Abstract
Mobile cloud computing (MCC) has emerged as a significant area of interest due to its ability of facilitating high computing power and massive storage capacity to the mobile users based on the cost-effective scheme of “pay-as-you-go”. Usually, the mobile devices have limited resources such as limited storage, limited computing power, limited battery life, etc. However, MCC provides the facility of using the cloud servers for storing data and executing exhaustive computation to deal with this problem. Internet of Things (IoT) is another promising paradigm of recent time that enables the integration of several technologies and supports networked interconnection of everyday objects equipped with ubiquitous intelligence. A huge amount of sensory data is generated from the large scale IoT networks which need to be stored and processed. In that case cloud computing has come up with the solution that can provide processing and storage on demand. The integration of IoT with MCC gives birth to a new dimension in wireless communication to support a variety of smart applications. This chapter presents an overview of IoT-MCC along with an illustration of the architecture and applications. The power-efficiency i.e. green aspect for IoT-MCC is also highlighted in this chapter. Finally, we highlight the future research directions of IoT- MCC in this chapter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
De, D.: Mobile Cloud Computing: Architectures, Algorithms and Applications. Chapman and Hall/CRC (2019)
Fernando, N., Loke, S.W., Rahayu, W.: Mobile cloud computing: a survey. Futur. Gener. Comput. Syst. 29(1), 84–106 (2013)
Dinh, H.T., Lee, C., Niyato, D., Wang, P.: A survey of mobile cloud computing: architecture, applications, and approaches. Wirel. Commun. Mob. Comput. 13(18), 1587–1611 (2013)
Peng, K., Leung, V., Xu, X., Zheng, L., Wang, J., Huang, Q.: A survey on mobile edge computing: focusing on service adoption and provision. Wirel. Commun. Mob. Comput. 2018 (2018)
Mukherjee, A., De, D., Ghosh, S.K., Buyya, R.: Mobile Edge Computing. Springer (2021). https://doi.org/10.1007/978-3-030-69893-5. eBook ISBN: 978-3-030-69893-5. Hardcover ISBN: 978-3-030-69892-8
Mukherjee, A., Deb, P., De, D., Buyya, R.: IoT-F2N: an energy-efficient architectural model for IoT using Femtolet-based fog network. J. Supercomput. 75(11), 7125–7146 (2019)
Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of Things (IoT): a vision, architectural elements, and future directions. Futur. Gener. Comput. Syst. 29(7), 1645–1660 (2013)
Ghosh, S., Mukherjee, A., Ghosh, S.K., Buyya, R.: Mobi-IoST: mobility-aware cloud-fog-edge-IOT collaborative framework for time-critical applications. IEEE Trans. Netw. Sci. Eng. (2019)
Mukherjee, A., Ghosh, S., Behere, A., Ghosh, S.K., Buyya, R.: Internet of health things (IoHT) for personalized health care using integrated edge-fog-cloud network. J. Ambient. Intell. Humaniz. Comput., 1–17 (2020)
Van Krevelen, D.W.F., Poelman, R.: A survey of augmented reality technologies, applications and limitations. Int. J. Virtual Real. 9(2), 1–20 (2010)
Deb, P., Mukherjee, A., De, D.: A study of densification management using energy efficient femto-cloud based 5g mobile network. Wirel. Pers. Commun. 101(4), 2173–2191 (2018)
De, D., Mukherjee, A.: Femto-cloud based secure and economic distributed diagnosis and home health care system. J. Med. Imaging Health Inform. 5(3), 435–447 (2015)
Psannis, K.E., Xinogalos, S., Sifaleras, A.: Convergence of internet of things and mobile cloud computing. Syst. Sci. Cont. Eng. An Open Access J. 2(1), 476–483 (2014)
Biswas, A.R., Giaffreda, R.: IoT and cloud convergence: opportunities and challenges. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp. 375–376. IEEE (2014, March)
