This is an open access article published by the IET under the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/3.0/)
Internet of Things (IoT) and cyber-physical systems (CPS) technologies can be applied to many application domains. Examples include intelligent green house, intelligent transportation system, power distribution grid, smart home, smart building, and smart city. Among these application domains, some of them have been extensively studied, e.g., smart home and intelligent transportation systems. In the meantime, smart buildings and smart cities attract researchers and industries to investigate these two use scenarios. Well-designed IoT/CPS can reduce energy consumption, enhance safety in buildings and cities, or can increase the comfortability in the building. In the last few years, the research communities and industrial partners started to study and investigate these two use scenarios to develop prototype or commercial services for these two scenarios. Although many works have been conducted on these two scenarios, many challenges remain open. In this study, the authors study the development and challenges in five topics. They are middleware, computation model, fault tolerance, quality of data, and virtual run-time environment.
References
-
-
1)
-
16. Su, K., Li, J., Fu, H.: ‘Smart city and the applications’. Int. Conf. on Electronics, Communications and Control (ICECC), 2011, September 2011, pp. 1028–1031, .
-
2)
-
23. Reijers, N., Lin, K.J., Wang, Y.C., et al: ‘Design of an intelligent middleware for flexible sensor configuration in M2M systems’. Proc. Second Int. Conf. on Sensor Networks (SENSORNETS), February 2013, pp. 1–6.
-
3)
-
42. Müller, R., Alonso, G., Kossmann, D.: ‘A virtual machine for sensor networks’. Proc. second ACM European Conf. on Computer Systems 2007, EuroSys ‘07, 2007, pp. 145–158.
-
4)
-
19. Heidemann, J., Govindan, R.: ‘Embedded sensor networks’, inHristu-Varsakelis, D., Levine, W.S. (Eds.): ‘Handbook of networked and embedded control systems’ (Springer, 2005), 7656, pp. 721–738.
-
5)
-
10. Google Inc.: ‘Efficiency: How we do it – Data Centers’, .
-
6)
-
12. Kortuem, G., Kawsar, F., Sundramoorthy, V., et al: ‘Smart objects as building blocks for the Internet of things’, IEEE Internet Comput, 2010, 14, (1), pp. 44–51 (doi: 10.1109/MIC.2009.143).
-
7)
-
17. Bowerman, B., Braverman, J., Taylor, J., et al: ‘The vision of a smart city’. Second Int. Life Extension Technology Workshop, Paris, 2000, vol. 28.
-
8)
-
44. Harbaum, T.: ‘NanoVM’, .
-
9)
-
22. Zhang, Y., Gill, C., Lu, C.: ‘Reconfigurable real-time middleware for distributed cyber-physical systems with aperiodic events’. The 28th Int. Conf. on Distributed Computing Systems, 2008, ICDCS ‘08, 2008, pp. 581–588.
-
10)
-
11)
-
40. Levis, P., Gay, D., Culler, D.: ‘Active sensor networks’. NSDI'05 Proc. second Conf. on Symp. on Networked Systems Design & Implementation, 2005, pp. 343–356.
-
12)
-
14. Abbasi, A.A., Younis, Z.: ‘A survey on clustering algorithms for wireless sensor networks’, Comput. Commun., 2007, 30, (1), pp. 2826–2841 (doi: 10.1016/j.comcom.2007.05.024).
-
13)
-
38. Gupta, G., Younis, M.: ‘Fault-tolerant clustering of wireless sensor networks’. Wireless Communications and Networking, 2003, WCNC 2003, 2003, vol. 3, pp. 1579–1584.
-
14)
-
29. Statt, N.: ‘NEST is permanently disabling the Revolv smart home hub’, .
-
15)
-
30. Blackstock, M., Lea, R.: ‘Toward a distributed data flow platform for the web of things (Distributed Node-RED)’. Proc. fifth Int. Workshop on Web of Things. WoT ’14, Cambridge, MA, USA, 2014, pp. 34–39. .
-
16)
-
33. Wang, J., Yonamine, Y., Kodama, E., et al: ‘A distributed approach to constructing k-hop connected dominating set in ad hoc networks’. Int. Conf. on Parallel and Distributed Systems (ICPADS), 2013, 2013, pp. 357–364.
