Bio-Inspired Dynamic Composition and Reconfiguration of Service-Oriented Internetware Systems

Dynamic composition and reconfiguration of service-oriented Internetware systems are of paramount importance as we can not predefine everything during the design time of a software system. Recent biology studies show that the slime mold Physarum polycephalum - a single-cell organism - can form a veined network that explores the available space and connects food sources in the absence of central control mechanisms. Inspired by the formation and behavior of such biological adaptive networks, a new bionic approach is proposed for dynamic service composition and reconfiguration of Internetware systems. Simulation experiments were conducted. The experimental results show that the proposed approach is effective and efficient. It is hoped that this paper will shed new light in Internetware system design and construction.

[1]  T. Ueda,et al.  Interaction between cell shape and contraction pattern in the Physarum plasmodium. , 2000, Biophysical chemistry.

[2]  A. Tero,et al.  A mathematical model for adaptive transport network in path finding by true slime mold. , 2007, Journal of theoretical biology.

[3]  Anne H. H. Ngu,et al.  Declarative composition and peer-to-peer provisioning of dynamic Web services , 2002, Proceedings 18th International Conference on Data Engineering.

[4]  George R. Ribeiro-Justo,et al.  Intelligent Reconfiguration of Dynamic Distributed Components , 2007, Electron. Notes Theor. Comput. Sci..

[5]  A. Tero,et al.  Minimum-risk path finding by an adaptive amoebal network. , 2007, Physical review letters.

[6]  A. Tero,et al.  Rules for Biologically Inspired Adaptive Network Design , 2010, Science.

[7]  Alan Bundy,et al.  Constructing Induction Rules for Deductive Synthesis Proofs , 2006, CLASE.

[8]  Fabio Casati,et al.  Adaptive and Dynamic Service Composition in eFlow , 2000, CAiSE.

[9]  Jin Zhi Some Discussion on the Development of Software Technology , 2002 .

[10]  W. Marwan Amoeba-Inspired Network Design , 2010, Science.

[11]  T. Nakagaki,et al.  Smart network solutions in an amoeboid organism. , 2004, Biophysical chemistry.

[12]  T. Nakagaki,et al.  Intelligence: Maze-solving by an amoeboid organism , 2000, Nature.

[13]  David Z. Zhang,et al.  An agent-based approach for integrating manufacturing operations , 2009 .

[14]  Y. Nishiura,et al.  Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium , 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[15]  M. Matsubara,et al.  ペロブスカイトマンガン酸塩Gd0.55Sr0.45MnO3における超高速光誘導絶縁体‐強磁性体転移 , 2007 .

[16]  Li Man,et al.  Dynamic Composition of Web Services Based on Domain Ontology , 2005 .

[17]  Toshiyuki Nakagaki,et al.  Physarum solver: A biologically inspired method of road-network navigation , 2006 .

[18]  Quan Z. Sheng,et al.  Quality driven web services composition , 2003, WWW '03.

[19]  Boualem Benatallah,et al.  A Petri Net-based Model for Web Service Composition , 2003, ADC.

[20]  Michel Riveill,et al.  Dynamic Reconfiguration of Agent-Based Applications , 1998 .

[21]  Wu Cheng Survey on Web Services Composition Methods , 2008 .

[22]  Toshiyuki Nakagaki,et al.  Flow-network adaptation in Physarum amoebae , 2008, Theory in Biosciences.

[23]  Steven Reece,et al.  Rumours and reputation: evaluating multi-dimensional trust within a decentralised reputation system , 2007, AAMAS '07.

[24]  Anne H. H. Ngu,et al.  QoS-aware middleware for Web services composition , 2004, IEEE Transactions on Software Engineering.