• Previous Article
    A partitioning column approach for solving LED sorter manipulator path planning problems
  • JIMO Home
  • This Issue
  • Next Article
    Time-consistent investment-reinsurance strategy with a defaultable security under ambiguous environment
doi: 10.3934/jimo.2021038

Designing and analysis of a Wi-Fi data offloading strategy catering for the preference of mobile users

1. 

Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai, China

2. 

The Chinese University of Hong Kong(Shenzhen), 2001 Longxiang Boulevard, Longgang District, Shenzhen, China

* Corresponding author: Xiaoyi Zhou

Received  July 2020 Revised  December 2020 Published  March 2021

In recent years, offloading mobile traffic through Wi-Fi has emerged as a potential solution to lower down the communication cost for mobile users. Users hope to reduce the cost while keeping the delay in an acceptable range through Wi-Fi offloading. Also, different users have different sensitivities to the cost and the delay performance. How to make a proper cost-delay tradeoff according to the user's preference is the key issue in the design of the offloading strategy. To address this issue, we propose a preference-oriented offloading strategy for current commercial terminals, which transmit traffic only via one channel simultaneously. We model the strategy as a three-state M/MMSP/1 queueing system, of which the service process is a Markov modulated service process (MMSP), and obtain the structured solutions by establishing a hybrid embedded Markov chain. Our analysis shows that, given the user's preference, there exists an optimal deadline to maximize the utility, which is defined as the linear combination of the cost and the delay. We also provide a method to select the optimal deadline. Our simulation demonstrates that this strategy with the optimal deadline can achieve a good performance.

Citation: Xiaoyi Zhou, Tong Ye, Tony T. Lee. Designing and analysis of a Wi-Fi data offloading strategy catering for the preference of mobile users. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2021038
References:
[1]

Cisco, VNI Mobile Forecast Highlights Tool, 2020. Available from: https://www.cisco.com/c/m/en_us/solutions/service-provider/forecast-highlights-mobile.html. Google Scholar

[2]

Proxim Wireless Corporation, White Paper-Mobile Data Offloading Through Wi-Fi, 2010. Available from: https://www.sourcesecurity.com/docs/moredocs/proximmicrosite/Mobile-Data-Offloading-Through-WiFi-V1.2.pdf. Google Scholar

[3]

Samsung, Samsung Galaxy S10e/S10/S10+ User Manual, 2020. Available from: http://downloadcenter.samsung.com/content/UM/201903/20190305061207197/TMO_SM-G970U_SM-G973U_SM-G975U_EN_UM_P_9.0_022219_FINAL.pdf. Google Scholar

[4]

Umass Trace Repository, Wifi Availability Trace, 2020. Available from: http://traces.cs.umass.edu/index.php/Network/Networkl. Google Scholar

[5]

A. Ajith and T. G. Venkatesh, QoEenhanced mobile data offloading with balking, IEEE Commun. Lett., 21 (2017), 1143-1146.   Google Scholar

[6]

J. G. Andrews, Seven ways that HetNets are a cellular paradigm shift, IEEE Commun. Mag., 51 (2013), 136-144.   Google Scholar

[7]

A. Balasubramanian, R. Mahajan and A. Venkataramani, Augmenting mobile 3G using WiFi, in Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, (2010), 209-222. doi: 10.1145/1814433.1814456.  Google Scholar

[8]

D. Bertsekas and R. Gallager, Data Networks, 2nd Ed., Prentice-Hall, Inc., USA, 1992. Google Scholar

[9]

V. Bychkovsky, B. Hull, A. Miu, H. Balakrishnan and S. Madden, A measurement study of vehicular internet access using in situ Wi-Fi networks, in Proceedings of MobiCom, (2006), 50-61. doi: 10.1145/1161089.1161097.  Google Scholar

[10]

N. Cheng, N. Lu, N. Zhang, X. S. Shen and J. W. Mark, Opportunistic WiFi offloading in vehicular environment: A queueing analysis, in Proceedings of GLOBECOM, (2014), 211-216. Google Scholar

[11]

C. H. FohM. Zukerman and J. W. Tantra, A markovian framework for performance evaluation of ieee 802.11, IEEE Trans. Wireless Commun., 6 (2007), 1276-1265.   Google Scholar

[12]

C. HuaH. YuR. ZhengJ. Li and R. Ni, Online packet dispatching for delay optimal concurrent transmissions in heterogeneous multi-RAT networks, IEEE Trans. Wirel. Commun., 15 (2016), 5076-5086.   Google Scholar

[13]

