In this chapter, we have extended the SSSHS framework with additional organi-zational concepts (namely, organiorgani-zational structure and normative roles) to allow modeling of self-sustainable smart cities with special regard to resource manage-ment, using our LSMAS organizational metamodel that is still under development.
We have described the current state of the LSMAS metamodel and showed its practical applicability in modeling complex multi-agent organizations.
By introducing a hierarchical structure into the SSSHS framework and by defining the role of negotiator, we have shown that it becomes feasible even for large-scale systems like smart cities. Additionally, we have provided an example scenario which aims on better depicting the various interactions that might take place in such a system. In the end, we have discussed the implications of the proposed model, and identified a number of spatiotemporal constraints, namely, feasibility zones, that have to be imposed on the model to become feasible for certain types of resources.
Our future research will focus on further enrichment of the provided models through the introduction of the proposed feasibility zones, as well as large-scale simulations of various scenarios to identify possible additional bottlenecks and problems with the model. Another line of research might be the introduction of learning techniques for smart devices in residential buildings as outlined in [19], through possible inclusion of additional organizational design techniques.
Acknowledgements This work has been supported in full by the Croatian Science Foundation under the project number 8537.
References
1. Ahmed Abbas H (2015) Organization of multi-agent systems: an overview. IJIIS 4:46.https://
doi.org/10.11648/j.ijiis.20150403.11
2. Anvari-Moghaddam A, Guerrero JM, Rahimi-Kian A, Mirian MS (2016) Optimal real-time dispatch for integrated energy systems: an ontology-based multi-agent approach. In: 2016 IEEE 7th international symposium on power electronics for distributed generation systems (PEDG). IEEE, pp 1–7
3. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54:2787– 2805.https://doi.org/10.1016/j.comnet.2010.05.010
4. Ayala I, Amor M, Fuentes L (2012) An agent platform for self-configuring agents in the internet of things. In: Infrastructures and tools for multiagent
5. Bowerman B, Braverman J, Taylor J et al. (2000) The vision of a smart city. In: 2nd international life
6. Corkill DD, Lander SE (1998) Diversity in agent organizations. Object Mag 8:41–47 7. Coutinho LR, Sichman JS, Boissier O (2009) Modeling dimensions for agent organizations.
In: Dignum V (ed) Handbook of research on multi-agent systems: semantics and dynamics of organizational models. IGI Global, pp 18–50
8. De Wolf T (2004) Emergence and self-organization: a statement of similarities and differences. In: Proceedings of the 2nd international workshop on engineering self-organizing applications, pp 96–110
9. Dignum V (2009) Handbook of research on multi-agent systems: semantics and dynamics of organizational models.https://doi.org/10.4018/978-1-60566-256-5
10. Fontana M, Terna P (2015) From agent-based models to network analysis (and return): the policy-making perspective. Working Paper Series 07
11. Hurtado LA, Nguyen PH, Kling WL (2015) Smart grid and smart building inter-operation using agent-based particle swarm optimization. Sustain Energy Grids Netw 2:32–40.https://
doi.org/10.1016/j.segan.2015.03.003
12. Karnouskos S, Holanda TN de (2009) Simulation of a smart grid city with software agents. In:
2009 third UKSim European symposium on computer modeling and simulation. IEEE, pp 424–429
13. Mihaylov M, Razo-Zapata I, Rădulescu R, Jurado S, Avellana N, Nowé A (2016) Smart grid demonstration platform for renewable energy exchange. In: Demazeau Y, Ito T, Bajo J, Escalona MJ (eds) Advances in practical applications of scalable multi-agent systems.
