A Comprehensive Survey on Resource Management in Internet of Things

• Autorzy: Bhajantri Lokesh B. , S. Gangadharaiah

Identyfikatory

DOI

10.26636/jtit.2020.145220

• Języki publikacji: EN

Abstrakty

EN

Efficient resource management is a challenging task in distributed systems, such as the Internet of Things, fog, edge, and cloud computing. In this work, we present a broad overview of the Internet of Things ecosystem and of the challenges related to managing its resources. We also investigate the need for efficient resource management and the guidelines given/suggested by Standard Development Organizations. Additionally, this paper contains a comprehensive survey of the individual phases of resource management processes, focusing on resource modeling, resource discovery, resource estimation, and resource allocation approaches based on performance parameters or metrics, as well as on architecture types. This paper presents also the architecture of a generic resource management enabler. Furthermore, we present open issues concerning resource management, pointing out the directions of future research related to the Internet of Things.

Słowa kluczowe

EN

Internet of things; resource allocation; resource discovery; resource management

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2020
• Tom: nr 4
• Strony: 27--43
• Opis fizyczny: Bibliogr. 68 poz., rys., tab.

Twórcy

autor

Bhajantri Lokesh B.

• Department of Computer Science and Engineering, Basaveshwar Engineering College (Autonomous), Bagalkot, Karnataka, India

autor

S. Gangadharaiah

• Department of Computer Science, S.R.S.M.N. Government First Grade College, Udupi, Karnataka, India