L. Huang and T. T. Lee, Generalized Pollaczek-Khinchin formula for Markov channels, IEEE Trans. Commun., 61 (2013), 3530-3540.   Google Scholar

[14]

L. Huang and T. T. Lee, Queueing behavior of hybrid ARQ wireless system with finite buffer capacity, in Proceedings of the 21th Annual Wireless and Optical Communications Conference, (2012), 32-36. doi: 10.1109/WOCC.2012.6198142.  Google Scholar

[15]

C. -D. Iskander and P. Takis Mathiopoulos, Analytical level crossing rates and average fade durations for diversity techniques in Nakagami fading channels, IEEE Trans. Commun., 50 (2002), 1301-1309.   Google Scholar

[16]

K. Kawanishi and T. Takine, The M/PH/1+D queue with Markov-renewal service interruptions and its application to delayed mobile data offloading, Perform. Eval., 134 (2019), 102002. doi: 10.1016/j.peva.2019.102002.  Google Scholar

[17]

K. LeeJ. LeeY. YiI. Rhee and S. Chong, Mobile data offloading: How much can WiFi deliver?, IEEE/ACM Trans. Netw., 21 (2013), 536-550.   Google Scholar

[18]

J. LingS. KanugoviS. Vasudevan and A. K. Pramod, Enhanced capacity and coverage by Wi-Fi LTE integration, IEEE Commun. Mag., 53 (2015), 165-171.   Google Scholar

[19]

S. Mahabhashyam and N. Gautam, On queues with Markov modulated service rates, Queueing Syst., 51 (2005), 89-113.  doi: 10.1007/s11134-005-2158-x.  Google Scholar

[20]

F. Mehmeti and T. Spyropoulos, Performance analysis of "on-the-spot" mobile data offloading, in Proceedings of GLOBECOM, (2013), 1577-1583. Google Scholar

[21]

F. Mehmeti and T. Spyropoulos, Performance analysis of mobile data offloading in heterogeneous networks, IEEE Trans. Mob. Comput., 16 (2017), 482-497.   Google Scholar

[22]

F. Mehmeti and T. Spyropoulos, Performance modeling, analysis, and optimization of delayed mobile data offloading for mobile users, IEEE/ACM Trans. Netw., 25 (2017), 550-564.   Google Scholar

[23]

J. F. Shoch and J. A. Hupp, Measured performance of an ethernet local network, ACM Commun., 23 (1980), 711-721.  doi: 10.1145/359038.359044.  Google Scholar

[24]

N. Wang and J. Wu, Opportunistic WiFi offloading in a vehicular environment: Waiting or downloading now?, in Proceedings of INFOCOM, (2016), 1-9. Google Scholar

[25]

R. W. Wolff, Poisson arrivals see time averages, Oper. Res., 30 (1982), 223-231.  doi: 10.1287/opre.30.2.223.  Google Scholar

[26]

C. Zhang, B. Gu, Z. Liu, K. Yamori and Y. Tanaka, A reinforcement learning approach for cost- and energy-aware mobile data offloading, in Proceedings of the 18th Asia-Pacific Network Operations and Management Symposium, (2016), 1-6. Google Scholar

[27]

C. ZhangB. GuZ. LiuK. Yamori and Y. Tanaka, Cost- and energy-aware multi-flow mobile data offloading using Markov decision process, IEICE Trans. Commun., E101.B (2017), 657-666.  doi: 10.1587/transcom.2017NRP0014.  Google Scholar

[28]

D. Zhang and C. K. Yeo, Optimal handing-back point in mobile data offloading, in Proceedings of VNC, (2012), 219-225. Google Scholar

[29]

J. Zhang, Z. Zhou, T. T. Lee and T. Ye, Delay analysis of three-state Markov channels, in Proceedings of 12th International Conference on Queueing Theory and Network Applications, (2017), 101-117. doi: 10.1007/978-3-319-68520-5_7.  Google Scholar

[30]

H. ZhuM. LiL. FuG. XueY. Zhu and L. M. Ni, Impact of traffic influxes: Revealing exponential intercontact time in urban VANETs, IEEE Trans. Parallel Distrib. Syst., 22 (2011), 1258-1266.   Google Scholar

show all references

References:
[1]

Cisco, VNI Mobile Forecast Highlights Tool, 2020. Available from: https://www.cisco.com/c/m/en_us/solutions/service-provider/forecast-highlights-mobile.html. Google Scholar

[2]

Proxim Wireless Corporation, White Paper-Mobile Data Offloading Through Wi-Fi, 2010. Available from: https://www.sourcesecurity.com/docs/moredocs/proximmicrosite/Mobile-Data-Offloading-Through-WiFi-V1.2.pdf. Google Scholar

