AUTHORS: Ivaylo Atanasov, Evelina Pencheva

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ABSTRACT: Machine-to-Machine (M2M) stands for networking of machines and devices that gather information from their environment and share it over the communication network. Devices must be set up and configured correctly, and they need to use available network bearers efficiently. The growth of connected devices makes the device management a challenging task. Reduction in M2M device deployment time and operational costs may be achieved by automation of management processes. In this paper, we propose context-ware models for connectivity management and study aspects of autonomous behaviour in the context of bearer selection procedure based on policies. Connectivity management models are formally described and verified using the concept of weak bi-simulation. The autonomous behaviour which includes monitoring of device connectivity parameters and policy-based bearer selection is modelled and formalized by temporal logic. The validation process is based on a suit of unit tests that allow comparing the expected message exchange traces to the observed ones.

KEYWORDS: Machine-to-Machine communications, Connectivity management, Finite state machines, Formal verification, Weak bi-simulation, Autonomous agent, REST

REFERENCES:

[1] C. Pereira, A. Aguiar, Towards Efficient Mobile M2M Communications: Survey and Open Challenges, Sensors no. 14, 19582- 19608; 2014, pp.19582-19608.

[2] J. Holler, V. Tsiatsis, C. Mulligan, S. Avesand, S. Karnouskos, D. Boyle, IoT Architecture – State of the Art, In edited book From Machineto-Machine to the Internet of Things: Introduction to a New Age, Elsevier, 2014, pp.145-165.

[3] M. Elkhodr, S. Shahrestani, Hon Cheung, The Internet of Things: New Interoperability, Management and Security Challenges, International Journal of Network Security & Its Applications (IJNSA),vol.8, No.2, 2016.

[4] H. Park, H Kim, H Joo, J.S. Song, Recent advancements in the Internet-of-Things related standards: A oneM2M perspective, ICT Express, Special Issue on ICT Convergence in the Internet of Things (IoT), vol.2, issue 3, 2019, pp.126-129.

[5] G. Klas, F. Rodermund, Z. Shelby, S. Akhouri, J. Höller, Lightweight M2M: Enabling Device Management and Applications for the Internet of Things, 2014, Available at: http://archive.ericsson.net/service/internet/pico v/get?DocNo=1/28701-FGB101973.

[6] Open Mobile Alliance, Enabler Test Specification for Lightweight M2M Candidate Version 1.0 – 03 Feb 2015, OMA-ETSLightweightM2M-V1_0-20150203-C

[7] J. Sachs, N. Beijar, P. Elmdahl, J. Melen, F. Militano, P. Salmela, Capillary networks – a smart way to get things connected, Ericsson Review, no. 8, 2014, pp. 2-8.

[8] A. Sehgal, V. Perelman, S. Kuryla, J. Schönwälder. Management of Resource Constrained Devices in the Internet of Things” IEEE Communications Magazine, December 2012, pp.144-149.

[9] Z. Sheng, H. Wang, C. Yin, X. Hu, S. Yang, V. Leung, Lightweight Management of ResourceConstrained Sensor Devices in Internet of Things, Internet of Things Journal, Vol.2, Issue 5, 2015, pp.402-411.

[10] D. Schulz, R. Gitzel, Seamless maintenance - Integration of FDI Device Management & CMMS, IEEE Conference on Emerging Technologies & Factory Automation (ETFA), 2013, pp.402-407.

[11] C. S. Shih. C. T. Chou, K. J. Lin, B. L. Tsai, C. H Lee, D. Cheng, C. J. Chou, Out-of-Box Device Management for Large Scale CyberPhysical Systems, IEEE International Conference on Internet of Things (iThings), and Green Computing and Communications (GreenCom), and Cyber, Physical and Social Computing (CPSCom), 2014, pp.402 – 407.

[12] V. Cackovic, Z. Popovic, Device Connection Platform for M2M communications, IEEE International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2012, pp.1-7.

