Team for Research in
Ubiquitous Secure Technology

Citation
Joe Hoffert, Douglas Schmidt, Aniruddha Gokhale. "Adapting and Evaluating Distributed Real-time and Embedded Systems in Dynamic Environments". 1st International Workshop on Data Dissemination for Large scale Complex Critical Infrastructures, April, 2010.

Abstract
Quality of Service (QoS)-enabled publish/subscribe (pub/- sub) middleware provides much needed infrastructure for data dissemination in distributed real-time and embedded (DRE) systems. It is hard, however, to quantify the performance of mechanisms that support multiple interrelated QoS concerns, e.g., reliability, latency, and jitter. Moreover, once an appropriate mechanism is selected, it is hard to maintain QoS properties as the operating environment fluctuates since the chosen mechanism might no longer provide the needed QoS. For DRE systems operating in such environments, adjustments to mechanisms supporting QoS must be both timely and resilient to unforeseen environments. This paper describes our work to (1) define composite metrics to evaluate multiple interrelated QoS concerns and (2) analyze various adjustment techniques ( i.e., policy-based approaches, machine learning techniques) used for the QoS mechanisms of a DRE system in a dynamic environment. Our results show that (1) composite metrics quantify the support that mechanisms provide for multiple QoS concerns to ease mechanism evaluation and creation of related composite metrics and (2) neural network machine learning techniques provide the constant-time complexity needed for DRE pub/- sub systems to determine adjustments and the robustness to handle unknown environments.

Electronic downloads

• adamant-dd4lcci.pdf · application/pdf · 212 kbytes

• HTML

  Joe Hoffert, Douglas Schmidt, Aniruddha Gokhale. <a
  href="http://www.truststc.org/pubs/681.html"
  >Adapting and Evaluating Distributed Real-time and
  Embedded Systems in Dynamic Environments</a>, 1st
  International Workshop on Data Dissemination for Large scale
  Complex Critical Infrastructures, April, 2010.

• Plain text

  Joe Hoffert, Douglas Schmidt, Aniruddha Gokhale.
  "Adapting and Evaluating Distributed Real-time and
  Embedded Systems in Dynamic Environments". 1st
  International Workshop on Data Dissemination for Large scale
  Complex Critical Infrastructures, April, 2010.

• BibTeX

  @inproceedings{HoffertSchmidtGokhale10_AdaptingEvaluatingDistributedRealtimeEmbeddedSystems,
      author = {Joe Hoffert and Douglas Schmidt and Aniruddha
                Gokhale},
      title = {Adapting and Evaluating Distributed Real-time and
                Embedded Systems in Dynamic Environments},
      booktitle = {1st International Workshop on Data Dissemination
                for Large scale Complex Critical Infrastructures},
      month = {April},
      year = {2010},
      abstract = {Quality of Service (QoS)-enabled publish/subscribe
                (pub/- sub) middleware provides much needed
                infrastructure for data dissemination in
                distributed real-time and embedded (DRE) systems.
                It is hard, however, to quantify the performance
                of mechanisms that support multiple interrelated
                QoS concerns, e.g., reliability, latency, and
                jitter. Moreover, once an appropriate mechanism is
                selected, it is hard to maintain QoS properties as
                the operating environment fluctuates since the
                chosen mechanism might no longer provide the
                needed QoS. For DRE systems operating in such
                environments, adjustments to mechanisms supporting
                QoS must be both timely and resilient to
                unforeseen environments. This paper describes our
                work to (1) define composite metrics to evaluate
                multiple interrelated QoS concerns and (2) analyze
                various adjustment techniques ( i.e., policy-based
                approaches, machine learning techniques) used for
                the QoS mechanisms of a DRE system in a dynamic
                environment. Our results show that (1) composite
                metrics quantify the support that mechanisms
                provide for multiple QoS concerns to ease
                mechanism evaluation and creation of related
                composite metrics and (2) neural network machine
                learning techniques provide the constant-time
                complexity needed for DRE pub/- sub systems to
                determine adjustments and the robustness to handle
                unknown environments.},
      URL = {http://www.truststc.org/pubs/681.html}
  }
  

Posted by Joe Hoffert on 29 Mar 2010.
Groups: trust
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