Botta, A., De Donato, W., Persico, V., Pescapé, A.: Integration of cloud computing and internet of things: a survey. Futur. Gener. Comput. Syst. 56, 684–700 (2016)
Hashmi, S.A., Ali, C.F., Zafar, S.: Internet of things and cloud computing-based energy management system for demand side management in smart grid. Int. J. Energy Res. 45(1), 1007–1022 (2021)
Ruan, J., et al.: Agriculture IoT: emerging trends, cooperation networks, and outlook. IEEE Wirel. Commun. 26(6), 56–63 (December 2019). https://doi.org/10.1109/MWC.001.1900096
Ferrag, M.A., Shu, L., Yang, X., Derhab, A., Maglaras, L.: Security and privacy for green IoT-based agriculture: review, blockchain solutions, and challenges. IEEE Access. 8, 32031–32053 (2020)
Kiran, S., Kanumalli, S.S., Krishna, K.V.S.S.R., Chandra, N.: Internet of things integrated smart agriculture for weather predictions and preventive mechanism. Mater. Today Proc. (2021)
Suciu, G., Suciu, V., Martian, A., Craciunescu, R., Vulpe, A., Marcu, I., Halunga, S., Fratu, O.: Big data, internet of things and cloud convergence–an architecture for secure e-health applications. J. Med. Syst. 39(11), 1–8 (2015)
Nandyala, C.S., Kim, H.K.: Green IoT agriculture and healthcare application (GAHA). Int. J. Smart Home. 10(4), 289–300 (2016)
Islam, M.M., Razzaque, M.A., Hassan, M.M., Ismail, W.N., Song, B.: Mobile cloud-based big healthcare data processing in smart cities. IEEE Access. 5, 11887–11899 (2017)
Oueida, S., Kotb, Y., Aloqaily, M., Jararweh, Y., Baker, T.: An edge computing based smart healthcare framework for resource management. Sensors. 18(12), 4307 (2018)
Ijaz, M., Li, G., Lin, L., Cheikhrouhou, O., Hamam, H., Noor, A.: Integration and applications of fog computing and cloud computing based on the internet of things for provision of healthcare services at home. Electronics. 10(9), 1077 (2021)
Jiang, D.: The construction of smart city information system based on the Internet of Things and cloud computing. Comput. Commun. 150, 158–166 (2020)
Kumar, M., Raju, K.S., Kumar, D., Goyal, N., Verma, S., Singh, A.: An efficient framework using visual recognition for IoT based smart city surveillance. Multimed. Tools Appl., 1–19 (2021)
Chen, N., Qiu, T., Zhao, L., Zhou, X., Ning, H.: Edge intelligent networking optimization for internet of things in smart city. IEEE Wirel. Commun. 28(2), 26–31 (2021)
Haseeb, K., Din, I.U., Almogren, A., Ahmed, I., Guizani, M.: Intelligent and secure edge-enabled computing model for sustainable cities using green internet of things. Sustain. Cities Soc. 68, 102779 (2021)
Kumar, K.S., Kumar, T.A., Sundaresan, S., Kumar, V.K.: Green IoT for 9 Sustainable Growth and Energy Management in Smart Cities, p. 155. Handbook of green engineering technologies for sustainable smart cities (2021)
Sarkar, N.I., Gul, S.: Green computing and internet of things for smart cities: technologies, challenges, and implementation. In: Green Computing in Smart Cities: Simulation and Techniques, pp. 35–50. Cham, Springer (2021)
Jokanović, V.: Smart healthcare in smart cities. In: Towards Smart World, pp. 45–72. Chapman and Hall/CRC (2020)
Rajab, H., Cinkelr, T.: IoT based smart cities. In: 2018 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1–4. IEEE (2018, June)
Sundari, V.K., Nithyashri, J., Kuzhaloli, S., Subburaj, J., Vijayakumar, P., Jose, P.S.H.: Comparison analysis of IoT based industrial automation and improvement of different processes–review. Mater. Today Proc. 45, 2595–2598 (2021)
Xenakis, A., Karageorgos, A., Lallas, E., Chis, A.E., González-Vélez, H.: Towards distributed IoT/cloud based fault detection and maintenance in industrial automation. Proc. Comput. Sci. 151, 683–690 (2019)