[3]

Samsung, Samsung Galaxy S10e/S10/S10+ User Manual, 2020. Available from: http://downloadcenter.samsung.com/content/UM/201903/20190305061207197/TMO_SM-G970U_SM-G973U_SM-G975U_EN_UM_P_9.0_022219_FINAL.pdf. Google Scholar

[4]

Umass Trace Repository, Wifi Availability Trace, 2020. Available from: http://traces.cs.umass.edu/index.php/Network/Networkl. Google Scholar

[5]

A. Ajith and T. G. Venkatesh, QoEenhanced mobile data offloading with balking, IEEE Commun. Lett., 21 (2017), 1143-1146.   Google Scholar

[6]

J. G. Andrews, Seven ways that HetNets are a cellular paradigm shift, IEEE Commun. Mag., 51 (2013), 136-144.   Google Scholar

[7]

A. Balasubramanian, R. Mahajan and A. Venkataramani, Augmenting mobile 3G using WiFi, in Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, (2010), 209-222. doi: 10.1145/1814433.1814456.  Google Scholar

[8]

D. Bertsekas and R. Gallager, Data Networks, 2nd Ed., Prentice-Hall, Inc., USA, 1992. Google Scholar

[9]

V. Bychkovsky, B. Hull, A. Miu, H. Balakrishnan and S. Madden, A measurement study of vehicular internet access using in situ Wi-Fi networks, in Proceedings of MobiCom, (2006), 50-61. doi: 10.1145/1161089.1161097.  Google Scholar

[10]

N. Cheng, N. Lu, N. Zhang, X. S. Shen and J. W. Mark, Opportunistic WiFi offloading in vehicular environment: A queueing analysis, in Proceedings of GLOBECOM, (2014), 211-216. Google Scholar

[11]

C. H. FohM. Zukerman and J. W. Tantra, A markovian framework for performance evaluation of ieee 802.11, IEEE Trans. Wireless Commun., 6 (2007), 1276-1265.   Google Scholar

[12]

C. HuaH. YuR. ZhengJ. Li and R. Ni, Online packet dispatching for delay optimal concurrent transmissions in heterogeneous multi-RAT networks, IEEE Trans. Wirel. Commun., 15 (2016), 5076-5086.   Google Scholar

[13]

L. Huang and T. T. Lee, Generalized Pollaczek-Khinchin formula for Markov channels, IEEE Trans. Commun., 61 (2013), 3530-3540.   Google Scholar

[14]

L. Huang and T. T. Lee, Queueing behavior of hybrid ARQ wireless system with finite buffer capacity, in Proceedings of the 21th Annual Wireless and Optical Communications Conference, (2012), 32-36. doi: 10.1109/WOCC.2012.6198142.  Google Scholar

[15]

C. -D. Iskander and P. Takis Mathiopoulos, Analytical level crossing rates and average fade durations for diversity techniques in Nakagami fading channels, IEEE Trans. Commun., 50 (2002), 1301-1309.   Google Scholar

[16]

K. Kawanishi and T. Takine, The M/PH/1+D queue with Markov-renewal service interruptions and its application to delayed mobile data offloading, Perform. Eval., 134 (2019), 102002. doi: 10.1016/j.peva.2019.102002.  Google Scholar

[17]

K. LeeJ. LeeY. YiI. Rhee and S. Chong, Mobile data offloading: How much can WiFi deliver?, IEEE/ACM Trans. Netw., 21 (2013), 536-550.   Google Scholar

[18]

J. LingS. KanugoviS. Vasudevan and A. K. Pramod, Enhanced capacity and coverage by Wi-Fi LTE integration, IEEE Commun. Mag., 53 (2015), 165-171.   Google Scholar

[19]

S. Mahabhashyam and N. Gautam, On queues with Markov modulated service rates, Queueing Syst., 51 (2005), 89-113.  doi: 10.1007/s11134-005-2158-x.  Google Scholar

[20]

F. Mehmeti and T. Spyropoulos, Performance analysis of "on-the-spot" mobile data offloading, in Proceedings of GLOBECOM, (2013), 1577-1583. Google Scholar

[21]

F. Mehmeti and T. Spyropoulos, Performance analysis of mobile data offloading in heterogeneous networks, IEEE Trans. Mob. Comput., 16 (2017), 482-497.   Google Scholar

[22]

