Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System
Data prioritization problem is paramount for distributed publish/subscribe infrastructure to the timely delivery of real-time events since a large number of low priority events may clog the channel thereby causing high priority events to get delayed. The challenge raised for the event-based middlewa...
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doaj-b75de5fd63184e189d863211986be01b2020-11-25T03:43:31ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-10-011110.1155/2015/390329390329Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based SystemRuisheng Shi0Yang Zhang1Lina Lan2Fei Li3Junliang Chen4 Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, and School of Humanities, Beijing University of Posts and Telecommunications, Beijing 100876, China State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China School of Network Education, Beijing University of Posts and Telecommunications, Beijing 100088, China Siemens AG Austria, Siemensstrasse 90, 1210 Vienna, Austria State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaData prioritization problem is paramount for distributed publish/subscribe infrastructure to the timely delivery of real-time events since a large number of low priority events may clog the channel thereby causing high priority events to get delayed. The challenge raised for the event-based middleware in large-scale distributed system such as vehicular ad hoc networks is that event priority determination engine must be efficient and scalable in terms of priority rule size and event throughputs. This paper proposes an innovative approach based on Bloom filter and event discretization. A Bloom filter data structure is used to store the rule instances and their priorities. The complex rule evaluation is reduced to set membership testing as queries on Bloom filters. The time complexity of data prioritization is constant and independent of the number of priority rules. As event discretization signatures can be cached, this approach is cache friendly in nature. The previous computation results can be cached in overlay network nodes and reused to improve the system throughputs and determination time. We have evaluated our proposed approach and the results show a significant performance improvement.https://doi.org/10.1155/2015/390329 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ruisheng Shi Yang Zhang Lina Lan Fei Li Junliang Chen |
spellingShingle |
Ruisheng Shi Yang Zhang Lina Lan Fei Li Junliang Chen Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System International Journal of Distributed Sensor Networks |
author_facet |
Ruisheng Shi Yang Zhang Lina Lan Fei Li Junliang Chen |
author_sort |
Ruisheng Shi |
title |
Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System |
title_short |
Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System |
title_full |
Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System |
title_fullStr |
Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System |
title_full_unstemmed |
Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System |
title_sort |
summary instance: scalable event priority determination engine for large-scale distributed event-based system |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2015-10-01 |
description |
Data prioritization problem is paramount for distributed publish/subscribe infrastructure to the timely delivery of real-time events since a large number of low priority events may clog the channel thereby causing high priority events to get delayed. The challenge raised for the event-based middleware in large-scale distributed system such as vehicular ad hoc networks is that event priority determination engine must be efficient and scalable in terms of priority rule size and event throughputs. This paper proposes an innovative approach based on Bloom filter and event discretization. A Bloom filter data structure is used to store the rule instances and their priorities. The complex rule evaluation is reduced to set membership testing as queries on Bloom filters. The time complexity of data prioritization is constant and independent of the number of priority rules. As event discretization signatures can be cached, this approach is cache friendly in nature. The previous computation results can be cached in overlay network nodes and reused to improve the system throughputs and determination time. We have evaluated our proposed approach and the results show a significant performance improvement. |
url |
https://doi.org/10.1155/2015/390329 |
work_keys_str_mv |
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