Analytical Modelling and Performability Evaluation of LTE as Dominant Connectivity Technology for Internet of Things

The future network standards, Long Term Evolution (LTE), has been designed to operate at high speeds for wireless and mobile communication. The exact time at which LTE becomes the dominant connectivity technology in the Internet of Things (IoT) is not certain, however it is clear that's where the world of communications is headed and the time is approachingquickly as for both IoT and LTE adaptations are growing rapidly. In many practical systems, failures are expected and they have a significant effect on the system's performance. The wireless and mobile systems are prone to failures and such systems do not have a simple product form solution. This is because of the irregularities caused by the wireless channel failures. The study of such systems is important because system failures and repairs can affect the QoS measurements of the systems significantly. In this paper, mobile wireless channels of LTE based cellular networks are analysed using queueing theory. The characteristics of wireless channel are considered in abstract level as well as channel unavailability. The model is based on previous work in performance modelling and availability modelling of such systems. Markov Reward Model (MRM) method is used to obtain various QoS measures. The results explicitly show that failures and repairs affect the system performance significantly.

[1]  Olga Galinina,et al.  Impact of machine-type communications on energy and delay performance of random access channel in LTE-advanced , 2013, Trans. Emerg. Telecommun. Technol..

[2]  Jun Zheng,et al.  Modeling and Performance Analysis of Periodic Broadcast in Vehicular Ad Hoc Networks , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[3]  Jiao Wang,et al.  Performance evaluation of a real long term evolution (LTE) network , 2012, 37th Annual IEEE Conference on Local Computer Networks - Workshops.

[4]  Athanasios S. Lioumpas,et al.  Analytical modelling and performance evaluation of realistic time-controlled M2M scheduling over LTE cellular networks , 2013, Trans. Emerg. Telecommun. Technol..

[5]  Yasir Mehmood,et al.  Mobile M2M communication architectures, upcoming challenges, applications, and future directions , 2015, EURASIP Journal on Wireless Communications and Networking.

[6]  Yonal Kirsal,et al.  Performability Modelling of Handoff in Wireless Cellular Networks with Channel Failures and Recovery , 2009, 2009 11th International Conference on Computer Modelling and Simulation.

[7]  Mohamed Kadhem Karray,et al.  A Queueing Theoretic Approach to the Dimensioning of Wireless Cellular Networks Serving Variable-Bit-Rate Calls , 2013, IEEE Transactions on Vehicular Technology.

[8]  George Baravdish,et al.  Analysis of vehicular wireless channel communication via queueing theory model , 2014, 2014 IEEE International Conference on Communications (ICC).

[9]  Bernd E. Wolfinger,et al.  Availability of IPTV services in VANETs using different access network technologies , 2013, 2013 13th International Conference on ITS Telecommunications (ITST).

[10]  Junyu Lai,et al.  Availability evaluation of IPTV services in roadside backbone networks with vehicle-to-infrastructure communication , 2013, 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC).

[11]  M. D. Beaudry,et al.  Performance-Related Reliability Measures for Computing Systems , 1978, IEEE Transactions on Computers.

[12]  Donald F. Towsley,et al.  A mixed queueing network model of mobility in a campus wireless network , 2012, 2012 Proceedings IEEE INFOCOM.

[13]  Enver Ever,et al.  Performability Modelling of Handoff in Wireless Cellular Networks and the Exact Solution of System Models with Service Rates Dependent on Numbers of Originating and Handoff Calls , 2009, 2009 International Conference on Computational Intelligence, Modelling and Simulation.

[14]  Mecit Cetin,et al.  Analytical Evaluation of the Error in Queue Length Estimation at Traffic Signals From Probe Vehicle Data , 2011, IEEE Transactions on Intelligent Transportation Systems.

[15]  M. K. Hasan,et al.  Traffic flow model for vehicular network , 2012, 2012 International Conference on Computer and Communication Engineering (ICCCE).

[16]  Biplab Sikdar,et al.  Queueing Analysis of Polling Based Wireless MAC Protocols with Sleep-Wake Cycles , 2012, IEEE Transactions on Communications.

[17]  John F. Meyer,et al.  On Evaluating the Performability of Degradable Computing Systems , 1980, IEEE Transactions on Computers.

[18]  Jean-François Frigon,et al.  Analysis of cognitive radio networks based on a queueing model with server interruptions , 2011, 2012 IEEE International Conference on Communications (ICC).

[19]  Anthony Ephremides,et al.  Queueing Delay Analysis for Multicast With Random Linear Coding , 2012, IEEE Transactions on Information Theory.