Bibliografia

• [1] A. Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, „Internet of Things: A survey on enabling technologies, protocols, and applications", IEEE Communi. Surv. Tutor., vol. 17, no. 4, pp. 2347-2376, 2015 (DOI: 10.1109/COMST.2015.2444095).
• [2] M. Burhan, R. A. Rehman, B. Khan, and B. Kim, „IoT elements, layered architectures and security issues: a comprehensive survey", J. of Sensors, vol. 18, no. 9, pp. 2796- 831, 2018 (DOI: 10.3390/s18092796).
• [3] „IoT Reference Model" [Online]. Available: https://www.itu.int/ITU-T/recommendations/rec.aspx?rec=y.2060
• [4] F. Delicato, P. Pires, and T. Batista, Resource Management for Internet of Things. Springer, 2017 (ISBN: 9783319542478).
• [5] Z. Ghanbari, N. J. Navimipour, M. Hosseinzadeh, and A. Darwesh, „Resource allocation mechanisms and approaches on the Internet of Things", J. of Cluster Comput., vol. 22, no. 4, pp. 1253-1282, 2019 (DOI: 0.1007/s10586-019-02910-8).
• [6] A. Botta, W. Donato, V. Persico, and A. Pescape, „Integration of cloud computing and Internet of Things", J. of Fut. Gener. Com. Syst., vol. 56, pp. 684-700, 2016 (DOI: 10.1016/j.future.2015.09.021).
• [7] „ITU Common Functional and Non Functional requirement of IoT" [Online]. Available: https://www.itu.int/rec/T-REC-Y.2066
• [8] M. Glinz, „On non-functional requirements", in Proc. of 15th IEEE Int. Requir. Engin. Conf., Delhi, India, 2007, pp. 21-22 (DOI: 10.1109/RE.2007.45).
• [9] A. N. Lam and O. Haugen, „Applying semantics into service-oriented IoT framework", in Proc. of IEEE 17th Int. Conf. on Indust. Inform. INDIN 2019, Helsinki, Finland, 2019, pp. 206-213 (DOI: 10.1109/INDIN41052.2019.8972295).
• [10] A. Sheth, C. Henson, and S. Sahoo, „Semantic sensor web", IEEE J. on Internet Comput.", vol. 12, no. 4, pp. 1-10, 2008 (DOI: 10.1109/MIC.2008.87).
• [11] P. Barnaghi, M. Presser, and K. Moessner, „Published linked sensor data", in Proc. of Int. Symp. on Collabor. Technol. and Syst., pp. 1-16, 2010, in ISWC 2010, 2010-11-07-2010-11-11, Shanghai, China [Online]. Available: http://epubs.surrey.ac.uk/470673/1/sense2web.pdf
• [12] I. Alam et al., „IoT virtualization: A survey of software definition and function virtualization techniques for Internet of Things", pp. 1-30, 2019 [Online]. Available: https://arxiv.org/pdf/ 1902.10910.pdf
• [13] B. I. Ismail, „Evaluation of docker as edge computing platform", In Proc. of IEEE Int. Conf. on Open Syst., Bandar Melaka, Malaysia, 2015, pp. 130-135 (DOI: 10.1109/ICOS.2015.7377291).
• [14] J. G. Ko et al., „Sensor virtualization module: virtualizing IoT devices on mobile smart phones for effective sensor data management", J. of Distrib. Sensor Netw., vol. 11, no. 3, pp. 1-10, 2015 (DOI: 10.1155/2015/730762).
• [15] B. Billet and V. Issarny, „From task graphs to concrete actions: A new task mapping algorithm for the future Internet of Things", in Proc. of IEEE 11th Int. Conf. on Mob. ad hoc and Sensor Syst., Philadelphia, PA, USA, 2014, pp. 470-478 (DOI: 10.1109/MASS.2014.20).
• [16] V. Angelakis, I. Avgouleas, N. Pappas, E. Fitzgerald, and D. Yuan, „Allocation of Heterogeneous resources of an IoT device to exible services in IoT", J. on IEEE Internet of Things, vol. 3, no. 5, pp. 691-700, 2016 (DOI: 10.1109/JIOT.2016.2535163).
• [17] M. Sharief, O. Kingston, S. Hossam, and O. Kingston, „Resource re-use in wireless sensor networks: realizing a synergetic Internet of Things", J. of Commun., vol. 7, no. 7, pp. 484-493, 2012 (DOI: 10.4304/jcm.7.7.484-493).
• [18] P. Banerjee et al., „Everything as a service: powering the new information economy", J. of Comp., vol. 44, no. 3, pp. 36-43, 2011 (DOI: 10.1109/MC.2011.67).