The PAAMS collection. Springer International Publishing, Cham, pp 277–280
14. Okreša Ðurić B (2017) A novel approach to modeling distributed systems: using large-scale multi-agent systems. In: Mahmood Z (ed) Software project management for distributed computing. Springer International Publishing, Cham, pp 229–254
15. Okreša Đurić B (2016) Organizational metamodel for large-scale multi-agent systems. In: de la Prieta F, Escalona MJ, Corchuelo R, Mathieu P, Vale Z, Campbell AT, Rossi S, Adam E, Jiménez-López MD, Navarro EM, Moreno MN (eds) Trends in practical applications of scalable multi-agent systems, the PAAMS collection. Springer International Publishing, Cham, pp 387–390
16. Roscia M, Longo M, Lazaroiu GC (2013) Smart City by multi-agent systems. In: 2013 international conference on renewable energy research and applications (ICRERA). IEEE, pp 371–376
17. Schatten M (2012) Active graph rewriting rules for modeling multi-agent organizational dynamics. In: 1st international internet & business conference
18. Schatten M (2014) Organizational architectures for large-scale multi-agent systems’ development: an initial ontology. In: Omatu S, Bersini H, Corchado JM, Rodríguez S, Pawlewski P, Bucciarelli E (eds) Distributed computing and artificial intelligence. 11th international conference. Springer International Publishing, Cham, pp 261–268
19. Schatten M (2014) Smart residential buildings as learning agent organizations in the internet of things. Bus Syst Res J.https://doi.org/10.2478/bsrj-2014-0003
20. Schatten M, Grd P, Konecki M, Kudelić R (2014) Towards a formal conceptualization of organizational design techniques for large scale multi agent systems. Proc Technol 15:576– 585.https://doi.org/10.1016/j.protcy.2014.09.018
21. Schatten M,Ševa J, Tomičić I (2016) A roadmap for scalable agent organizations in the internet of everything. J Syst Softw 115:31–41.https://doi.org/10.1016/j.jss.2016.01.022 22. Stavropoulos TG, Rigas ES, Kontopoulos E, Bassiliades N, Vlahavas I (2014) A multi-agent
coordination framework for smart building energy management. In: 2014 25th international workshop on database and expert systems applications. IEEE, pp 126–130
23. Tomičić I (2016) Agent-based framework for modeling and simulation of resource management in smart self-sustainable human settlements. Doctoral dissertation
24. Tomicic I, Schatten M (2016) A case study on renewable energy management in an eco-village community in Croatia–an agent based approach. Int J Renew Energy Res (IJRER) 6:1307–1317
25. Tomičic I, Schatten M (2015) Towards an agent based framework for modeling smart self-sustainable systems. Interdisc Description Complex Syst 13:57–70
26. Tomičić I, Schatten M (2016) Agent-based framework for modeling and simulation of resources in self-sustainable human settlements: a case study on water management in an eco-village community in Croatia. Int J Sustain Dev World Ecol 23:504–513.https://doi.org/
10.1080/13504509.2016.1153527
27. Vlacheas P, Giaffreda R, Stavroulaki V, Kelaidonis D, Foteinos V, Poulios G, Demestichas P, Somov A, Biswas A, Moessner K (2013) Enabling smart cities through a cognitive management framework for the internet of things. IEEE Commun Mag 51:102–111.https://
doi.org/10.1109/MCOM.2013.6525602
28. Weyns D, Haesevoets R, Helleboogh A (2010) The MACODO organization model for context-driven dynamic agent organizations. ACM Trans Auton Adapt Syst 5:1–29.https://
doi.org/10.1145/1867713.1867717
29. Yang K, Cho S-B (2016) Towards sustainable smart homes by a hierarchical hybrid architecture of an intelligent agent. Sustainability 8:1020.https://doi.org/10.3390/su8101020
Cybersecurity System: An Essential Pillar of Smart Cities
Lata Nautiyal, Preeti Malik and Amit Agarwal
Abstract From smartphones to smart cities, the world has changed in nearly every aspect. Modern cities are seen as a collection of certain important components and entail dimensions such as the quality of life and socioeconomic developments. Smart cities are an attempt to develop cities that are well-organized, maintainable, secure, technology-driven, and a convenient place to live. In this context, smart cities also encounter a number of challenges especially with regard to legal complications, environment, and other regulatory matters that underpin the policy prospects. There are a number of crucial factors that are vital for the development and management of smart cities. These factors have been used to craft a framework that imparts a more upgraded idea of the smart city initiatives. The relevant pillars or factors refer to social, management, economy, and legal dimensions. Additionally, the technologies and smart devices used in smart cities that capture all manner of data raise the questions of security and privacy. Confidentiality can be endangered and ruptured by a large number of practices which are generally treated as intolerable; however, these are part of operations in a smart city ecosystem. This chapter discusses the security issues in great detail and also provides some solutions to security in smart cities.
Keywords Smart city
ICT-Driven cityDigital city Intelligent city CybersecurityTechnological factors Security of smart city