Foundations of Adaptive Networked Societies of Tiny Artefacts
FP7 ICT/FET STREP Project ICT-215270
Project web site http://fronts.cti.gr/
Start-End Dates 02/02/2008 - 31/01/2011
Coordinator Spirakis, Paul (CTI)
Partners
  • Research Academic Computer Technology Institute - Greece (CTI)
  • Braunschweig University of Technology - Germany (TUBS)
  • Universität Paderborn - Germany (UPB)
  • National and Kapodestrian University of Athens - Greece (UoA)
  • Ben-Gurion University of the Negev - Israel (BGU)
  • Università di Roma "La Sapienza" - Italy (UDRLS)
  • Università degli Studi di Salerno - Italy (UNISA)
  • Wroclaw University of Technology - Poland (WROC)
  • Universitat Politecnica de Catalunya - Spain (UPC)
  • University of Geneva - Switzerland (UNIGE)
  • University of Lübeck - Germany (UZL)

 

In the near future, it is reasonable to expect that new types of systems will appear, designed or emerged, of massive scale, expansive and permeating their environment, of very heterogeneous nature, and operating in a constantly changing networked environment. We expect that most such systems will have the form of a large society of networked artifacts that are small, have limited sensing, signal processing, and communication capabilities, and are usually of limited energy. Yet by cooperation, they will be organized in large societies to accomplish tasks that are difficult or beyond the capabilities of todays conventional centralized systems. The scale and nature of these systems requires naturally that they are pervasive and are expected to operate beyond the complete understanding and control of their designers, developers, and users. These systems or societies should have particular ways to achieve an appropriate level of organization and integration that is achieved seamlessly and with appropriate levels of flexibility.

The aim of this project is to establish the foundations of adaptive networked societies of small or tiny heterogeneous artifacts. We indent to develop an understanding of such societies that will enable us to establish their fundamental properties and laws, as well as, their inherent trade-offs. We will approach our goal by working on a usable quantitative theory of networked adaptation based on rigorous and measurable gains. We also indent to apply our models, methods, and results to the scrutiny of large scale simulations and experiments, from which we expect to obtain valuable feedback. The foundational results and the feedback from simulations and experiments will form a unifying framework for adaptive nets of artifacts that hopefully will enable us to come up with a coherent working set of design rules for such systems. In a nutshell, we will work towards a science of adaptive organization of pervasive networks of small or tiny artifacts.

 

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