Shaikh, F.K., Zeadally, S., Exposito, E.: Enabling technologies for green internet of things. IEEE Syst. J. 11(2), 983–994 (2015)
Choudhury, T., Gupta, A., Pradhan, S., Kumar, P., Rathore, Y.S.: Privacy and security of cloud-based internet of things (IoT). In: 2017 3rd International Conference on Computational Intelligence and Networks (CINE), pp. 40–45 (2017). https://doi.org/10.1109/CINE.2017.28
Sahmim, S., Gharsellaoui, H.: Privacy and security in internet-based computing: cloud computing, internet of things, cloud of things: a review. Proc. Comput. Sci. 112, 1516–1522 (2017)
Najafizadeh, A., Salajegheh, A., Rahmani, A.M., Sahafi, A.: Privacy-preserving for the internet of things in multi-objective task scheduling in cloud-fog computing using goal programming approach. Peer-to-Peer Netw. Appl., 1–26 (2021)
Ray, A., De, D.: An energy efficient sensor movement approach using multi-parameter reverse glowworm swarm optimization algorithm in mobile wireless sensor network. Simul. Model. Pract. Theory. 62, 117–136 (2016)
Ray, A., De, D.: Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm for enhanced network lifetime in wireless sensor network. IET Wirel. Sens. Syst. 6(6), 181–191 (2016)
Ray, A., De, D.: Energy efficient clustering algorithm for multi-hop green wireless sensor network using gateway node. Adv. Sci. Eng. Med. 5(11), 1199–1204 (2013)
Raychaudhuri, A., De, D.: Bio-inspired algorithm for multi-objective optimization in wireless sensor network. In: Nature Inspired Computing for Wireless Sensor Networks, pp. 279–301. Singapore, Springer (2020)
Kaur, G., Tomar, P., Singh, P.: Design of cloud-based green IoT architecture for smart cities. In: Internet of Things and Big Data Analytics Toward Next-Generation Intelligence, pp. 315–333. Cham, Springer (2018)
Liu, X., Ansari, N.: Toward green IoT: energy solutions and key challenges. IEEE Commun. Mag. 57(3), 104–110 (2019)
Eteläperä, M., Vecchio, M., Giaffreda, R.: Improving energy efficiency in IoT with re-configurable virtual objects. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp. 520–525. IEEE (2014, March)
Chen, J.I.Z., Lai, K.L.: Machine learning based energy management at Internet of Things network nodes. J. Trends Comput. Sci. Smart Technol. September. 2020(3), 127–133 (2020)
Oma, R., Nakamura, S., Duolikun, D., Enokido, T., Takizawa, M.: An energy-efficient model for fog computing in the internet of things (IoT). Internet of Things. 1, 14–26 (2018)
Azar, J., Makhoul, A., Barhamgi, M., Couturier, R.: An energy efficient IoT data compression approach for edge machine learning. Futur. Gener. Comput. Syst. 96, 168–175 (2019)
Tcarenko, I., Huan, Y., Juhasz, D., Rahmani, A.M., Zou, Z., Westerlund, T., Liljeberg, P., Zheng, L., Tenhunen, H.: Smart energy efficient gateway for internet of mobile things. In: 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), pp. 1016–1017. IEEE (2017, January)
Albreem, M.A., El-Saleh, A.A., Isa, M., Salah, W., Jusoh, M., Azizan, M.M., Ali, A.: Green internet of things (IoT): an overview. In: 2017 IEEE 4th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA), pp. 1–6. IEEE (2017, November)
Pan, J., Jain, R., Paul, S., Vu, T., Saifullah, A., Sha, M.: An internet of things framework for smart energy in buildings: designs, prototype, and experiments. IEEE Internet Things J. 2(6), 527–537 (2015)
Sangoleye, F., Irtija, N., Tsiropoulou, E.E.: Smart energy harvesting for internet of things networks. Sensors. 21(8), 2755 (2021)
Hans, M.R., Tamhane, M.A.: IoT based hybrid green energy driven street lighting system. In: 2020 Fourth International Conference on I-SMAC (IoT in Social, mobile, Analytics and Cloud)(I-SMAC), pp. 35–41. IEEE (2020)
Said, O., Al-Makhadmeh, Z., Tolba, A.M.R.: EMS: an energy management scheme for green IoT environments. IEEE Access. 8, 44983–44998 (2020)
