Skip to main content
SpringerLink
Log in

Background

  • Chapter
  • First Online:
Book cover Crowdsourcing of Sensor Cloud Services

  • 450 Accesses

Abstract

To the best of our knowledge, there is no similar composition approach in the literature considering spatio-temporal aspects. The strength of the proposed framework is the ability to combine techniques from four separate areas, i.e., sensor cloud, service composition, spatio-temporal crowdsourcing and incentive models. The sensor cloud is a potential key to storing and accessing large-scale sensor data. The concept of services is used as an abstraction that delivers data through the sensor cloud to end-users. In addition, a composition of sensor cloud services creates new value-added functionality to resolve complex sensor cloud service requests. Spatio-temporal features are fundamental to the functional aspect of the sensor cloud. In this regard, we focus on spatio-temporal aspects as key parameters to access sensor cloud services. A credit-based incentive model motivates crowd participation to achieve the desired coverage. In this chapter, we provide an overview of related work in these areas.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Nimbits data logging cloud sever.

    Google Scholar 

  2. Pachube feed cloud service.

    Google Scholar 

  3. Karl Aberer, Manfred Hauswirth, and Ali Salehi. A middleware for fast and flexible sensor network deployment. In Proceedings of the 32nd international conference on Very large data bases, pages 1199–1202. VLDB Endowment, 2006.

    Google Scholar 

  4. Khandakar Ahmed and Mark Gregory. Integrating wireless sensor networks with cloud computing. In 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks (MSN), pages 364–366. IEEE, 2011.

    Google Scholar 

  5. Sarfraz Alam, Mohammad MR Chowdhury, and Josef Noll. Senaas: An event-driven sensor virtualization approach for internet of things cloud. In 2010 IEEE International Conference on Networked Embedded Systems for Enterprise Applications (NESEA), pages 1–6. IEEE, 2010.

    Google Scholar 

  6. Atif Alamri, Wasai Shadab Ansari, Mohammad Mehedi Hassan, M Shamim Hossain, Abdulhameed Alelaiwi, and M Anwar Hossain. A survey on sensor-cloud: architecture, applications, and approaches. International Journal of Distributed Sensor Networks, 9(2):917–923, 2013.

    Article  Google Scholar 

  7. Florian Alt, Alireza Sahami Shirazi, Albrecht Schmidt, Urs Kramer, and Zahid Nawaz. Location-based crowdsourcing: extending crowdsourcing to the real world. In Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries, pages 13–22. ACM, 2010.

    Google Scholar 

  8. Michael Armbrust, Armando Fox, Rean Griffith, Anthony D Joseph, Randy Katz, Andy Konwinski, Gunho Lee, David Patterson, Ariel Rabkin, Ion Stoica, et al. A view of cloud computing. Communications of the ACM, 53(4):50–58, 2010.

    Article  Google Scholar 

  9. John Bethencourt, Amit Sahai, and Brent Waters. Ciphertext-policy attribute-based encryption. In IEEE Symposium on Security and Privacy, pages 321–334. IEEE, 2007.

    Google Scholar 

  10. Sunanda Bose and Nandini Mukherjee. Sensiaas: A sensor-cloud infrastructure with sensor virtualization. In 3rd International Conference on Cyber Security and Cloud Computing (CSCloud), pages 232–239. IEEE, 2016.

    Google Scholar 

  11. Denis Bouyssou, Didier Dubois, Henri Prade, and Marc Pirlot. Decision Making Process: Concepts and Methods. John Wiley & Sons, 2013.

    Google Scholar 

  12. Muhammed Fatih Bulut, Yavuz Selim Yilmaz, and Murat Demirbas. Crowdsourcing location-based queries. In 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pages 513–518. IEEE, 2011.

    Google Scholar 

  13. Jeffrey A Burke, Deborah Estrin, Mark Hansen, Andrew Parker, Nithya Ramanathan, Sasank Reddy, and Mani B Srivastava. Participatory sensing. Center for Embedded Network Sensing, 2006.

