Performance Evaluation of Mobile Wi-Fi-based M2M Data Traffic Multiplexing

Transcription

1 Performance Evaluation of Mobile Wi-Fi-based M2M Data Traffic Multiplexing Muhammad Tariq Afridi 1, Safdar Nawaz Khan Marwat 1, Yasir Mehmood 2, Jebran Khan 1, Carmelita Görg 2 1 Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan 2 Communication Networks, University of Bremen, Bremen, Germany ym@comnets.uni-bremen.de

2 Outline Introduction Machine-to-Machine (M2M) traffic Architecture and application areas Mobile Wi-Fi device Data aggregation and multiplexing Simulation results and analysis Conclusion and outlook 2

3 Introduction Rising popularity of M2M devices Driving factors Fall in cost of cellular services Global availability of broadband services Reduced sizes of devices with sensors Improved power and networking capability M2M thriving on driving factors 3

4 Machine-to-Machine Traffic M2M enable machines to communicate with each other Automation of processes resulting in M2M traffic growth 1 1 Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, Technical Report Digital Publication, Cisco Systems Inc., 5 Feb ym@comnets.uni-bremen.de 4

5 Architecture and Applications Architectural elements Devices Area networks Gateway Communication networks Applications Domains Area domain Network domain Application domain Standardization 3GPP 1 ETSI 2 IEEE 3 onem2m Application areas Logistics Smart metering and monitoring Intelligent traffic systems E-healthcare 1 3 rd Generation Partnership Project 2 European Telecommunications Standards Institute 3 Institute of Electrical and Electronics Engineers ym@comnets.uni-bremen.de 5

6 Mobile Wi-Fi Device Mobile Wi-Fi device utilized for connecting devices to LTE-A Mobile Wi-Fi device capable of accessing LTE-A using SIM Mobile Wi-Fi device offers hotspot functionality By utilizing LTE-A as backbone for internet access By providing Wi-Fi access to devices in vicinity Mobile Wi-Fi device consists of Wi-Fi protocol stack towards interface with mobile devices LTE-A protocol stack towards backbone 6

7 Aggregation and Multiplexing Challenges of M2M communication in future mobile networks Nature of M2M traffic a major concern M2M applications usually generate narrowband traffic M2M devices transmit small number of bits after minutes or hours Smallest resource unit that can be allocated to a device is PRB 1 o PRB consists of 12 sub-carriers, each of 15 KHz o PRB can transmit hundreds of bytes of data in favorable channel conditions o Radio spectrum a scarce resource o Allocation of entire PRB to single device can result in spectrum wastage 1 Physical Resource Block ym@comnets.uni-bremen.de 7

8 Aggregation and MUX (cont.) Utilization of wireless inband layer 3 Relay Node (RN) For data traffic aggregation and multiplexing of narrowband applications 1 Aggregated data transmitted to enodeb Inband RN uses same frequency bands for access and backhaul link Time division mechanism for bandwidth sharing required Utilization of mobile Wi-Fi device Aggregation of data packets in mobile Wi-Fi device Algorithm designed to multiplex data packets at GPRS Tunneling Protocol layer of LTE-A side of mobile Wi-Fi Packets aggregated according to Transport Block Size (TBS) Radio uplink resource request from enodeb for group of packets multiplexed for several devices 1 S. N. K. Marwat, Y. Zaki, J. Chen, A. Timm-Giel, and C. Goerg, A Novel Machine-to-Machine Traffic Multiplexing in LTE-A System using Wireless In-band Relaying, 5th International Conference on Mobile Networks and Management, Cork, Ireland, September ym@comnets.uni-bremen.de 8

9 Aggregation and MUX (cont.) Small IP (Internet Protocol) packets of several devices multiplexed into single large packet at GTP layer enodeb would consider this as individual radio resource request Possible to allocate a single PRB to several M2M devices and enhance spectral efficiency significantly ym@comnets.uni-bremen.de 9

10 Simulation Results and Analysis Simulation scenarios of different traffic loads using OPNET Results of M2M data traffic performance without and with mobile Wi-Fi device compared Without multiplexing M2M devices communicate directly with enodeb Location of the mobile Wi-Fi close to enodeb o Corresponds to an MCS of 22 as defined by 3GPP o TBS larger than TBS at far away location Multiplexing of M2M packets into large packets by utilizing information about available TBS Maximum number of PRBs allocated to mobile Wi-Fi device is fixed o Assumption that device is not mobile and has consistent channel conditions Parameters System bandwidth Maximum PRBs for a mobile Wi-Fi device Noise per PRB Noise floor Message size Mean message inter-transmission time Settings 25 PRBs (5 MHz) 5 PRBs dbm 9 db 80 bytes (at GTP) 1 sec (exponential) ym@comnets.uni-bremen.de 10

11 Results and Analysis (cont.) Average PRBs usage with and without multiplexing 11

12 Results and Analysis (cont.) Average packet end-to-end delay 12

13 Results and Analysis (cont.) Average traffic arriving in the cell 13

14 Conclusion and Outlook Scheme for exploiting functionality of mobile Wi-Fi to facilitate M2M communication proposed Based on aggregation and multiplexing of narrowband data traffic Performance of scheme evaluated in terms of o Spectrum usage o Packet end-to end delay Results showed improvement in performance Scheme can be practicable solution for capacity problems Plan to implement innovative and QoS aware architecture To perform several performance evaluations Exhibit the utility of proposed scheme for easy integration of M2M traffic within LTE-A network o Integration to be achieved by ensuring that no degradation experienced by regular LTE-A users o Normal network operations are not hindered in any way QoS guarantee can be provided by adding timer o Packet waiting times in low load cases to be minimized ym@comnets.uni-bremen.de 14

15 Thank you! 15