• [19] W. Wang, S. De, G. Cassar, and K. Moessner, „Knowledge representation in the Internet of Things: semantic modeling and its applications", Automatika J. for Control, Measur., Electron., Comput., vol. 54, no.4, pp. 388-400, 2013 (DOI: 10.7305/automatika.54-4.414).
• [20] J. Soldatos et al., „OpenIoT: open source Internet-of-Things in the cloud", in Interoperability and Open-Source Solutions for the Internet of Things, LNCS, vol. 9001, pp. 13-25. Springer, 2015 (DOI: 10.1007/978-3-319-16546-2 3).
• [21] M. Compton et al., „The SSN Ontology of the W3C Semantic Sensor Network", J. of Web Semant., vol. 17, pp. 25-32, 2012 (DOI: 10.1016/j.websem.2012.05.003).
• [22] S. Nagowah and B. A. Rahimbux, „An overview of semantic interoperability ontologies and frameworks for IoT", in Proc. of IEEE 6th Int. Conf. on Enterpr. Syst. ES 2018, Limassol, Cyprus, 2018, pp. 470-478 (DOI: 10.1109/ES.2018.00020).
• [23] A. Palade, C. Cabrera, G. White, M. A., Razzaque, and S. Clarke, „Middleware for Internet of Things: A quantitative evaluation In small scale", in Proc. of IEEE 18th Int. Symp. on A World of Wirel., Mob. and Multim. Netw. WoWMoM 2017, Macau, China, 2017, pp. 1-6 (DOI: 10.1109/WoWMoM.2017.7974340).
• [24] K. Ogawa, K. Kanai, K. Nakamura, H. Kanemitsu, J. Katto, and H. Nakazato, „IoT device virtualization for efficient resource utilization in smart city IoT platform", in Proc. of IEEE Int. Conf. on Perv. Comput. and Commun. Worksh. PerCom Workshops 2019, Kyoto, Japan, 2019, pp. 419-422 (DOI: 10.1109/PERCOMW.2019.8730806).
• [25] S. K. Datta, R. P. Costa, and C. Bonnet, „Resource discovery in Internet of Things: Current trends and future standardization aspects", in Proc. of IEEE 2nd World Forum on Internet of Things WF-IoT 2015, Milan, Italy, 2015, pp. 542-547 (DOI: 10.1109/WF-IoT.2015.7389112).
• [26] N. Hussain, T. Anees, and AzeemUllah, „Development of a novel approach to search resources in IoT", Int. J. of Adv. Comp. Sci. And Appl., vol. 9, no. 9, pp. 385-398, 2018 (DOI: 10.14569/IJACSA.2018.090949).
• [27] C. Perera and A. V. Vasilakos, „A knowledge-based resource discovery for Internet of Things", J. of Knowledge-Based Syst., vol. 109, pp. 122-136, 2016 (DOI: 10.1016/j.knosys.2016.06.030).
• [28] M. Afrin and R. Mahmud, „Software defined network-based scalable resource discovery for Internet of Things", J. of EAI Endorsed Trans. on Scalable Inform. Syst., vol. 17, no. 14, pp. 1-6, 2017 [Online]. Available: https://eudl.eu/pdf/10.4108/eai.25-9-2017.153149
• [29] P. Krivic, P. Skocir, and M. Kusek, „Agent-based approach for energy-efficient IoT services discovery and management", in Agents and Multi-Agent Systems: Technologies and Applications 2018 Proceedings of the 12th International Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA-18). Springer, 2018, pp. 57-66 (DOI: 10.1007/978-3-319-92031-3 6).
• [30] L. Nunes, J. Estrella, C. Perera, S. Reiff-Marganiec, and A. Delbem, „Multi-criteria IoT resource discovery: a comparative analysis", J. on Software-Practice and Exper., vol. 47, no. 10, pp. 1325-1341, 2016 (DOI: 10.1002/spe.2469).
• [31] K. Khalil, K. Elgazzar, and M. Bayoumi, „A comparative analysis on resource discovery protocols for the Internet of Things", in Proc. of IEEE Global Commun. Conf. GLOBECOM-2018, Abu Dhabi, United Arab Emirates, 2018 (DOI: 10.1109/GLO-COM.2018.8647553).
• [32] M. Aazam, M. St-Hilaire, C. Lung, I. Lambadaris, and E. Huh, „IoT resource estimation challenges and modeling in fog", in Fog Computing in the Internet of Things. Springer, 2018, pp. 17-31 (DOI: 10.1007/978-3-319-57639-8 2).
• [33] M. Aazam and E. N. Huh, „Fog computing micro data center based dynamic resource estimation and pricing model for IoT", in Proc. Of the 29th IEEE Int. Conf. on Adv. Inform. Netw. and Appl., Gwangiu, South Korea, 2015, pp. 687-694 (DOI: 10.1109/AINA.2015.254).
