST) (No. 2012046684).
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Lim, J., Chung, KS., Gil, JM., Suh, T., Yu, H. (2013). An Unstructured Termination Detection Algorithm Using Gossip in Cloud Computing Environments. In: Kubátová, H., Hochberger, C., Daněk, M., Sick, B. (eds) Architecture of Computing Systems – ARCS 2013. ARCS 2013. Lecture Notes in Computer Science, vol 7767. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36424-2_1
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