Protocols for the Dynamic Lines of Collaboration

In this chapter, DLOC is established with mathematical definitions to model network-to-network services. From the client perspective, DLOC provides conflict/error prevention, detection, and recovery services; and from the service team perspective, DLOC determines the dynamic configuration structure of collaborative agents. The three research questions (see Sect. 3.3) are answered by three control mechanisms: (1) Asynchronous collaboration requirement planning is designed for the formation of service team; (2) The nodes with high centrality in the client network are used as the depot for the agents in the service team; (3) Neuroplasticity-inspired protocols are applied to determine the schedule of providing services requested from the client network. Performance metrics are designed to evaluate the efficacy of different control protocols. The experimental platform for DLOC model and control protocols are described in Chap. 5. The experiments and results are detailed in Chap. 6.

[1]  J. Freeman,et al.  Emotional problems of the gifted child. , 1983, Journal of child psychology and psychiatry, and allied disciplines.

[2]  P. Bonacich Factoring and weighting approaches to status scores and clique identification , 1972 .

[3]  Stephen P. Borgatti,et al.  Centrality and network flow , 2005, Soc. Networks.

[4]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[5]  Markus Butz,et al.  A Simple Rule for Dendritic Spine and Axonal Bouton Formation Can Account for Cortical Reorganization after Focal Retinal Lesions , 2013, PLoS Comput. Biol..

[6]  Bartlett W. Mel,et al.  Cortical rewiring and information storage , 2004, Nature.

[7]  Bo Zeng,et al.  Vulnerability Analysis of Power Grids With Line Switching , 2013, IEEE Transactions on Power Systems.

[8]  Seokcheon Lee,et al.  The role of centrality in ambulance dispatching , 2012, Decis. Support Syst..

[9]  M. Newman Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Shimon Y. Nof,et al.  Cooperation Requirements Planning (CRP) for multiprocessors: Optimal assignment and execution planning , 1996, J. Intell. Robotic Syst..

[11]  C. Mani Krishna,et al.  Fault-tolerant scheduling in homogeneous real-time systems , 2014, ACM Comput. Surv..

[12]  L. Freeman Centrality in social networks conceptual clarification , 1978 .

[13]  T. Murphy,et al.  Plasticity during stroke recovery: from synapse to behaviour , 2009, Nature Reviews Neuroscience.

[14]  Salima Benbernou,et al.  A survey on service quality description , 2013, CSUR.

[15]  Martin Mellado,et al.  Review. Technologies for robot grippers in pick and place operations for fresh fruits and vegetables , 2011 .

[16]  Liang Wang,et al.  Dynamic functional reorganization of the motor execution network after stroke. , 2010, Brain : a journal of neurology.

[17]  Dirk Helbing,et al.  Efficient response to cascading disaster spreading. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Gert Sabidussi,et al.  The centrality index of a graph , 1966 .