• [34] M. Aazam and E. Huh, „Resource management in media Cloud of Things", in Proc. of IEEE Int. Conf. on Parall. Process. Worksh., Minneapolis, MN, USA, 2014, pp. 361-367 (DOI: 10.1109/ICPPW.2014.54).
• [35] M. Aazam and E. Huh, „Dynamic resource provisioning through fog micro data center", in Proc. of the IEEE Int. Conf. on Perv. Comput. Commun. Worksh. PerCom Workshops 2015, St. Louis, MO, USA, 2015, pp. 105-110 (DOI: 10.1109/PERCOMW.2015.7134002).
• [36] M. Aazam, M. St-Hilaire, C. Lung, and I. Lambadaris, „PRE-Fog: IoT trace based probabilistic resource estimation at fog", in Proc. of the 13th IEEE Ann. Consumer Commun. and Netw. Conf. CCNC 2016, Las Vegas, NV, USA, 2016, pp. 12-17 (DOI: 10.1109/C-CNC.2016.7444724).
• [37] E. Solaiman, R. Ranjan, P. Jayaraman, and K. Mitra, „Monitoring Internet of Things application ecosystems for failure", J. on IEEE IT Profess., vol. 18, no. 5, pp. 1-4, 2016 (DOI: 10.1109/MITP.2016.90).
• [38] X. Liu, Z. Qin, Y. Gao, and J. A. McCann, „Resource allocation In wireless powered IoT networks", IEEE Internet of Things J., vol. 6, no. 3, pp. 4935-4945, 2019 (DOI: 10.1109/JIOT.2019.2895417).
• [39] S. Manakkadu and S. Dutta, „On efficient resource allocation in the Internet of Things environment", in Proc. of 8th Int. Conf. on the Internet of Things, Santa Barbara, CA, USA, 2018, no. 22, pp. 1-5 (DOI: 10.1145/3277593.3277623).
• [40] S. F. Abedin et al., „Resource allocation for ultra-reliable and enhanced mobile broadband IoT applications in fog network", J. on IEEE Trans. on Commun., vol. 67, no. 1, pp. 489-502, 2019 (DOI: 10.1109/TCOMM.2018.2870888).
• [41] C. Tsai and S. Liu, „An effiective IoT service-to-interface assignment algorithm via search economics", J. on IEEE Internet of Things, vol. 5, no. 3, pp. 1708-1718, 2018 (DOI: 10.1109/JIOT.2018.2796310).
• [42] S. Kim, „Asymptotic shapley value based resource allocation scheme for IoT services", J. on Comp. Netw., vol. 100, pp. 55-63, 2016 (DOI: 10.1016/j.comnet.2016.02.021).
• [43] C. Tsai, „SEIRA: An effective algorithm for IoT resource allocation problem", J. on Comp. Commun., vol. 119, pp. 156-166, 2017 (DOI: 10.1016/j.comcom.2017.10.006).
• [44] H. Zhang, Y. Xiao, S. Bu, D. Niyato, F. R. Yu, and Z. Han, „Computing resource allocation in three-tier IoT fog networks: A joint optimization approach combining Stackelberg game and matching", J. on IEEE Internet of Things, vol. 4, no. 5, pp. 1204-1215, 2017 (DOI: 10.1109/JIOT.2017.2688925).
• [45] V. Pilloni and L. Atzori, „Consensus-based resource allocation among objects in the Internet of Things", J. on Annals of Telecommun., vol. 72, pp. 415-429, 2017 (DOI: 10.1007/s12243-017-0583-6).
• [46] A. Nassar and Y. Yilmaz, „Resource allocation in fog RAN for heterogeneous IoT environments based on reinforcement learning", in Proc. of IEEE Int. Conf. on Commun. ICC 2019, Shanghai, China, 2019, pp. 1-6 (DOI: 10.1109/ICC.2019.8761626).
• [47] G. Colistra, V. Pilloni, and L. Atzori, „The problem of task allocation in the Internet of Things and the consensus-based approach", J. of Comp. Netw., vol. 73, pp. 98-111, 2014 (DOI: 10.1016/j.comnet.2014.07.011).
• [48] M. Kim and I. Ko, „An efficient resource allocation approach based on a genetic algorithm for composite services in IoT environments", in Proc. of IEEE Int. Conf. on Web Services, New York, NY, USA, 2015, pp. 543-550 (DOI: 10.1109/ICWS.2015.78).
• [49] H. Lan, H. Song, H. Liu, and G. Y. Zhang, „Heterogeneous-oriented resource allocation method in Internet of Things", J. of Appl. Mechan. and Mater., vol. 427, pp. 2791-2794, 2013 (DOI: 10.4028/www.scienti_c.net/AMM.427-429.2791).
• [50] L. Zheng, L. Kaihua, S. Yuting, and M. Yongtao. „Adaptive resource allocation algorithm for Internet of Things with bandwidth constraint", J. on Trans. of Tianjin Univer., vol. 18, pp. 253-258, 2012 (DOI: 10.1007/s12209-012-1873-8).
