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Language expressiveness and quality of service for content-based publish/subscribe systems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhang, Kaiwen |
| Copyright Year | 2016 |
| Abstract | Language Expressiveness and Quality of Service for Content-based Publish/Subscribe Systems Kaiwen Zhang Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2015 The publish/subscribe paradigm is known for its loosely coupled interactions and event filtering capabilities. Traditional applications using pub/sub systems require large-scale deployment and high event throughput. Thus, pub/sub has always put the emphasis on scalability and performance, to the detriment of filtering expressiveness and quality of service. The matching language is usually limited to topic-based or content-based event filtering and does not allow complex stream-based subscriptions to be expressed. Messages are delivered on a best-effort basis without any ordering or reliability guarantees. Recently, modern pub/sub applications such as online games, social networks, and sensor networks, have specifications which extend beyond the basic semantics provided by standard systems. Installing additional services and event processing systems at the endpoints can overcome these limitations. However, this thesis argue that such solutions are inefficient and put an avoidable strain on the pub/sub layer itself. Therefore, the focus of this thesis is to develop integrated solutions to extend pub/sub language expressiveness and quality of service, as well as demonstrate that this approach results in better performance from a holistic perspective. The different pub/sub extensions described are ranked data dissemination, fair subscription filtering, and total order. Each section first describes the applica- |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://msrg.org/publications/pdf_files/2015/kzthesis-Language_Expressiveness_and_Quality_.pdf |
| Alternate Webpage(s) | https://tspace.library.utoronto.ca/bitstream/1807/71714/3/Zhang_Kaiwen_201603_PhD_thesis.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Thesis |