    Google Scholar 

  14. Gerardo Canfora, Massimiliano Di Penta, Raffaele Esposito, and Maria Luisa Villani. An approach for QoS-aware service composition based on genetic algorithms. In Proceedings of the 7th annual conference on Genetic and evolutionary computation, pages 1069–1075. ACM, 2005.

    Google Scholar 

  15. Subarna Chatterjee and Sudip Misra. Target tracking using sensor-cloud: Sensor-target mapping in presence of overlapping coverage. IEEE Communications Letters, 18(8):1435–1438, 2014.

    Article  Google Scholar 

  16. Nanxi Chen, Nicolás Cardozo, and Siobhán Clarke. Goal-driven service composition in mobile and pervasive computing. IEEE Transactions on Services Computing, 99, 2016.

    Google Scholar 

  17. Yohan Chon, Nicholas D Lane, Fan Li, Hojung Cha, and Feng Zhao. Automatically characterizing places with opportunistic crowdsensing using smartphones. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pages 481–490. ACM, 2012.

    Google Scholar 

  18. Richard Chow, Philippe Golle, Markus Jakobsson, Elaine Shi, Jessica Staddon, Ryusuke Masuoka, and Jesus Molina. Controlling data in the cloud: outsourcing computation without outsourcing control. In Proceedings of the 2009 ACM workshop on Cloud computing security, pages 85–90. ACM, 2009.

    Google Scholar 

  19. Soon Ae Chun, Vijayalakshmi Atluri, and Nabil R. Adam. Using semantics for policy-based web service composition. Journal of Distributed and Parallel Databases, 18(1):37–64, 2005.

    Article  Google Scholar 

  20. Wen-Yaw Chung, Pei-Shan Yu, and Chao-Jen Huang. Cloud computing system based on wireless sensor network. In 2013 Federated Conference on Computer Science and Information Systems (FedCSIS), pages 877–880. IEEE, 2013.

    Google Scholar 

  21. Sanjit Kumar Dash, Subasish Mohapatra, and Prasant Kumar Pattnaik. A survey on application of wireless sensor network using cloud computing. International Journal of Computer science & Engineering Technologies (E-ISSN: 2044-6004), 1(4):50–55, 2010.

    Google Scholar 

  22. Shuiguang Deng, Longtao Huang, Daning Hu, J Leon Zhao, and Zhaohui Wu. Mobility-enabled service selection for composite services. IEEE Transactions on Services Computing, 9(3):394–407, 2016.

    Article  Google Scholar 

  23. Shuiguang Deng, Longtao Huang, Ying Li, and Jianwei Yin. Deploying data-intensive service composition with a negative selection algorithm. International Journal of Web Services Research (IJWSR), 11(1):76–93, 2014.

    Article  Google Scholar 

  24. Shuiguang Deng, Longtao Huang, Ying Li, Honggeng Zhou, Zhaohui Wu, Xiongfei Cao, Mikhail Yu Kataev, and Ling Li. Toward risk reduction for mobile service composition. IEEE Transactions on Cybernetics, 46(8):1807–1816, 2016.

    Article  Google Scholar 

  25. Shuiguang Deng, Longtao Huang, Javid Taheri, Jianwei Yin, MengChu Zhou, and Albert Y Zomaya. Mobility-aware service composition in mobile communities. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(3):555–568, 2017.

    Article  Google Scholar 

  26. Shuiguang Deng, Longtao Huang, Hongyue Wu, and Zhaohui Wu. Constraints-driven service composition in mobile cloud computing. In 2016 IEEE International Conference on Web Services (ICWS), pages 228–235. IEEE, 2016.

    Google Scholar 

  27. Salvatore Distefano, Giovanni Merlino, and Antonio Puliafito. Sensing and actuation as a service: a new development for clouds. In 11th IEEE International Symposium on Network Computing and Applications (NCA), pages 272–275. IEEE, 2012.

    Google Scholar 

  28. Markus Eisenhauer, Peter Rosengren, and Pablo Antolin. Hydra: A development platform for integrating wireless devices and sensors into ambient intelligence systems. In The Internet of Things, pages 367–373. Springer, 2010.