F. Mehmeti and T. Spyropoulos, Performance modeling, analysis, and optimization of delayed mobile data offloading for mobile users, IEEE/ACM Trans. Netw., 25 (2017), 550-564.   Google Scholar

[23]

J. F. Shoch and J. A. Hupp, Measured performance of an ethernet local network, ACM Commun., 23 (1980), 711-721.  doi: 10.1145/359038.359044.  Google Scholar

[24]

N. Wang and J. Wu, Opportunistic WiFi offloading in a vehicular environment: Waiting or downloading now?, in Proceedings of INFOCOM, (2016), 1-9. Google Scholar

[25]

R. W. Wolff, Poisson arrivals see time averages, Oper. Res., 30 (1982), 223-231.  doi: 10.1287/opre.30.2.223.  Google Scholar

[26]

C. Zhang, B. Gu, Z. Liu, K. Yamori and Y. Tanaka, A reinforcement learning approach for cost- and energy-aware mobile data offloading, in Proceedings of the 18th Asia-Pacific Network Operations and Management Symposium, (2016), 1-6. Google Scholar

[27]

C. ZhangB. GuZ. LiuK. Yamori and Y. Tanaka, Cost- and energy-aware multi-flow mobile data offloading using Markov decision process, IEICE Trans. Commun., E101.B (2017), 657-666.  doi: 10.1587/transcom.2017NRP0014.  Google Scholar

[28]

D. Zhang and C. K. Yeo, Optimal handing-back point in mobile data offloading, in Proceedings of VNC, (2012), 219-225. Google Scholar

[29]

J. Zhang, Z. Zhou, T. T. Lee and T. Ye, Delay analysis of three-state Markov channels, in Proceedings of 12th International Conference on Queueing Theory and Network Applications, (2017), 101-117. doi: 10.1007/978-3-319-68520-5_7.  Google Scholar

[30]

H. ZhuM. LiL. FuG. XueY. Zhu and L. M. Ni, Impact of traffic influxes: Revealing exponential intercontact time in urban VANETs, IEEE Trans. Parallel Distrib. Syst., 22 (2011), 1258-1266.   Google Scholar

Figure 1.  Transition of wireless channel states in urban areas
Figure 2.  Process of the proposed Wi-Fi offloading strategy
Figure 3.  State transition of the data transmission
Figure 4.  Relationship between two kinds of embedded points
Figure 5.  The $ m $th frame starts service in the cellular state, while the last event is (a) the $ (m-1) $th frame starts its service in the cellular state, or (b) the service state transits to cellular state when the $ (m-1) $th frame is in service
Figure 6.  The service time when a frame starts its service in the deferred state
Figure 7.  Waiting time of the newly-arrived frame
Figure 8.  Delay and efficiency performance in the M/MMSP/1 queueing system
Figure 9.  Utility vs. deadline in the M/MMSP/1 queueing system
Figure 10.  Utility $ U $ vs. preference weight $ a $ in the M/MMSP/1 queueing system
Figure 11.  Utility $ U $ vs. preference weight $ a $ when the duration of channel states $ C $ and $ F $ follow the truncated Pareto distribution
Figure 12.  Utility $ U $ vs. preference weight $ a $ when the data frame size is dual-fixed
Figure 13.  Utility $ U $ vs. preference weight $ a $ when the data rate of each Wi-Fi hotspot is different
Figure 14.  State transition diagram of the two-dimensional Markov chain
Table 1.  Parameters employed in the performance study
Parameter Value
Mean duration of channel state $ C $ 28.42s
Mean duration of channel state $ F $ 12.57s
Data rate of cellular network 8.7Mbps
Data rate of Wi-Fi hotspots 24.4Mbps
Mean frame size 8.184Kb
Arrival rate of data frames 800 frames/s
Parameter Value
Mean duration of channel state $ C $ 28.42s
Mean duration of channel state $ F $ 12.57s
Data rate of cellular network 8.7Mbps
Data rate of Wi-Fi hotspots 24.4Mbps
Mean frame size 8.184Kb
Arrival rate of data frames 800 frames/s
[1]

Ajay Jasra, Kody J. H. Law, Yaxian Xu. Markov chain simulation for multilevel Monte Carlo. Foundations of Data Science, 2021, 3 (1) : 27-47. doi: 10.3934/fods.2021004

[2]

Cheng-Kai Hu, Fung-Bao Liu, Hong-Ming Chen, Cheng-Feng Hu. Network data envelopment analysis with fuzzy non-discretionary factors. Journal of Industrial & Management Optimization, 2021, 17 (4) : 1795-1807. doi: 10.3934/jimo.2020046

[3]

