Resource sharing in cyber-physical systems: modelling framework and case studies

Cyber-physical systems (CPSs) have attracted significant research interest because of their promising applications across different domains; nonetheless, how to effectively model CPSs in real applications is still a challenge. In this article, a resource sharing-based framework (RSBF) for CPSs is developed to enable flexible modelling of a wide range of CPSs and systems of CPSs, with specific focus on resource sharing. RSBF combines elements from graph theory and social welfare to describe complex arrangements of overlapping task and resource communities in CPSs, with the objective of maximising CPS utility through decentralised control. The framework implementation is validated through three case studies: scheduling in smart factories, energy distribution in smart grids and information routing in multi-robot systems. Results show that RSBF can successfully represent the dissimilar systems under study. Furthermore, performance analysis on benchmark scheduling problems yields near-optimal results with less computational time, showing the potential of the use of social welfare functions to CPS modelling and control.

[1]  Sangbok Lee,et al.  The role of preparedness in ambulance dispatching , 2011, J. Oper. Res. Soc..

[2]  Soundar R. T. Kumara,et al.  Distributed routing in wireless sensor networks using energy welfare metric , 2010, Inf. Sci..

[3]  Justin M. Bradley,et al.  Toward Continuous State–Space Regulation of Coupled Cyber–Physical Systems , 2012, Proceedings of the IEEE.

[4]  F. Bourguignon On the Measurement of Inequality , 2003 .

[5]  Soundar R. T. Kumara,et al.  Maximum Energy Welfare Routing in Wireless Sensor Networks , 2007, Networking.

[6]  Shimon Y. Nof,et al.  Springer Handbook of Automation , 2009, Handbook of Automation.

[7]  C. Dagum,et al.  On the relationship between income inequality measures and social welfare functions , 1990 .

[8]  Pieter J. Mosterman,et al.  Industry 4.0 as a Cyber-Physical System study , 2016, Software & Systems Modeling.

[9]  Edward A. Lee,et al.  Modeling Cyber–Physical Systems , 2012, Proceedings of the IEEE.

[10]  Seokcheon Lee,et al.  Resource Welfare Based Task Allocation for UAV Team with Resource Constraints , 2015, J. Intell. Robotic Syst..

[11]  Insup Lee,et al.  Cyber-physical systems: The next computing revolution , 2010, Design Automation Conference.

[12]  Min-Hyuk Kim,et al.  Social-welfare based task allocation for multi-robot systems with resource constraints , 2012, Comput. Ind. Eng..

[13]  Aji Gautama Putrada,et al.  Cyber physical system: Paper survey , 2014, 2014 International Conference on ICT For Smart Society (ICISS).

[14]  Shimon Y. Nof,et al.  Dynamic coalition reformation for adaptive demand and capacity sharing , 2014 .

[15]  Soo Dong Kim,et al.  A Service-Based Approach to Designing Cyber Physical Systems , 2010, 2010 IEEE/ACIS 9th International Conference on Computer and Information Science.

[16]  Pu-Tai Yang,et al.  A Distributed Reclustering Hierarchy Routing Protocol Using Social Welfare in Wireless Sensor Networks , 2012, Int. J. Distributed Sens. Networks.

[17]  Ye Ping Zhu,et al.  Research of Crop Production System Based on the CPS Framework , 2014 .

[18]  Xingshe Zhou,et al.  An Implementation towards Integrated Simulation of Cyber-physical Systems , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.

[19]  Edward A. Lee,et al.  A model-based design methodology for cyber-physical systems , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[20]  Sang Won Yoon,et al.  Affiliation/dissociation decision models in demand and capacity sharing collaborative network , 2011 .

[21]  Tony Givargis,et al.  Including variability of physical models into the design automation of cyber-physical systems , 2015, 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[22]  José M. F. Moura,et al.  Modeling of Future Cyber–Physical Energy Systems for Distributed Sensing and Control , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[23]  Sandeep K. S. Gupta,et al.  Special Issue on Cyber-Physical Systems [Scanning the Issue] , 2012, Proc. IEEE.

[24]  D. Plimmer,et al.  Sensing and Control , 1995 .

[25]  Shing Chung Josh Wong Dynamic continuum modeling for urban cities , 2014 .

[26]  Ravi Sethi,et al.  The Complexity of Flowshop and Jobshop Scheduling , 1976, Math. Oper. Res..

[27]  Ying Tan,et al.  Spatio-Temporal Event Model for Cyber-Physical Systems , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems Workshops.

[28]  Lichen Zhang,et al.  A framework to specify big data driven complex cyber physical control systems , 2014, 2014 IEEE International Conference on Information and Automation (ICIA).

[29]  Shimon Y. Nof,et al.  Collaborative capacity sharing among manufacturers on the same supply network horizontal layer for sustainable and balanced returns , 2014 .

[30]  Fatos Xhafa,et al.  Special issue on cyber physical systems , 2013, Computing.

[31]  Ling Wang,et al.  An effective hybrid optimization strategy for job-shop scheduling problems , 2001, Comput. Oper. Res..

[32]  Wayne H. Wolf,et al.  Cyber-physical Systems , 2009, Computer.

[33]  Xingshe Zhou,et al.  An event-based architecture for cyber physical systems , 2014, 2014 4th IEEE International Conference on Information Science and Technology.

[34]  Sang Won Yoon,et al.  Demand and capacity sharing decisions and protocols in a collaborative network of enterprises , 2010, Decis. Support Syst..

[35]  Till Becker,et al.  Dynamics of resource sharing in production networks , 2015 .

[36]  Shimon Y. Nof,et al.  Combined demand and capacity sharing with best matching decisions in enterprise collaboration , 2014 .

[37]  A. Sen,et al.  Choice, Welfare and Measurement , 1982 .

[38]  Manoj Kumar Tiwari,et al.  Multi-objective process planning and scheduling using controlled elitist non-dominated sorting genetic algorithm , 2015 .

[39]  Awais Ahmad,et al.  Smart cyber society: Integration of capillary devices with high usability based on Cyber-Physical System , 2016, Future Gener. Comput. Syst..

[40]  Gabriela Magureanu,et al.  Validation of static properties in unified modeling language models for cyber physical systems , 2013, Journal of Zhejiang University SCIENCE C.

[41]  Rüdiger Klein,et al.  Complex events and actions to control cyber-physical systems , 2011, DEBS '11.

[42]  Ragunathan Rajkumar,et al.  Resource Allocation in Distributed Mixed-Criticality Cyber-Physical Systems , 2010, 2010 IEEE 30th International Conference on Distributed Computing Systems.

[43]  Jan Kleissl,et al.  Cyber-physical energy systems: Focus on smart buildings , 2010, Design Automation Conference.

[44]  Duanfeng Chu,et al.  A method of vehicle motion prediction and collision risk assessment with a simulated vehicular cyber physical system , 2014 .

[45]  Shimon Y. Nof Collaborative control theory for e-Work, e-Production, and e-Service , 2007, Annu. Rev. Control..

[46]  Jing Lin,et al.  Modeling Cyber-Physical Systems with Semantic Agents , 2010, 2010 IEEE 34th Annual Computer Software and Applications Conference Workshops.