    Chapter  Google Scholar 

  29. Iria Estevez-Ayres, Pablo Basanta-Val, Marisol García-Valls, Jesús A Fisteus, and Luís Almeida. QoS-aware real-time composition algorithms for service-based applications. IEEE Transactions on Industrial Informatics, 5(3):278–288, 2009.

    Article  Google Scholar 

  30. Patrick Th Eugster, Pascal A Felber, Rachid Guerraoui, and Anne-Marie Kermarrec. The many faces of publish/subscribe. ACM Journal of Computing Surveys (CSUR), 35(2):114–131, 2003.

    Article  Google Scholar 

  31. Hossein Falaki, Ratul Mahajan, Srikanth Kandula, Dimitrios Lymberopoulos, Ramesh Govindan, and Deborah Estrin. Diversity in smartphone usage. In Proceedings of the 8th international conference on Mobile systems, applications, and services, pages 179–194. ACM, 2010.

    Google Scholar 

  32. Brian Ferris, Kari Watkins, and Alan Borning. Onebusaway: results from providing real-time arrival information for public transit. In Proceedings of the Conference on Human Factors in Computing Systems (SIGCHI), pages 1807–1816. ACM, 2010.

    Google Scholar 

  33. Giancarlo Fortino, Mukaddim Pathan, and Giuseppe Di Fatta. Bodycloud: Integration of cloud computing and body sensor networks. In 4th International Conference on Cloud Computing Technology and Science (CloudCom), pages 851–856. IEEE, 2012.

    Google Scholar 

  34. Ian Foster, Yong Zhao, Ioan Raicu, and Shiyong Lu. Cloud computing and grid computing 360-degree compared. In Grid Computing Environments Workshop (GCE’08), pages 1–10. IEEE, 2008.

    Google Scholar 

  35. Drew Fudenberg and Jean Tirole. Game theory, 1991. Cambridge, Massachusetts, 393:12, 1991.

    Google Scholar 

  36. Amir Hossein Gandomi and Amir Hossein Alavi. Krill herd: a new bio-inspired optimization algorithm. In Journal of Communications in Nonlinear Science and Numerical Simulation, 17(12):4831–4845, 2012.

    Article  MathSciNet  Google Scholar 

  37. Nawal Guermouche and Claude Godart. Composition of web services based on timed mediation. International Journal of Next-Generation Computing (IJNGC), 5(1):26p, 2014.

    Google Scholar 

  38. Ikbel Guidara, Nawal Guermouche, Tarak Chaari, Said Tazi, and Mohamed Jmaiel. Pruning based service selection approach under QoS and temporal constraints. In 2014 IEEE International Conference on Web Services (ICWS), pages 9–16. IEEE, 2014.

    Google Scholar 

  39. Mohammad Mehedi Hassan, Biao Song, and Eui-Nam Huh. A framework of sensor-cloud integration opportunities and challenges. In Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication, pages 618–626. ACM, 2009.

    Google Scholar 

  40. Wendi Rabiner Heinzelman, Joanna Kulik, and Hari Balakrishnan. Adaptive protocols for information dissemination in wireless sensor networks. In Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, pages 174–185. ACM, 1999.

    Google Scholar 

  41. Jeff Howe. The rise of crowdsourcing. Wired magazine, 14(6):1–4, 2006.

    Google Scholar 

  42. John Ibbotson, Christopher Gibson, Joel Wright, Peter Waggett, Petros Zerfos, Boleslaw Szymanski, and David J Thornley. Sensors as a service oriented architecture: Middleware for sensor networks. In 2010 Sixth International Conference on Intelligent Environments (IE),, pages 209–214. IEEE, 2010.

    Google Scholar 

  43. George Iosifidis, Lin Gao, Jianwei Huang, and Leandros Tassiulas. Enabling crowd-sourced mobile internet access. In 2014 IEEE International Conference on Computer Communications INFOCOM, pages 451–459. IEEE, 2014.

    Google Scholar 

  44. Luis G Jaimes, Idalides Vergara-Laurens, and Alireza Chakeri. Spread, a crowd sensing incentive mechanism to acquire better representative samples. In 2014 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pages 92–97. IEEE, 2014.