-
17)
-
15. Nam, T., Pardo, T.A.: ‘Conceptualizing smart city with dimensions of technology, people, and institutions’. Proc. 12th Annual Int. Digital Government Research Conf.: Digital Government Innovation in Challenging Times. dg.o ’11, College Park, Maryland, USA, 2011, pp. 282–291. .
-
18)
-
34. Kuhn, F., Moscibroda, T., Wattenhofer, R.: ‘Fault-tolerant clustering in ad hoc and sensor networks’. 26th IEEE Int. Conf. on Distributed Computing Systems (ICDCS'06), 2006, pp. 68–68.
-
19)
-
13. Zanella, A., Bui, N., Castellani, A., et al: ‘Internet of things for smart cities’, IEEE Internet of Things J., 2014, 1, (1), pp. 22–32. .
-
20)
-
21)
-
4. Sha, L., Gopalakrishnan, S., Liu, X., et al: ‘Cyber-physical systems: a new frontier’. Proc. 2008 IEEE Int. Conf. on Sensor Networks, UBIQUITOUS, and Trustworthy Computing, 2008.
-
22)
-
41. Levis, P., Culler, D.: ‘Maté a tiny virtual machine for sensor networks’. The 10th Int. Conf. on Architectural Support for Programming Languages and Operating Systems ASPLOS X, 2002, pp. 85–95.
-
23)
-
3. Sztipanovits, J., Ying, S., Cohen, I., et al: ‘Strategic R&D Opportunities for 21st Century Cyber-Physical Systems – Connecting computation and Information systems with the physical worlds’. , National Institute of Standards and Technology (NIST), Rosement, Illionis, 2013, p. 32, .
-
24)
-
35. Wu, J., Li, H.: ‘On calculating connected dominating set for efficient routing in ad hoc wireless networks’. Proc. Third Int. Workshop on Discrete Algorithms and Methods for Mobile Computing and Communications, 1999, pp. 7–14.
-
25)
-
51. Ellul, J., Martinez, K.: ‘Run-time compilation of bytecode in sensor networks’. SENSORCOMM 2010 Fourth Int. Conf. on Sensor Technologies and Applications, 2010, pp. 133–138.
-
26)
-
6. Park, S.O., Park, J.H., Jeong, Y.S.: ‘An efficient dynamic integration middleware for cyber-physical systems in mobile environments’. Mobile Networks and Applications, 2012, .
-
27)
-
27. Saukh, O., Hasenfratz, D., Thiele, L.: ‘Route selection for mobile sensor nodes on public transport networks’, J. Ambient Intell. Humanized Comput., 2012, 5, (3), pp. 307–321. .
-
28)
-
47. Evers, L.: ‘Concise and flexible programming of wireless sensor networks’, 2010.
-
29)
-
14. Nam, T., Pardo, T.A.: ‘Smart city as urban innovation: focusing on management, policy, and context’. Proc. of the fifth Int. Conf. on Theory and Practice of Electronic Governance. ICEGOV ‘11, Tallinn, Estonia, 2011, pp. 185–194. .
-
30)
-
25. Hasenfratz, D., Saukh, O., Walser, C., et al: ‘Pushing the spatio-temporal resolution limit of urban air pollution maps’. 2014 IEEE Int. Conf. on Pervasive Computing and Communications (PerCom), March 2014, pp. 69–77.
-
31)
-
18. Neirotti, P., De Marco, A., Corinna Cagliano, A., et al: ‘Current trends in smart city initiatives: some stylised facts’, Cities, 2014, 38, pp. 25–36. .
-
32)
-
45. Brouwers, N., Langendoen, K., Corke, P.: ‘Darjeeling, a feature-rich VM for the resource poor’. Seventh ACM Conf. on Embedded Networked Sensor Systems Sensys ‘09, 2009, pp. 169–182.
-
33)
-
26. Slijepcevic, S., Megerian, S., Potkonjak, M.: ‘Location errors in wireless embedded sensor networks’, ACM SIGMOBILE Mob. Comput. Commun. Rev., 2002, 6, (3), p. 67. (doi: 10.1145/581291.581301).
