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Automatic Message Compression with Overload Protection
Ericsson, Stockholm, Sweden.ORCID iD: 0000-0003-2612-4135
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5070-9312
Ericsson, Stockholm, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5297-6548
2016 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 121, no 1 nov, 209-222 p.Article in journal (Refereed) Published
Resource type
Text
Abstract [en]

In this paper, we show that it is possible to increase the message throughput of a large-scale industrial system by selectively compress messages. The demand for new high-performance message processing systems conflicts with the cost effectiveness of legacy systems. The result is often a mixed environment with several concurrent system generations. Such a mixed environment does not allow a complete replacement of the communication backbone to provide the increased messaging performance. Thus, performance-enhancing software solutions are highly attractive. Our contribution is 1) an online compression mechanism that automatically selects the most appropriate compression algorithm to minimize the message round trip time; 2) a compression overload mechanism that ensures ample resources for other processes sharing the same CPU. We have integrated 11 well-known compression algorithms/configurations and tested them with production node traffic. In our target system, automatic message compression results is a 9.6% reduction of message round trip time. The selection procedure is fully automatic and does not require any manual intervention. The automatic behavior makes it particularly suitable for large systems where it is difficult to predict future system behavior.

Place, publisher, year, edition, pages
2016. Vol. 121, no 1 nov, 209-222 p.
Keyword [en]
Automatic compression, Message compression, Feedback control, Performance prediction, Network performance, Mobile systems
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-31500DOI: 10.1016/j.jss.2016.04.010ISI: 000384864500015Scopus ID: 2-s2.0-84966728710OAI: oai:DiVA.org:mdh-31500DiVA: diva2:926043
Available from: 2016-05-03 Created: 2016-05-03 Last updated: 2017-11-30Bibliographically approved
In thesis
1. Utilizing Hardware Monitoring to Improve the Performance of Industrial Systems
Open this publication in new window or tab >>Utilizing Hardware Monitoring to Improve the Performance of Industrial Systems
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The drastically increasing use of Information and Communications Technology has resulted in a growing demand for network capacity. In this Licentiate thesis, we show how to monitor, model and finally improve network performance for large industrial systems. We also show how to use modeling techniques to move performance testing to an earlier design phase, with the aim to reduce the total development time of large systems. Our first contribution is a low-intrusive method for long-term hardware characteristic measurements of production nodes located at customer sites. Our second contribution is a technique to mimic the hardware usage of a production environment by creating a characteristics model. The cloned environment makes function test suites more realistic. The goal when creating the model is to reduce the system development time by moving late-stage performance testing to early design phases thereby improving the quality of the test environment. The third and final contribution is a network performance improvement where we dynamically trade computational capacity for a message round-trip time reduction when there are CPU cycles to spare. We have implemented an automatic feedback controlled mechanism for transparent message compression resulting in improved messaging performance between interconnected network nodes. Our mechanism continuously evaluates eleven compression algorithms on message stream content and network congestion level. The message subsystem will use the compression algorithm that provides the lowest messaging time. If the message content or network load change, a new evaluation is performed. We have conducted several case studies in an industrial environment and verified all contributions on a large telecommunication system manufactured by Ericsson. System engineers frequently use the monitoring and modeling functionality for debugging purposes in production environments. We have deployed all techniques in a complicated industrial legacy system with minimal impact. We show that we can provide not only a solution but a cost-effective solution, which is an important requirement for industrial systems.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2016
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 200
National Category
Computer Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-31501 (URN)978-91-7485-203-5 (ISBN)
Presentation
2016-06-20, Kappa, Mälardalens högskola, Västerås, 13:00 (English)
Opponent
Supervisors
Projects
ITS-EASY
Available from: 2016-05-04 Created: 2016-05-03 Last updated: 2016-06-01Bibliographically approved

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