[13] S. Datta, C. Bonnet, Smart M2M Gateway Based Architecture for M2M Device and Endpoint Management, IEEE International Conference on Internet of Things (iThings), and Green Computing and Communications (GreenCom), and Cyber, Physical and Social Computing (CPSCom), 2014, pp.61-68.

[14] A. A. Corici, R. Shrestha, G. Carella, A. Elmangoush, R. Steinke, T. Magedanz, A solution for provisioning reliable M2M infrastructures using SDN and device management, International Conference on Information and Communication Technology (ICoICT), 2015, pp.81-86.

[15] E. J. Kim, S. Youm, Machine-to-machine platform architecture for horizontal service integration, EURASIP Journal on Wireless Communications and Networking, 2013, doi:10.1186/1687-1499-2013-79, Available at: http://jwcn.eurasipjournals.com/content/2013/1 /79

[16] T. Sakamoto and K. Nimura, 'Dynamic connection management between Web apps and peripheral devices by Web driver,' 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), Sydney, NSW, 2016, pp. 1-6.

[17] D. Kyriazisa, T. Varvarigoua, Smart, autonomous and reliable Internet of Things, International Workshop on Communications and Sensor Networks (ComSense’2013), International Workshop on Communications and Sensor Networks, ComSense’2013, Procedia Computer Science, 2013, pp. 442 – 448.

[18] S. Vassaki, G. Pitsiladis, C. Kourogiorgas, M. Poulakis, A. Panagopoulos, G. Gardikis, S. Costicoglou, Satellite-based sensor networks: M2M sensor communications and connectivity analysis, International Conference on Telecommunications and Multimedia (TEMU), Greece, 2014, pp.132–137.

[19] K. Misura, M. Zagar, Internet of things cloud mediator platform, International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014, pp.1052-1056

[20] M. Ruta, F. Scioscia, G. Loseto, E. Di Sciascio, Semantic-Based Resource Discovery and Orchestration in Home and Building Automation: A Multi-Agent Approach, IEEE Transactions on Industrial Informatics, vol. 10, no. 1, 2014, pp.730-741.

[21] S. Frey, A. Diaconescu, D. Menga1, I. Demeure, Towards a generic architecture and methodology for multi-goal, highly-distributed and dynamic autonomic systems, International Conference on Autonomic Computing (ICAC), 2013, pp.201-212.

[22] Y. Wang, Formal Cognitive Models of Data, Information, Knowledge, and Intelligence, WSEAS Transactions on Computers, 2015, Vol.14, pp.770-781.

[23] G. Cabodi, P. Camurati, C. Loiacono, G. Pipitone, F. Savarese, D. Vendraminetto, Formal Verification of Embedded Systems for Remote Attestation, WSEAS Transactions on Computers, 2015, Vol.14, pp.760-769.

[24] G. D’Angelo, S. Ferretti, V. Ghini, Simulation of the Internet of Things. Proceedings of the IEEE 2016 International Conference on High Performance Computing and Simulation (HPCS 2016)”, pp1-8

[25] Qazi Mamoon Ashraf, Mohamed Hadi Habaebi, Md. Rafiqul Islam, TOPSIS-Based Service Arbitration for Autonomic Internet of Things, IEEE Access, vol.4, 2016, pp.1313- 1320.

[26] L. Fuchun, Z. Qiansheng, C. Xuesong, Bisimilarity control of decentralized nondeterministic discrete-event systems, International Control Conference CCC, 2014, pp.3898-3903.

[27] Open Mobile Alliance (2009). Diagnostics and Monitoring management Object, OMA-TSDiagMonTrapMO-V1_0-20090414-C

[28] Open Mobile Alliance (2013). Diagnostics and Monitoring Trap Events Specifications, 2013, OMA-TS-DiagonTrapEvents-V1_2-20131008- A

[29] ETSI TS 102 690 Machine-to-Machine communications (M2M); Functional architecture. v1.1.1, 2011.

[30] Google Advanced REST client, 2016, Available at: https://chrome.google.com/web store/detail/advanced-rest-client/hgmloofddffdn phfgcellkdfbfbjeloo