ISCAS OpenIR  > 人机交互技术与智能信息处理实验室
rrps: a ranked real-time publish/subscribe using adaptive qos
Lu Xinjie; Li Xin; Yang Tian; Liao Zaifei; Liu Wei; Wang Hongan
2009
Conference NameInternational Conference on Computational Science and Its Applications (ICCSA 2009)
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference DateJUN 29-JUL
Conference PlaceSeoul, SOUTH KOREA
Publish PlaceHEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
PublisherCOMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2009, PT II
ISSN0302-9743
ISBN978-3-642-02456-6
DepartmentLu, Xinjie; Yang, Tian; Liao, Zaifei; Liu, Wei; Wang, Hongan Chinese Acad Sci, Inst Software, Beijing 100190, Peoples R China.
English AbstractPublish-Subscribe paradigm has been widely employed in Real-Time applications. However, the existing technologies and models only support a, simple binary concept of snatching: an event either matches a subscription or it does not; for instance, a production monitoring event will either snatch or not match a subscription for production anomaly. Based on adaptive Quality of Service (QoS) management, we propose a novel publish/subscribe model; which is implemented as a critical service in a real-time database Agilor. We argue that publications have different relevance to a subscription. On the premise of guaranteeing deadline d, a subscriber approximately receives k most relevant publications, where k and d are parameters defined by each subscription. After the architecture of our model is described, we present negotiations between components and scalable strategies for adaptive QoS management. Then, we propose an efficient algorithm to select different; strategies adaptively depending on estimation of current QoS. Furthermore, we experimentally evaluate our model on real production data collected from manufacture industry to demonstrate its applicability in practice.
KeywordAlgorithms Manufacture Publishing Quality Of Service
SponsorshipUniv Perugia, Monash Univ, Univ Calgary, La Trobe Univ, Soongsil Univ, Kyung Hee Univ
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8352
Collection人机交互技术与智能信息处理实验室
Recommended Citation
GB/T 7714
Lu Xinjie,Li Xin,Yang Tian,et al. rrps: a ranked real-time publish/subscribe using adaptive qos[C]. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY:COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2009, PT II,2009.
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