    Google Scholar 

  45. Luis G Jaimes, Idalides Vergara-Laurens, and Miguel A Labrador. A location-based incentive mechanism for participatory sensing systems with budget constraints. In 2012 IEEE International Conference on Pervasive Computing and Communications (PerCom), pages 103–108. IEEE, 2012.

    Google Scholar 

  46. Luis G Jaimes, Idalides J Vergara-Laurens, and Andrew Raij. A survey of incentive techniques for mobile crowd sensing. IEEE Internet of Things Journal, 2(5):370–380, 2015.

    Article  Google Scholar 

  47. Wei Jiang, Tian Wu, Song-Lin Hu, and Zhi-Yong Liu. QoS-aware automatic service composition: A graph view. Journal of Computer Science and Technology, 26(5):837–853, 2011.

    Article  Google Scholar 

  48. Hai Jin, Shadi Ibrahim, Tim Bell, Wei Gao, Dachuan Huang, and Song Wu. Cloud types and services. Handbook of Cloud Computing, pages 335–355, 2010.

    Google Scholar 

  49. David B Johnson and David A Maltz. Dynamic source routing in ad hoc wireless networks. In Mobile computing, pages 153–181. Springer, 1996.

    Google Scholar 

  50. Sanem Kabadayi, Adam Pridgen, and Christine Julien. Virtual sensors: Abstracting data from physical sensors. In Proceedings of the 2006 International Symposium on World of Wireless, Mobile and Multimedia Networks, pages 587–592. IEEE Computer Society, 2006.

    Google Scholar 

  51. Burak Kantarci and Hussein T Mouftah. Sensing services in cloud-centric internet of things: A survey, taxonomy and challenges. In 2015 IEEE International Conference on Communication Workshop (ICCW), pages 1865–1870. IEEE, 2015.

    Google Scholar 

  52. Leyla Kazemi and Cyrus Shahabi. Geocrowd: enabling query answering with spatial crowdsourcing. In Proceedings of the 20th International Conference on Advances in Geographic Information Systems, pages 189–198. ACM, 2012.

    Google Scholar 

  53. Samir Khuller, Anna Moss, and Joseph Seffi Naor. The budgeted maximum coverage problem. Information Processing Letters, 70(1):39–45, 1999.

    Article  MathSciNet  Google Scholar 

  54. Benjamin Klöpper, Fuyuki Ishikawa, and Shinichi Honiden. Service composition with pareto-optimality of time-dependent QoS attributes. In International conference on Service-oriented Computing, pages 635–640. Springer, 2010.

    Google Scholar 

  55. Iordanis Koutsopoulos. Optimal incentive-driven design of participatory sensing systems. In 2013 IEEE International Conference on Computer Communications INFOCOM, pages 1402–1410. IEEE, 2013.

    Google Scholar 

  56. Vijay Krishna. Auction theory. Academic press, 2009.

    Google Scholar 

  57. Ioannis Krontiris and Andreas Albers. Monetary incentives in participatory sensing using multi-attributive auctions. International Journal of Parallel, Emergent and Distributed Systems, 27(4):317–336, 2012.

    Article  Google Scholar 

  58. LP Dinesh Kumar, S Shakena Grace, Akshaya Krishnan, VM Manikandan, R Chinraj, and MR Sumalatha. Data filtering in wireless sensor networks using neural networks for storage in cloud. In 2012 International Conference on Recent Trends In Information Technology (ICRTIT), pages 202–205. IEEE, 2012.

    Google Scholar 

  59. Juong-Sik Lee and Baik Hoh. Dynamic pricing incentive for participatory sensing. Pervasive and Mobile Computing, 6(6):693–708, 2010.

    Article  Google Scholar 

  60. Juong-Sik Lee and Baik Hoh. Sell your experiences: a market mechanism based incentive for participatory sensing. In 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom), pages 60–68. IEEE, 2010.