-
34)
-
20. Koushanfar, F., Potkonjak, M., Sangiovanni-Vincentell, A.: ‘Fault tolerance techniques for wireless ad hoc sensor networks’. Proc. of IEEE Sensors, 2002, 2002, vol. 2, pp. 1491–1496.
-
35)
-
5. Liu, J., Shih, C.-S., Chu, E.: ‘Cyber-physical elements of disaster prepared smart environment’. IEEE Computer Magazine, February 2013.
-
36)
-
50. Balani, R., Han, C.-C., Kumar Rengaswamy, R., et al: ‘Multi-level software reconfiguration for sensor networks’. Proc. sixth ACM & IEEE Int. Conf. on Embedded Software. EMSOFT ’06, New York, NY, USA, 2006, pp. 112–121.
-
37)
-
24. Hasenfratz, D., Saukh, O., Walser, C., et al: ‘Deriving high-resolution urban air pollution maps using mobile sensor nodes’, Pervasive Mob. Comput., 2015, 16, (PB), pp. 268–285. (doi: 10.1016/j.pmcj.2014.11.008).
-
38)
-
43. Koshy, J., Pandey, R.: ‘VM*: synthesizing scalable runtime environments for sensor networks’. Third ACM Conf. on Embedded Networked Sensor Systems Sensys ‘05, 2005, pp. 243–254.
-
39)
-
36. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: ‘Energy-efficient communication protocol for wireless microsensor networks’. Proc. 33rd Annual Hawaii Int. Conf. on System sciences, 2000, 2000, p. 10.
-
40)
-
32. Boyinbode, O., Le, H., Takizawa, M.: ‘A survey on clustering algorithms for wireless sensor networks’, Int. J. Space-Based Situated Comput., 2011, 1, (2-3), pp. 130–136 (doi: 10.1504/IJSSC.2011.040339).
-
41)
-
4. Stankovic, J.A.: ‘Research directions for the Internet of things’, IEEE Internet Things J., 2014, 1, (1), pp. 3–9 (doi: 10.1109/JIOT.2014.2312291).
-
42)
-
21. Sugihara, R., Gupta, R.K.: ‘Programming models for sensor networks: a survey’, ACM Trans. Sensor Netw. (TOSN), 2008, 4, (2), p. 8.
-
43)
-
46. Aslam, F., Schindelhauer, C., Ernst, G., et al: ‘Introducing TakaTuka: A Java Virtual machine for Motes’. Sixth ACM Conf. on Embedded Networked Sensor Systems Sensys ‘08, 2008, pp. 399–400.
-
44)
-
7. Evans, D.: ‘The Internet of Things How the Next Evolution of the Internet Is Changing Everything’, .
-
45)
-
49. Hong, K., Park, J., Kim, T., et al: ‘TinyVM, an efficient virtual machine infrastructure for sensor networks’. Seventh ACM Conf. on Embedded Networked Sensor Systems Sensys ‘09, 2009, pp. 399–400.
-
46)
-
31. Khan, M.S., Kim, D.: ‘DIY interface for enhanced service customization of remote IoT devices: a CoAP based prototype’, Int. J. Distrib. Sen. Netw., 2016, 2015, pp. 185:185–185:185. .
-
47)
-
28. Noguero, A., Calvo, I., Almeida, L.: ‘A time-triggered middleware architecture for ubiquitous cyber physical system applications’, Ubiquitous Comput. Ambient Intell., 2012, pp. 73–80 (doi: 10.1007/978-3-642-35377-2_10).
-
48)
-
49)
-
50)
-
39. Ilker Oyman, E., Ersoy, C.: ‘Multiple sink network design problem in large scale wireless sensor networks’. IEEE Int. Conf. on Communications, 2004, 2004, vol. 6, pp. 3663–3667.
-
51)
-
8. Spencer, L.: ‘Internet of Things market to hit $7.1 trillion by 2020’, .
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cps.2016.0025
Related content
content/journals/10.1049/iet-cps.2016.0025
pub_keyword,iet_inspecKeyword,pub_concept
6
6