Locality and globality: Estimations of the encryption collectivities

In this paper we try to define a collectivity, to model and to measure it. Because N. Bourbaki names ”collectivizing relation” the relation defining a set, we name collectivities only the sets selected or built by the help of the relations. The orthogonal interconnections model very well the collectivities. The behavior (structural self-organization) around the origin is different for homogenous and non-homogenous interconnections. How can we measure this behavior? A way is by locality and globality. The locality measures analytically by neighborhoods, neighborhood reserves, Moorereserves and synthetically by diameters, degrees, average distances. The globality is the behavior of an interconnection around a property. The globality vs. symmetry measures by the compactity, efficiency and interconnecting filling. The locality and the globality are among primary manifestations of the self-organization. In this way, collectivities modeled by self-organizing interconnections can contribute to changing our fundamental view of computers by trying to bring them nearer to the nature.

[1]  Stephen P. Boyd,et al.  Future directions in control in an information-rich world , 2003 .

[2]  Hai Zhuge The Future Interconnection Environment , 2005, Computer.

[3]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[4]  Julio Rosenblatt,et al.  DAMN: a distributed architecture for mobile navigation , 1997, J. Exp. Theor. Artif. Intell..

[5]  John Mylopoulos,et al.  Socio-Intentional Architectures for Multi-Agent Systems: the Mobile Robot Control case , 2002, AOIS@CAiSE.

[6]  Claude d. Goudimel Abstract , 1997, Neurobiology of Aging.

[7]  C. Lupu,et al.  Interconnection Locality and Group Locality , 2005, EUROCON 2005 - The International Conference on "Computer as a Tool".

[8]  Alessandro Saffiotti,et al.  The uses of fuzzy logic in autonomous robot navigation , 1997, Soft Comput..

[9]  Joanna J. Bryson,et al.  Intelligence by design: principles of modularity and coordination for engineering complex adaptive agents , 2001 .

[10]  Cristian Lupu,et al.  Cryptography methods using the RSA algorithm , 2005 .

[11]  Joan Colomer,et al.  SUPERVISION OF HETEROGENEOUS CONTROLLERS FOR A MOBILE ROBOT , 2002 .

[12]  Sheldon B. Akers,et al.  A Group-Theoretic Model for Symmetric Interconnection Networks , 1989, IEEE Trans. Computers.

[13]  Kenneth Y. Goldberg,et al.  Collaborative control of robot motion: robustness to error , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[14]  Dídac Busquets,et al.  A Multiagent Approach to Qualitative Landmark-Based Navigation , 2003, Auton. Robots.

[15]  Ramón López de Mántaras,et al.  A CBR System for Autonomous Robot Navigation , 2005, CCIA.