    Google Scholar 

  61. Kevin Lee and Danny Hughes. System architecture directions for tangible cloud computing. In 2010 First ACIS International Symposium on Cryptography and Network Security, Data Mining and Knowledge Discovery, E-Commerce & Its Applications and Embedded Systems (CDEE), pages 258–262. IEEE, 2010.

    Google Scholar 

  62. Kevin Lee, David Murray, Danny Hughes, and Wouter Joosen. Extending sensor networks into the cloud using amazon web services. In 2010 IEEE International Conference on Networked Embedded Systems for Enterprise Applications (NESEA), pages 1–7. IEEE, 2010.

    Google Scholar 

  63. Ruoshui Liu and Ian J Wassell. Opportunities and challenges of wireless sensor networks using cloud services. In Proceedings of the workshop on Internet of Things and Service Platforms, page 4. ACM, 2011.

    Google Scholar 

  64. Ahmed Lounis, Abdelkrim Hadjidj, Abdelmadjid Bouabdallah, and Yacine Challal. Secure and scalable cloud-based architecture for e-health wireless sensor networks. In 21st International Conference on Computer Communications and Networks (ICCCN), pages 1–7. IEEE, 2012.

    Google Scholar 

  65. Sanjay Madria, Vimal Kumar, and Rashmi Dalvi. Sensor cloud: A cloud of virtual sensors. Journal of IEEE Software, 31(2):70–77, 2014.

    Article  Google Scholar 

  66. Afra J Mashhadi and Licia Capra. Quality control for real-time ubiquitous crowdsourcing. In Proceedings of the 2nd international workshop on Ubiquitous crowdsouring, pages 5–8. ACM, 2011.

    Google Scholar 

  67. Brahim Medjahed, Athman Bouguettaya, and Ahmed K Elmagarmid. Composing web services on the semantic web. The International Journal on Very Large Data Bases (VLDB), 12(4):333–351, 2003.

    Google Scholar 

  68. Peter Mell and Timothy Grance. The NIST definition of cloud computing. NIST special publication, 800:145, 2011.

    Google Scholar 

  69. Diego Mendez and Miguel A Labrador. Density maps: Determining where to sample in participatory sensing systems. In 2012 Third FTRA International Conference on Mobile, Ubiquitous, and Intelligent Computing (MUSIC), pages 35–40. IEEE, 2012.

    Google Scholar 

  70. Sudip Misra, Subarna Chatterjee, and Mohammad S Obaidat. On theoretical modeling of sensor cloud: A paradigm shift from wireless sensor network. IEEE Systems Journal, pages 1–10, 2014.

    Google Scholar 

  71. Sudip Misra, Anuj Singh, Subarna Chatterjee, and Amit Kumar Mandal. QoS-aware sensor allocation for target tracking in sensor-cloud. Ad Hoc Networks, 33:140–153, 2015.

    Article  Google Scholar 

  72. Arber Murturi, Burak Kantarci, and Sema F Oktug. A reference model for crowdsourcing as a service. In 2015 IEEE 4th International Conference on Cloud Networking (CloudNet), pages 64–66. IEEE, 2015.

    Google Scholar 

  73. Roger B Myerson. Optimal auction design. Mathematics of operations research, 6(1):58–73, 1981.

    Article  MathSciNet  Google Scholar 

  74. Nguyen Cao Hong Ngoc, Donghui Lin, Takao Nakaguchi, and Toru Ishida. QoS-aware service composition in mobile environments. In 7th International Conference on Service-Oriented Computing and Applications (SOCA), pages 97–104. IEEE, 2014.

    Google Scholar 

  75. Seog-Chan Oh, Ju-Yeon Lee, Seon-Hwa Cheong, Soo-Min Lim, Min-Woo Kim, Sang-Seok Lee, Jin-Bum Park, Sang-Do Noh, and Mye M Sohn. Wspr*: Web-service planner augmented with a* algorithm. In IEEE Conference on Commerce and Enterprise Computing (CEC’09), pages 515–518. IEEE, 2009.