Yau, C.W., Kwok, T.T.O., Lei, C.U., Kwok, Y.K.: Energy harvesting in internet of things. Internet of Everything, 35–79 (2018)
Sanislav, T., Mois, G.D., Zeadally, S., Folea, S.C.: Energy harvesting techniques for internet of things (IoT). IEEE Access. 9, 39530–39549 (2021)
Tahiliani, V., Dizalwar, M.: Green iot systems: an energy efficient perspective. In: 2018 Eleventh International Conference on Contemporary Computing (IC3), pp. 1–6. IEEE (2018, August)
Solanki, A., Nayyar, A.: Green internet of things (G-IoT): ICT technologies, principles, applications, projects, and challenges. In: Handbook of Research on Big Data and the IoT, pp. 379–405. IGI Global (2019)
De, D., Mukherjee, A., Ray, A., Roy, D.G., Mukherjee, S.: Architecture of green sensor mobile cloud computing. IET Wirel. Sens. Syst. 6(4), 109–120 (2016)
Sarkar, S., Debnath, A.: Green IoT: design goals, challenges and energy solutions. In: 2021 6th International Conference on Communication and Electronics Systems (ICCES), pp. 637–642. IEEE (2021, July)
Arshad, R., Zahoor, S., Shah, M.A., Wahid, A., Yu, H.: Green IoT: an investigation on energy saving practices for 2020 and beyond. IEEE Access. 5, 15667–15681 (2017)
Poongodi, T., Ramya, S.R., Suresh, P., Balusamy, B.: Application of IoT in green computing. In: Advances in Greener Energy Technologies, pp. 295–323. Singapore, Springer (2020)
Ray, A., De, D.: Performance evaluation of tree based data aggregation for real time indoor environment monitoring using wireless sensor network. Microsyst. Technol. 23(9), 4307–4318 (2017)
Sharma, N., Panwar, D.: Green IoT: advancements and sustainability with environment by 2050. In: 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 1127–1132. IEEE (2020)
Medhi, K., Mondal, M.A., Hussain, M.I.: An approach to handle heterogeneous healthcare IoT data using deep convolutional neural network. In: Emerging Technologies for Smart Cities, pp. 25–31. Singapore, Springer (2021)
Booij, T.M., Chiscop, I., Meeuwissen, E., Moustafa, N., den Hartog, F.T.: ToN_IoT: The Role of Heterogeneity and the Need for Standardization of Features and Attack Types in IoT Network Intrusion Datasets. IEEE Internet of Things J (2021)
Noura, M., Atiquzzaman, M., Gaedke, M.: Interoperability in internet of things: taxonomies and open challenges. Mob. Netw. Appl. 24(3), 796–809 (2019)
Abbasi, M.A., Memon, Z.A., Durrani, N.M., Haider, W., Laeeq, K., Mallah, G.A.: A multi-layer trust-based middleware framework for handling interoperability issues in heterogeneous IoTs. Clust. Comput., 1–28 (2021)
Ahmad, R., Asim, M.A., Khan, S.Z., Singh, B.: Green IOT—issues and challenges. In: Proceedings of 2nd International Conference on Advanced Computing and Software Engineering (ICACSE) (2019)
Raychaudhuri, A., Mukherjee, A., De, D.: SMEC: sensor mobile edge computing. In: Mobile Edge Computing, pp. 89–110. Springer, Cham (2021)
Tuysuz, M.F., Trestian, R.: From serendipity to sustainable green IoT: technical, industrial and political perspective. Comput. Netw. 182, 107469 (2020)
Abdul-Qawy, A.S.H., Srinivasulu, T.: SEES: a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes. J. Ambient. Intell. Humaniz. Comput. 10(4), 1571–1596 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Raychaudhuri, A., Mukherjee, A., De, D., Gill, S.S. (2022). Green Internet of Things Using Mobile Cloud Computing: Architecture, Applications, and Future Directions. In: De, D., Mukherjee, A., Buyya, R. (eds) Green Mobile Cloud Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-08038-8_11
Download citation
DOI: https://doi.org/10.1007/978-3-031-08038-8_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-08037-1
Online ISBN: 978-3-031-08038-8
eBook Packages: Computer ScienceComputer Science (R0)