%0 Conference Proceedings
%T DROAllocator: A Dynamic Resource-Aware Operator Allocation Framework in Distributed Streaming Processing
%+ School of Cyber Security
%+ Institute of Information Engineering [Beijing] (IIE)
%+ State Key Laboratory of Information Security, Institute of Information Engineering
%A Liu, Fan
%A Jin, Zongze
%A Mu, Weimin
%A Zhu, Weilin
%A Zhang, Yun
%A Wang, Weiping
%Z Part 7: Emering
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 17th IFIP International Conference on Network and Parallel Computing (NPC)
%C Zhengzhou, China
%Y Xin He
%Y En Shao
%Y Guangming Tan
%I Springer International Publishing
%3 Network and Parallel Computing
%V LNCS-12639
%P 349-360
%8 2020-09-28
%D 2020
%R 10.1007/978-3-030-79478-1_30
%K Data stream processing
%K Operator allocation
%K Resource change
%K Deep learning
%Z Computer Science [cs]Conference papers
%X With the rapid development of Internet services and the Internet of Things (IoT), many studies focus on operator allocation to enhance the DSPAs’ (data stream processing applications) performance and resource utilization. However, the existing approaches ignore the dynamic changes of the node resources to allocate the operator instances to guarantee the performance, which increasing the number of migration leads to the waste of resources and the instability. To address these issues, we propose a framework named DROAllocator to select the appropriate nodes to allocate the operator instances. By capturing the change tendency of the node resources and the operator performance, our allocation mechanism decreases the number of migration to enhance the performance. The experimental results show the DROAllocator not only decrease the number of migrations to allocate the operator instances to ensure the end-to-end throughput and the latency, but also enhance the resource utilization.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-03768731/document
%2 https://inria.hal.science/hal-03768731/file/511910_1_En_30_Chapter.pdf
%L hal-03768731
%U https://inria.hal.science/hal-03768731
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3
%~ IFIP-LNCS-12639