    Google Scholar 

  76. Michael Papazoglou. Web services: principles and technology. Addison-Wesley, 2008.

    Google Scholar 

  77. Xin Peng, Jingxiao Gu, Tian Huat Tan, Jun Sun, Yijun Yu, Bashar Nuseibeh, and Wenyun Zhao. Crowdservice: Serving the individuals through mobile crowdsourcing and service composition. In 2016 31st IEEE/ACM International Conference on Automated Software Engineering (ASE), pages 214–219. IEEE, 2016.

    Google Scholar 

  78. Charith Perera, Arkady Zaslavsky, Peter Christen, and Dimitrios Georgakopoulos. Sensing as a service model for smart cities supported by internet of things. Transactions on Emerging Telecommunications Technologies, 25(1):81–93, 2014.

    Google Scholar 

  79. V Rajesh, JM Gnanasekar, RS Ponmagal, and P Anbalagan. Integration of wireless sensor network with cloud. In 2010 International Conference on Recent Trends in Information, Telecommunication and Computing (ITC), pages 321–323. IEEE, 2010.

    Google Scholar 

  80. Sasank Reddy, Deborah Estrin, and Mani Srivastava. Recruitment framework for participatory sensing data collections. In International Conference on Pervasive Computing, pages 138–155. Springer, 2010.

    Google Scholar 

  81. Umair Sadiq, Mohan Kumar, Andrea Passarella, and Marco Conti. Service composition in opportunistic networks: A load and mobility aware solution. IEEE Transactions on Computers, 64(8):2308–2322, 2015.

    Article  MathSciNet  Google Scholar 

  82. Xiang Sheng, Jian Tang, Xuejie Xiao, and Guoliang Xue. Sensing as a service: Challenges, solutions and future directions. IEEE Sensors Journal, 13(10):3733–3741, 2013.

    Article  Google Scholar 

  83. Xiang Sheng, Xuejie Xiao, Jian Tang, and Guoliang Xue. Sensing as a service: A cloud computing system for mobile phone sensing. In Sensors 2012, pages 1–4. IEEE, 2012.

    Google Scholar 

  84. Dongyoun Shin, Stefan Müller Arisona, Sofia Georgakopoulou, Gerhard Schmitt, and Sungah Kim. A crowdsourcing urban simulation platform on smartphone technology: Strategies for urban data visualization and transportation mode detection. In Proceedings of the 30th eCAADe Conference, pages 377–384, 2012.

    Google Scholar 

  85. Katarina Stanoevska-Slabeva and Thomas Wozniak. Cloud basics–an introduction to cloud computing. Journal of Grid and Cloud Computing, pages 47–61, 2010.

    Google Scholar 

  86. Aaron Steinfeld, John Zimmerman, Anthony Tomasic, Daisy Yoo, and Rafae Aziz. Mobile transit information from universal design and crowdsourcing. Transportation Research Record: Journal of the Transportation Research Board, (2217):95–102, 2011.

    Google Scholar 

  87. Wen Sun and Chen-Khong Tham. A spatio-temporal incentive scheme with consumer demand awareness for participatory sensing. In 2015 IEEE International Conference on Communications (ICC), pages 6363–6369. IEEE, 2015.

    Google Scholar 

  88. Niwat Thepvilojanapong, Kai Zhang, Tomoya Tsujimori, Yoshikatsu Ohta, Yunlong Zhao, and Yoshito Tobe. Participation-aware incentive for active crowd sensing. In 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), pages 2127–2134. IEEE, 2013.

    Google Scholar 

  89. Wei-Tek Tsai, Xin Sun, and Janaka Balasooriya. Service-oriented cloud computing architecture. In 2010 Seventh International Conference on Information Technology: New Generations (ITNG), pages 684–689. IEEE, 2010.

    Google Scholar 

  90. Peter JM Van Laarhoven and Emile HL Aarts. Simulated annealing. In Simulated Annealing: Theory and Applications, pages 7–15. Springer, 1987.

    Google Scholar 

  91. Florian Wagner, Adrian Klein, Benjamin Klöpper, Fuyuki Ishikawa, and Shinichi Honiden. Multi-objective service composition with time-and input-dependent QoS. In 2012 IEEE 19th International Conference on Web Services (ICWS), pages 234–241. IEEE, 2012.