Reza Lotfi, Yahia Zare Mehrjerdi, Mir Saman Pishvaee, Ahmad Sadeghieh, Gerhard-Wilhelm Weber. A robust optimization model for sustainable and resilient closed-loop supply chain network design considering conditional value at risk. Numerical Algebra, Control & Optimization, 2021, 11 (2) : 221-253. doi: 10.3934/naco.2020023

[4]

Haodong Chen, Hongchun Sun, Yiju Wang. A complementarity model and algorithm for direct multi-commodity flow supply chain network equilibrium problem. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2217-2242. doi: 10.3934/jimo.2020066

[5]

Mohammed Abdelghany, Amr B. Eltawil, Zakaria Yahia, Kazuhide Nakata. A hybrid variable neighbourhood search and dynamic programming approach for the nurse rostering problem. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2051-2072. doi: 10.3934/jimo.2020058

[6]

Caichun Chai, Tiaojun Xiao, Zhangwei Feng. Evolution of revenue preference for competing firms with nonlinear inverse demand. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021071

[7]

Gelasio Salaza, Edgardo Ugalde, Jesús Urías. Master--slave synchronization of affine cellular automaton pairs. Discrete & Continuous Dynamical Systems, 2005, 13 (2) : 491-502. doi: 10.3934/dcds.2005.13.491

[8]

Roberto Civino, Riccardo Longo. Formal security proof for a scheme on a topological network. Advances in Mathematics of Communications, 2021  doi: 10.3934/amc.2021009

[9]

Rabiaa Ouahabi, Nasr-Eddine Hamri. Design of new scheme adaptive generalized hybrid projective synchronization for two different chaotic systems with uncertain parameters. Discrete & Continuous Dynamical Systems - B, 2021, 26 (5) : 2361-2370. doi: 10.3934/dcdsb.2020182

[10]

Juliang Zhang, Jian Chen. Information sharing in a make-to-stock supply chain. Journal of Industrial & Management Optimization, 2014, 10 (4) : 1169-1189. doi: 10.3934/jimo.2014.10.1169

[11]

Akane Kawaharada. Singular function emerging from one-dimensional elementary cellular automaton Rule 150. Discrete & Continuous Dynamical Systems - B, 2021  doi: 10.3934/dcdsb.2021125

[12]

Liqiang Jin, Yanqing Liu, Yanyan Yin, Kok Lay Teo, Fei Liu. Design of probabilistic $ l_2-l_\infty $ filter for uncertain Markov jump systems with partial information of the transition probabilities. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021070

[13]

Paul E. Anderson, Timothy P. Chartier, Amy N. Langville, Kathryn E. Pedings-Behling. The rankability of weighted data from pairwise comparisons. Foundations of Data Science, 2021, 3 (1) : 1-26. doi: 10.3934/fods.2021002

[14]

Rui Hu, Yuan Yuan. Stability, bifurcation analysis in a neural network model with delay and diffusion. Conference Publications, 2009, 2009 (Special) : 367-376. doi: 10.3934/proc.2009.2009.367

[15]

Jingni Guo, Junxiang Xu, Zhenggang He, Wei Liao. Research on cascading failure modes and attack strategies of multimodal transport network. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2020159

[16]

Andrey Kovtanyuk, Alexander Chebotarev, Nikolai Botkin, Varvara Turova, Irina Sidorenko, Renée Lampe. Modeling the pressure distribution in a spatially averaged cerebral capillary network. Mathematical Control & Related Fields, 2021  doi: 10.3934/mcrf.2021016

[17]

Yusra Bibi Ruhomally, Muhammad Zaid Dauhoo, Laurent Dumas. A graph cellular automaton with relation-based neighbourhood describing the impact of peer influence on the consumption of marijuana among college-aged youths. Journal of Dynamics & Games, 2021  doi: 10.3934/jdg.2021011

[18]

Kehan Si, Zhenda Xu, Ka Fai Cedric Yiu, Xun Li. Open-loop solvability for mean-field stochastic linear quadratic optimal control problems of Markov regime-switching system. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021074

[19]

Liqin Qian, Xiwang Cao. Character sums over a non-chain ring and their applications. Advances in Mathematics of Communications, 2021  doi: 10.3934/amc.2020134

[20]

Min Li, Jiahua Zhang, Yifan Xu, Wei Wang. Effects of disruption risk on a supply chain with a risk-averse retailer. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021024

2019 Impact Factor: 1.366

Metrics

  • PDF downloads (14)
  • HTML views (54)
  • Cited by (0)

Other articles
by authors

[Back to Top]