Management of adaptation capability of networked systems in dynamic environments

The paper formulates methods to assess the QoS capability of a networked system S under hostile environment conditions incident on S. How good is the system S in meeting the QoS expectations of applications is analyzed in terms of the non-functional attributes of the QoS behavior of S (e.g., transaction latency & drop rate in on-line web services). A self-assessment mechanism programmed in S enables autonomic reconfiguration of the system-internal algorithmic processes & parameters to sustain an optimal behavior of S in the face of changing environment conditions. We employ PO-MDP based modeling tools to benchmark the QoS capability by stress-testing S with artificially injected environment conditions. As case study, we describe the assessment of a CDN (content delivery network) vis-a-vis the algorithmic processes for optimal placement of content caching nodes in a distribution topology to lower the content read latency and overhead experienced by clients.

[1]  Kaliappa Nadar Ravindran,et al.  QoS-Oriented Management of Automobile Cruise Control Processes , 2017, 2017 26th International Conference on Computer Communication and Networks (ICCCN).

[2]  Alba Cristina Magalhaes Alves de Melo,et al.  A WS-Agreement-Based QoS Auditor Negotiation Mechanism for Grids , 2011, 2011 IEEE/ACM 12th International Conference on Grid Computing.

[3]  Randy H. Katz,et al.  Dynamic Replica Placement for Scalable Content Delivery , 2002, IPTPS.

[4]  Carl E. Landwehr,et al.  Basic concepts and taxonomy of dependable and secure computing , 2004, IEEE Transactions on Dependable and Secure Computing.

[5]  Joseph P. Macker,et al.  Group communication for event dissemination in dynamic distributed networks , 2013, 2013 Fifth International Conference on Communication Systems and Networks (COMSNETS).

[6]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[7]  Jemal H. Abawajy,et al.  Determining Service Trustworthiness in Intercloud Computing Environments , 2009, 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks.

[8]  Kaliappa Nadar Ravindran,et al.  Model-based assessment of QoS adaptation in complex networked systems , 2017, 2017 12th System of Systems Engineering Conference (SoSE).

[9]  Steven Drager,et al.  Assessment of QoS adaptation and cyber-defense mechanisms in networked systems , 2017, 2017 IEEE Conference on Dependable and Secure Computing.

[10]  Kaliappa Nadar Ravindran,et al.  Autonomic Management of Replica Voting based Data Collection Systems in Malicious Environments , 2015, Q2SWinet@MSWiM.

[11]  Moonseong Kim,et al.  On Multicasting Steiner Trees for Delay and Delay Variation Constraints , 2006, HPCC.

[12]  Kaliappa Nadar Ravindran,et al.  Model-based techniques for QoS assessment of cloud-hosted CDN services , 2016, 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS).

[13]  Klara Nahrstedt,et al.  A control-based middleware framework for quality-of-service adaptations , 1999, IEEE J. Sel. Areas Commun..

[14]  Steven Drager,et al.  Assessment of QoS adaptation capability of complex network systems , 2016, 2016 12th International Conference on the Design of Reliable Communication Networks (DRCN).