    Google Scholar 

  92. Hao Wang, Yunlong Zhao, Yang Li, Kai Zhang, Niwat Thepvilojanapong, and Yoshito Tobe. An optimized directional distribution strategy of the incentive mechanism in SenseUtil-based participatory sensing environment. In 2013 IEEE Ninth International Conference on Mobile Ad-hoc and Sensor Networks (MSN), pages 67–71. IEEE, 2013.

    Google Scholar 

  93. Jianping Wang. Exploiting mobility prediction for dependable service composition in wireless mobile ad hoc networks. IEEE Transactions on Services Computing, 4(1):44–55, 2011.

    Article  Google Scholar 

  94. Wei Wang, Kevin Lee, and David Murray. Integrating sensors with the cloud using dynamic proxies. In 23rd International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), pages 1466–1471. IEEE, 2012.

    Google Scholar 

  95. Bin Wu, Shuiguang Deng, Ying Li, Jian Wu, and Jianwei Yin. AWSP: an automatic web service planner based on heuristic state space search. In 2011 IEEE International Conference on Web Services (ICWS), pages 403–410. IEEE, 2011.

    Google Scholar 

  96. Dejun Yang, Guoliang Xue, Xi Fang, and Jian Tang. Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing. In Proceedings of the 18th annual international conference on Mobile computing and networking, pages 173–184. ACM, 2012.

    Google Scholar 

  97. Zhen Ye, Xiaofang Zhou, and Athman Bouguettaya. Genetic algorithm based QoS-aware service compositions in cloud computing. In International Conference on Database Systems for Advanced Applications, pages 321–334. Springer, Berlin, Heidelberg, 2011.

    Google Scholar 

  98. Jennifer Yick, Biswanath Mukherjee, and Dipak Ghosal. Wireless sensor network survey. Journal of Computer Networks, 52(12):2292–2330, 2008.

    Article  Google Scholar 

  99. Madoka Yuriyama and Takayuki Kushida. Sensor-cloud infrastructure-physical sensor management with virtualized sensors on cloud computing. In 2010 13th International Conference on Network-Based Information Systems (NBiS), pages 1–8. IEEE, 2010.

    Google Scholar 

  100. Madoka Yuriyama, Takayuki Kushida, and Mayumi Itakura. A new model of accelerating service innovation with sensor-cloud infrastructure. In 2011 Annual SRII Global Conference, pages 308–314. IEEE, 2011.

    Google Scholar 

  101. Liangzhao Zeng, Boualem Benatallah, Anne H. H. Ngu, Marlon Dumas, Jayant Kalagnanam, and Henry Chang. QoS-aware middleware for web services composition. IEEE Transactions on Software Engineering, 30(5):311–327, 2004.

    Article  Google Scholar 

  102. Qi Zhang, Lu Cheng, and Raouf Boutaba. Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, 1(1):7–18, 2010.

    Article  Google Scholar 

  103. Tao Zhang, JianFeng Ma, Qi Li, Ning Xi, and Cong Sun. Trust-based service composition in multi-domain environments under time constraint. Science China Information Sciences, 57(9):1–16, 2014.

    Google Scholar 

  104. John Zimmerman, Anthony Tomasic, Charles Garrod, Daisy Yoo, Chaya Hiruncharoenvate, Rafae Aziz, Nikhil Ravi Thiruvengadam, Yun Huang, and Aaron Steinfeld. Field trial of tiramisu: crowd-sourcing bus arrival times to spur co-design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1677–1686. ACM, 2011.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Information Technologies, University of School of Information Technologies, NSW, Australia

    Azadeh Ghari Neiat

  2. School of Information Technologies, University of Sydney, NSW, Australia

    Athman Bouguettaya

Authors
  1. Azadeh Ghari Neiat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Athman Bouguettaya
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ghari Neiat, A., Bouguettaya, A. (2018). Background. In: Crowdsourcing of Sensor Cloud Services. Springer, Cham. https://doi.org/10.1007/978-3-319-91536-4_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-91536-4_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91535-7

  • Online ISBN: 978-3-319-91536-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation