A new delay jitter smoothing algorithm based on Pareto distribution in Cyber-Physical Systems
Delay jitter, which can affect the performance of controlled physical system and result in system instability, is an important issue for supporting instantaneity in Cyber-Physical Systems (CPSs) to guarantee continuous, real-time and dependable operation. Thus, it is significant to establish an algo...
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| Published in: | Wireless networks Vol. 21; no. 6; pp. 1913 - 1923 |
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| Format: | Journal Article |
| Language: | English |
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01.08.2015
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| ISSN: | 1022-0038, 1572-8196 |
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| Abstract | Delay jitter, which can affect the performance of controlled physical system and result in system instability, is an important issue for supporting instantaneity in Cyber-Physical Systems (CPSs) to guarantee continuous, real-time and dependable operation. Thus, it is significant to establish an algorithm to smoothing the delay jitter. In this paper, first, we compare several delay jitter smoothing algorithms, discuss their merits and demerits, and then propose one new algorithm over the existing algorithms, called derivative least square (DLS), which can eliminates the reverse way delay variation spikes. Second, we address the problem of most delay jitter smoothing schemes, namely they used uniformly distributed random numbers to simulate network delay data, which deviates from real network delay. To demonstrate the validity and reliability of DLS, except uniform distribution, Pareto distribution, of which the cumulative distribution function (CDF) is more close to the CDF of real network delay, is applied to conduct the experiment. The experimental results show that compared with the other three existing algorithms, DLS can be more effective and reliable in predicting the play-back delay. |
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| AbstractList | Delay jitter, which can affect the performance of controlled physical system and result in system instability, is an important issue for supporting instantaneity in Cyber-Physical Systems (CPSs) to guarantee continuous, real-time and dependable operation. Thus, it is significant to establish an algorithm to smoothing the delay jitter. In this paper, first, we compare several delay jitter smoothing algorithms, discuss their merits and demerits, and then propose one new algorithm over the existing algorithms, called derivative least square (DLS), which can eliminates the reverse way delay variation spikes. Second, we address the problem of most delay jitter smoothing schemes, namely they used uniformly distributed random numbers to simulate network delay data, which deviates from real network delay. To demonstrate the validity and reliability of DLS, except uniform distribution, Pareto distribution, of which the cumulative distribution function (CDF) is more close to the CDF of real network delay, is applied to conduct the experiment. The experimental results show that compared with the other three existing algorithms, DLS can be more effective and reliable in predicting the play-back delay. |
| Author | Liu, Ping Zhang, Xiang-Li |
| Author_xml | – sequence: 1 givenname: Xiang-Li surname: Zhang fullname: Zhang, Xiang-Li organization: Institute of Information and Communication, Guilin University of Electronic Technology – sequence: 2 givenname: Ping surname: Liu fullname: Liu, Ping email: echo860504@163.com organization: Institute of Information and Communication, Guilin University of Electronic Technology |
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| CitedBy_id | crossref_primary_10_3390_met12122028 crossref_primary_10_1109_JPROC_2016_2519381 crossref_primary_10_1109_ACCESS_2017_2682499 crossref_primary_10_1109_ACCESS_2017_2772328 crossref_primary_10_1016_j_flowmeasinst_2019_101626 crossref_primary_10_1109_TNB_2020_2990690 |
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| Keywords | Pauta criterion Cyber-Physical Systems (CPSs) Derivative least square (DLS) Pareto distribution Delay jitter smoothing algorithms |
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| References_xml | – reference: ZhangWHeJSStatistical modeling and correlation analysis of end-to-end delay in wide area networksEighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing2007396897310.1109/SNPD.2007.490 – reference: SongYNLiuLMaHDA biology-based algorithm to minimal exposure problem of wireless sensor networksIEEE Transactions on Network and Service Management201411341743010.1109/TNSM.2014.2346080 – reference: Oklander., Sidi M. (2008). Jitter buffer analysis. In Computer Communications and Networks, ICCCN’08. Proceedings of 17th International Conference on, IEEE, 1–6. – reference: SenguptaSDasSNasirMAn evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networksIEEE Transactions on Systems, Man, and Cybernetics, Part C20124261093110210.1109/TSMCC.2012.2196996 – reference: LiMLiZJVasilakosVAA survey on topology control in wireless sensor networks: Taxonomy, comparative study, and open issuesProceedings of the IEEE2013101122538255710.1109/JPROC.2013.2257631 – reference: Leonardi, F., Pinto, A., & Carloni, L. P. (2011). Synthesis of distributed execution platforms for cyber-physical systems with applications to high-performance buildings. Proceedings of the IEEE/ACM International Conference on Cyber-Physical Systems (pp. 215–224). USA: IEEE. – reference: YoussefMIbrahimMAbdelatifMRouting metrics of cognitive radio networks: A surveyIEEE Communications Surveys and Tutorials20141619210910.1109/SURV.2013.082713.00184 – reference: Han, K., Luo, J., Liu, Y., et al. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine,51(7), 107–113. – reference: ShengZGYangSSYuYFA survey on the ietf protocol suite for the internet of things: Standards, challenges, and opportunitiesWireless Communications, IEEE2013206919810.1109/MWC.2013.6704479 – reference: ChengHJXiongNXVasilakosVANodes organization for channel assignment with topology preservation in multi-radio wireless mesh networksAd Hoc Networks201210576077310.1016/j.adhoc.2011.02.004 – reference: WeiGYLingYGuoBFPrediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman filterComputer Communications201134679380210.1016/j.comcom.2010.10.003 – reference: Al-OmariHWolffFPapachristouCSmoothing delay jitter in networked control systemsJournal of Embedded Computing2009 – reference: Zhang W., He J. S. (2007). Modeling End-to-End Delay Using Pareto Distribution. In Second International Conference on Internet Monitoring and Protection (ICIMP). – reference: XiongNXVasilakosVAYangTLComparative analysis of quality of service and memory usage for adaptive failure detectors in healthcare systemsIEEE Journal on Selected Areas in Communications200927449550910.1109/JSAC.2009.090512 – reference: KhanAMTembineHVasilakosVAGame dynamics and cost of learning in heterogeneous 4G networksIEEE Journal on Selected Areas in Communications201230119821310.1109/JSAC.2012.120118 – reference: Xiang L., Luo J., Vasilakos V. A. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 46–54. – reference: Liberatore V. (2006). Integrated play-back, sensing, and networked control. In Proceedings of IEEE INFOCOM. – reference: Al-Omari H., Wolff F., Papachristou C., et al. (2009). 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| SubjectTerms | Algorithms Analysis Communications Engineering Communications systems Computer Communication Networks Data smoothing Delay Derivatives Electrical Engineering Engineering Euclidean space IT in Business Jitter Linear programming Networks Pareto optimality Random numbers Smoothing Studies System theory Values Wireless networks |
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