• DocumentCode
    3356173
  • Title

    A Novel Internet Real-Time Traffic Pattern Detection Technique for Better Pervasive Computing

  • Author

    Lin, Wilfred W K ; Wu, Richard S L ; Wong, Allan K Y ; Dillon, Tharam S.

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ.
  • fYear
    2006
  • fDate
    3-5 Aug. 2006
  • Firstpage
    719
  • Lastpage
    724
  • Abstract
    The Internet follows the power law. For this reason its traffic pattern takes many forms, which change without warning. For example it may change suddenly from LRD (long-range dependence) such as heavy-tailed or self-similar to SRD (short-range dependence) such as Poisson or multifractal. This makes it difficult to run time-critical pervasive applications over the Internet successfully because it is hard to control the response timeliness of the logical TCP (transmission control protocol) channels. The proposed real-time traffic pattern detector (RTPD) technique is generic and detects and identifies LRD and SRD traffic pattern online. If it is implemented as a logical object, then realtime and pervasive applications can use its detected results to self-reconfigure at runtime for better performance that includes shorter service roundtrip time (RTT) and fault tolerance. The RTPD is conceptually the "M3RT + R/S + filtration" combination. The M 3RT (micro mean message response time) tool is the micro implementation of the convergence algorithm (CA), which is an IEPM (Internet end-to-end performance measurement) model with feedback. Alternatively known as the micro CA (MCA), this tool predicts the mean of any waveform quickly and accurately, either on-line or in a postmortem manner with pre-collected traces. A micro IEPM tool operates as an independent object, to be invoked for service anytime and anywhere by message passing. If M3RT is inhibited, then RTPD works with the traditional R/S (rescaled adjusted statistics) estimator, but still detects the LRD and SRD patterns on-line. If M3RT support is activated, then RTPD works with the enhanced R/S or E-R/S. The proposed RTPD technique differs from other post-mortem approaches (e.g. Hill estimator) because it detects and identifies traffic patterns on the fly. Its contribution to Internet-based pervasive applications is significant because its output enables these applications to- reconfigure on the fly and adapt quickly to new operational criteria. The result is better system performance in light of a shorter service roundtrip time (RTT) that makes the client happy
  • Keywords
    Internet; convergence; estimation theory; fault tolerance; feedback; statistics; telecommunication traffic; transport protocols; ubiquitous computing; Internet end-to-end performance measurement; convergence algorithm; fault tolerance; feedback; long-range dependence; pervasive computing; power law; real-time traffic pattern detection; rescaled adjusted statistics estimator; service roundtrip time; short-range dependence; transmission control protocol channels; Detectors; Fault detection; Fault tolerance; Fractals; Internet; Object detection; Pervasive computing; Protocols; Runtime; Time factors; Internet; M3 RT; R/S estimator; RTPD; pervasive; traffic patterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing and Applications, 2006 1st International Symposium on
  • Conference_Location
    Urumqi
  • Print_ISBN
    1-4244-0326-x
  • Electronic_ISBN
    1-4244-0326-x
  • Type

    conf

  • DOI
    10.1109/SPCA.2006.297517
  • Filename
    4079088