Remote Software Update in Trusted Connection of Long Range IoT Networking Integrated With Mobile Edge Cloud

The Internet of Things (IoT) leads to intelligent services by collecting information from tiny sensor devices. In recent years, storage-less sensing devices have been used to implement IoT services. They depend on delivered software from a network server to operate service functions, and IoT services are based on collected user information. Therefore, it is important to maintain trusted connections during software delivery or data transmission. If a network connection is untrustworthy, stable data transmission cannot be achieved. Untrustworthy data connections cause many problems in IoT services. Therefore, this paper proposes a software update method in trusted connection of IoT networking. The proposed method employs a low-power wide area network (LPWAN) as a long-range IoT networking technology and uses a mobile edge cloud to improve computing efficiency in an access network that consists of IoT devices with insufficient resources. In the proposed method, the mobile edge cloud is integrated into a gateway and processes sensing data and remote software updates of LPWAN. IoT devices can receive software functions from the mobile edge cloud. The proposed method analyzes statistical information about connections in an access network and determines the LPWAN trusted connections. Then, software updates can be performed over the trusted connection. Using trusted connections leads to an increased packet delivery rate and reduced transmission energy consumption. The proposed method is compared with currently available systems through computer simulation and the proposed method’s efficiency is validated.

[1]  Min Chen,et al.  Machine-to-Machine Communications: Architectures, Standards and Applications , 2012, KSII Trans. Internet Inf. Syst..

[2]  Peter I. Corke,et al.  A Java compatible virtual machine for wireless sensor nodes , 2008, SenSys '08.

[3]  Jaydip Sen,et al.  Internet of Things - Applications and Challenges in Technology and Standardization , 2011 .

[4]  Gustavo Alonso,et al.  A virtual machine for sensor networks , 2007, EuroSys '07.

[5]  Hayder A. A. Al-Kashoash,et al.  Comparison of 6LoWPAN and LPWAN for the Internet of Things , 2016 .

[6]  Saurabh Bagchi,et al.  Zephyr: efficient incremental reprogramming of sensor nodes using function call indirections and difference computation , 2009 .

[7]  M. H. MacDougall Simulating computer systems: techniques and tools , 1989 .

[8]  George Suciu,et al.  Smart Cities Built on Resilient Cloud Computing and Secure Internet of Things , 2013, 2013 19th International Conference on Control Systems and Computer Science.

[9]  Philip Levis,et al.  Maté: a tiny virtual machine for sensor networks , 2002, ASPLOS X.

[10]  Kishor S. Trivedi Probability and Statistics with Reliability, Queuing, and Computer Science Applications , 1984 .

[11]  Andrea Zanella,et al.  Long-range communications in unlicensed bands: the rising stars in the IoT and smart city scenarios , 2015, IEEE Wireless Communications.

[12]  Thomas H. Clausen,et al.  A Study of LoRa: Long Range & Low Power Networks for the Internet of Things , 2016, Sensors.

[13]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[14]  Gianni A. Di Caro,et al.  A mobility-assisted protocol for supervised learning of link quality estimates in wireless networks , 2012, 2012 International Conference on Computing, Networking and Communications (ICNC).

[15]  David E. Culler,et al.  The dynamic behavior of a data dissemination protocol for network programming at scale , 2004, SenSys '04.

[16]  Dae-Young Kim,et al.  Data Transmission and Network Architecture in Long Range Low Power Sensor Networks for IoT , 2017, Wirel. Pers. Commun..

[17]  Xiong Xiong,et al.  Low power wide area machine-to-machine networks: key techniques and prototype , 2015, IEEE Communications Magazine.

[18]  Bogdan V. Ghita,et al.  Mobile Edge Computing: Requirements for Powerful Mobile Near Real-Time Applications , 2016, INC.

[19]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[20]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[21]  Mani B. Srivastava,et al.  A dynamic operating system for sensor nodes , 2005, MobiSys '05.

[22]  David E. Culler,et al.  Incremental network programming for wireless sensors , 2004, SECON.

[23]  Dae-Young Kim,et al.  Efficient Remote Software Management Method based on Dynamic Address Translation for IoT Software Execution Platform in Wireless Sensor Network , 2016 .

[24]  Michael Till Beck,et al.  Mobile Edge Computing: A Taxonomy , 2014 .

[25]  Ejaz Ahmed,et al.  A survey on mobile edge computing , 2016, 2016 10th International Conference on Intelligent Systems and Control (ISCO).

[26]  Hwee Pink Tan,et al.  Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications , 2014, IEEE Communications Surveys & Tutorials.

[27]  Stephen R. Marsland,et al.  Machine Learning - An Algorithmic Perspective , 2009, Chapman and Hall / CRC machine learning and pattern recognition series.

[28]  Luca Mottola,et al.  FiGaRo: Fine-Grained Software Reconfiguration for Wireless Sensor Networks , 2008, EWSN.

[29]  Seokhoon Kim,et al.  Safe Data Transmission Architecture Based on Cloud for Internet of Things , 2016, Wirel. Pers. Commun..