Dissemination of Reconfiguration Policies on Mesh Networks

Component-based platforms are widely used to develop and deploy distributed pervasive system that exhibit a high degree of dynamicity, concurrency, distribution, heterogeneity, and volatility. This paper deals with the problem of ensuring safe yet efficient dynamic adaptation in a distributed and volatile environment. Most current platforms provide capabilities for dynamic local adaptation to adapt these systems to their evolving execution context, but are still limited in their ability to handle distributed adaptations. Thus, a remaining challenge is to safely propagate reconfiguration policies of component-based systems to ensure consistency of the architecture configuration models over a dynamic and distributed system. In this paper we implement a specific algorithm relying on the models at runtime paradigm to manage platform independent models of the current system architecture and its deployed configuration, and to propagate reconfiguration policies. We evaluate a combination of gossip-based algorithms and vector clock techniques that are able to propagate these policies safely in order to preserve consistency of architecture configuration models among all computation nodes of the system. This evaluation is done with a test-bed system running on a large size grid network.

[1]  Bobby Woolf The Type Object Pattern , 2005 .

[2]  João Leitão,et al.  Gossip-Based Broadcast , 2010 .

[3]  P. S. Almeida,et al.  Interval Tree Clocks : A Logical Clock for Dynamic Systems , 2008 .

[4]  Thierry Coupaye,et al.  The FRACTAL component model and its support in Java , 2006, Softw. Pract. Exp..

[5]  P. S. Almeida,et al.  Interval Tree Clocks , 2008, OPODIS.

[6]  Gordon S. Blair,et al.  Models@ run.time , 2009, Computer.

[7]  Leslie Lamport,et al.  Time, clocks, and the ordering of events in a distributed system , 1978, CACM.

[8]  Rüdiger Schollmeier,et al.  A definition of peer-to-peer networking for the classification of peer-to-peer architectures and applications , 2001, Proceedings First International Conference on Peer-to-Peer Computing.

[9]  Michel Raynal,et al.  Fundamentals of Distributed Computing: A Practical Tour of Vector Clock Systems , 2002, IEEE Distributed Syst. Online.

[10]  Thorsten von Eicken,et al.  技術解説 IEEE Computer , 1999 .

[11]  Brice Morin,et al.  Models@ Run.time to Support Dynamic Adaptation , 2009, Computer.

[12]  Xuemin Shen,et al.  Handbook of Peer-to-Peer Networking , 2009 .

[13]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[14]  Thierry Coupaye,et al.  The FRACTAL component model and its support in Java: Experiences with Auto-adaptive and Reconfigurable Systems , 2006 .

[15]  Anne-Marie Kermarrec,et al.  Epidemic information dissemination in distributed systems , 2004, Computer.

[16]  Gordon S. Blair,et al.  Facilitating Gossip Programming with the GossipKit Framework , 2008, DAIS.

[17]  W. Pkwy The Type Object Pattern , 1997 .

[18]  J. J. Garcia-Luna-Aceves,et al.  A loop-free extended Bellman-Ford routing protocol without bouncing effect , 1989, SIGCOMM 1989.

[19]  Jeff Magee,et al.  FlashMob: distributed adaptive self-assembly , 2011, SEAMS '11.

[20]  Friedemann Mattern,et al.  Virtual Time and Global States of Distributed Systems , 2002 .

[21]  Anne-Marie Kermarrec,et al.  From Epidemics to Distributed Computing , 2004 .

[22]  J. J. Garcia-Luna-Aceves,et al.  A loop-free extended Bellman-Ford routing protocol without bouncing effect , 1989, SIGCOMM '89.

[23]  Colin J. Fidge,et al.  Timestamps in Message-Passing Systems That Preserve the Partial Ordering , 1988 .

[24]  BaldoniRoberto,et al.  Fundamentals of Distributed Computing , 2002 .