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Stream Processing i...
Stream Processing in Community Network Clouds
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- Danniswara, Ken (author)
- KTH,Programvaruteknik och Datorsystem, SCS
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- Peiro Sajjad, Hooman (author)
- KTH,Programvaruteknik och Datorsystem, SCS
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- Al-Shishtawy, Ahmad (author)
- SICS Swedish ICT
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- Vlassov, Vladimir (author)
- KTH,Programvaruteknik och Datorsystem, SCS
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(creator_code:org_t)
- IEEE conference proceedings, 2015
- 2015
- English.
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In: Future Internet of Things and Cloud (FiCloud), 2015 3rd International Conference on. - : IEEE conference proceedings. ; , s. 800-805
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https://kth.diva-por... (primary) (Raw object)
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Abstract
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- Community Network Cloud is an emerging distributed cloud infrastructure that is built on top of a community network. The infrastructure consists of a number of geographically distributed compute and storage resources, contributed by community members, that are linked together through the community network. Stream processing is an important enabling technology that, if provided in a Community Network Cloud, would enable a new class of applications, such as social analysis, anomaly detection, and smart home power management. However, modern stream processing engines are designed to be used inside a data center, where servers communicate over a fast and reliable network. In this work, we evaluate the Apache Storm stream processing framework in an emulated Community Network Cloud in order to identify the challenges and bottlenecks that exist in the current implementation. The community network emulation was performed using data collected from the Guifi.net community network, Spain. Our evaluation results show that, with proper configuration of the heartbeats, it is possible to run Apache Storm in a Community Network Cloud. The performance is sensitive to the placement of the Storm components in the network. The deployment of management components on wellconnected nodes improves the Storm topology scheduling time, fault tolerance, and recovery time. Our evaluation also indicates that the Storm scheduler and the stream groupings need to be aware of the network topology and location of stream sources in order to optimally place Storm spouts and bolts to improve performance.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Publication and Content Type
- ref (subject category)
- kon (subject category)
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