Dual-channel medium access control of low power wide area networks considering traffic characteristics in IoE

The Internet of Thing (IoT) is evolving into the Internet of Everything (IoE). Combining cloud computing with the IoE has attracted attention for wide area applications as a major service. In addition, low power wide area networks (LPWANs) have become a remarkable communication technology in IoT. Because the LPWAN provides long range communication with low power, it can be widely exploited for IoE applications. To improve quality of service, data traffic should be transmitted by considering its priority. However, this is not easy because the LPWAN has a low data rate and long transmission delay. Therefore, this paper proposes a dual-channel medium access control (MAC) to satisfy these requirements in the LPWAN. Generated data is classified into three categories by considering traffic characteristics and is delivered with different priority in dual channels. The performance evaluation is carried out with computer simulations. The results show that the proposed scheme outperforms existing schemes in the LPWAN.

[1]  Madhu Sharma Gaur,et al.  Impact of Signal-Strength on Trusted and Secure Clustering in Mobile Pervasive Environment , 2015 .

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

[3]  Liang Dong,et al.  Comparing FCFS & EDF scheduling algorithms for real-time packet switching networks , 2010, 2010 International Conference on Networking, Sensing and Control (ICNSC).

[4]  Nadeem Javaid,et al.  Simulation Analysis of Medium Access Techniques , 2012, 2012 Seventh International Conference on Broadband, Wireless Computing, Communication and Applications.

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

[6]  Deborah Estrin,et al.  Guest Editors' Introduction: Overview of Sensor Networks , 2004, Computer.

[7]  Anuradha Pughat,et al.  A review on stochastic approach for dynamic power management in wireless sensor networks , 2015, Human-centric Computing and Information Sciences.

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

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

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

[11]  Jinsung Cho,et al.  Practical Data Transmission in Cluster-Based Sensor Networks , 2010, KSII Trans. Internet Inf. Syst..

[12]  Bernhard Walke,et al.  IEEE 802 Wireless Systems: Protocols, Multi-Hop Mesh / Relaying, Performance and Spectrum Coexistence , 2007 .

[13]  J.A. Gutierrez,et al.  IEEE 802.15.4: a developing standard for low-power low-cost wireless personal area networks , 2001, IEEE Network.

[14]  Sheldon M. Ross,et al.  Probability Models for Computer Science , 2001 .

[15]  Jinsung Cho,et al.  Transmission Power Control with the Guaranteed Communication Reliability in WSN , 2015, Int. J. Distributed Sens. Networks.

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

[17]  Frank Vahid,et al.  A Survey on Concepts, Applications, and Challenges in Cyber-Physical Systems , 2014, KSII Trans. Internet Inf. Syst..

[18]  Seokhoon Kim,et al.  Safe Data Transmission Architecture Based on Cloud for Internet of Things , 2015, Wireless Personal Communications.

[19]  Runhe Huang,et al.  Design of fusion technique-based mining engine for smart business , 2015, Human-centric Computing and Information Sciences.

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