• [51] A. Kliem and O. Kao, „The Internet of Things resource management challenge", in Proc. of IEEE Int. Conf. on Data Sci. and Data Intensive Syst., Sydney, Australia, 20115, pp. 483-490 (DOI: 10.1109/DS-DIS.2015.21).
• [52] T. Renner, A. Kliem, and O. Kao, „The device cloud – applying cloud computing concepts to the Internet of Things", in Proc. Of IEEE 11th Int. Conf. on Ubiquit. Intell. and Comput., IEEE 11th Int. Conf. on Autonom. and Trust. Comput. and IEEE 14th Int. Conf. on Scal. Compu. and Commun. and Its Assoc. Worksh., Bali, Indonesia, 2014, pp. 396-401 (DOI: 10.1109/UIC-ATC-ScalCom.2014.106).
• [53] Q. Wang, and S. Chen, „Latency-minimum offloading decision and resource allocation for fog-enabled Internet of Things networks", J. of Trans. on Emerg. Telecommun. Technol., 2020 [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/ett.3880 (DOI: 10.1002/ett.3880).
• [54] X. Liu, Y. Li, X. Zhang, W. Lu, and M. Xiong, „Energy-efficient resource optimization in green cognitive Internet of Things", J. of Mob. and Netw. Appl., 2020 (DOI: 10.1007/s11036-020-01510-w).
• [55] Q. Fan and N. Ansari, „Application aware workload allocation for edge computing-based IoT", J. on IEEE Internet of Things, vol. 5, no. 3, pp. 2146-2153, 2018 (DOI: 10.1109/JIOT.2018.2826006).
• [56] W. Ejaz and M. Ibnkahla, „Multiband spectrum sensing and resource allocation for IoT in cognitive 5G networks", J. of IEEE Internet of Things, vol. 5, no. 1, pp. 150-163, 2018 (DOI: 10.1109/JIOT.2017.2775959).
• [57] A. Rullo, D. Midi, E. Serra, and E. Bertino, „Pareto optimal security resource allocation for Internet of Things", J. on ACM Trans. on Priv. and Secur., vol. 20, no. 4, pp. 1-30, 2017 (DOI: 10.1145/3139293).
• [58] Z. Yu, Y. Gong, S. Gong, and Y. Guo, „Joint task offloading and resource allocation in UAV-enabled mobile edge computing", J. on IEEE Internet of Things, vol. 7, no. 4, pp. 3147-3159, 2020 (DOI: 10.1109/JIOT.2020.2965898).
• [59] Y. Jiao, P. Wang, D. Niyato, and Z. Xiong, „Social welfare maxi mization auction in edge computing resource allocation for mobile blockchain", in Proc. of IEEE Int. Conf. on Commun. ICC 2018, Kansas City, MO, USA, 2018 (DOI: 10.1109/ICC.2018.8422632).
• [60] X. Xu et al., „Dynamic resource allocation for load balancing In fog environment", J. on Wirel. Commun. and Mob. Comput., vol. 2, 2018 (DOI: 10.1155/2018/6421607).
• [61] H. Malik et al., „Radio resource management scheme in NB-IoT systems", J. of IEEE Access, vol. 6, pp. 15051-15064, 2018 (DOI: 10.1109/ACCESS.2018.2812299).
• [62] Z. Dou, G. Si, Y. Lin, and M.Wang, „An adaptive resource allocation model with anti-jamming in IoT network", J. of IEEE Access, vol. 7, pp. 93250-93258, 2019 (DOI: 10.1109/ACCESS.2019.2903207).
• [63] F. Xu, F. Yang, S. Bao, and C. Zhao, „DQN inspired joint computing and caching resource allocation approach for software defined information-centric Internet of Things network", J. of IEEE Access, vol. 7, pp. 61987-61996, 2019 (DOI: 10.1109/ACCESS.2019.2916178).
• [64] FIWARE Open source Platform [Online]. Available: https://www.fiware.org/
• [65] IoTivity Open source Platform [Online]. Available: https://iotivity.org/
• [66] European Special Task Force 505 for IoT standards landscaping and IoT European Large Scale Pilot gap analysis [Online]. Available: https://portal.etsi.org/STF/STFs/STFHomePages/STF505
• [67] Standardization Gaps by The Alliance for Internet of Things Innovation [Online]. Available: https://aioti.eu/aioti-wg03-reports-on-iot-standards/
• [68] European Large Scale Pilot Programme [Online]. Available: https://european-iot-pilots.eu/

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).