Skip to main content
SpringerLink
Log in

Unicast Capacity of Vehicular Networks with Socialized Mobility

  • Chapter
  • First Online:
Capacity Analysis of Vehicular Communication Networks

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

  • 831 Accesses

Abstract

In this chapter, we investigate the throughput capacity of social-proximity vehicular networks. The considered network consists of N vehicles moving and communicating on a scalable grid-like street layout following the social-proximity model: each vehicle has a restricted mobility region around a specific social spot, and transmits via a unicast flow to a destination vehicle which is associated with the same social spot. Furthermore, the spatial distribution of the vehicle decays following a power-law distribution from the central social spot towards the border of the mobility region. With vehicles communicating using a variant of the two-hop relay scheme, the asymptotic bounds of throughput capacity are derived in terms of the number of social spots, the size of the mobility region, and the decay factor of the power-law distribution. By identifying these key impact factors of performance mathematically, we find three possible regimes for the throughput capacity and show that inherent mobility patterns of vehicles have considerable impact on network performance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    We do not consider the extreme case in which ν = 0. When ν = 0, there is only one social spot in the network.

  2. 2.

    A road segment is active when vehicles on the road segment can transmit successfully without any interference of transmissions from other road segments. The value of p ac is discussed later in the section.

  3. 3.

    As \(N \rightarrow \infty\) , the probability of the event approaches 1.

References

  1. F. Bai, B. Krishnamachari, Exploiting the wisdom of the crowd: localized, distributed information-centric VANETs. IEEE Commun. Mag. 48(5), 138–146 (2010)

    Article  Google Scholar 

  2. P. Gupta, P. Kumar, The capacity of wireless networks. IEEE Trans. Inf. Theory 46(2), 388–404 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  3. N. Lu, T. Luan, M. Wang, X. Shen, F. Bai, Bounds of asymptotic performance limits of social-proximity vehicular networks. IEEE/ACM Trans. Netw. to appear

    Google Scholar 

  4. M. Neely, E. Modiano, Capacity and delay tradeoffs for ad hoc mobile networks. IEEE Trans. Inf. Theory 51(6), 1917–1937 (2005)

    Article  MathSciNet  Google Scholar 

  5. M. Garetto, P. Giaccone, E. Leonardi, Capacity scaling in ad hoc networks with heterogeneous mobile nodes: the super-critical regime. IEEE/ACM Trans. Netw. 17(5), 1522–1535 (2009)

    Article  Google Scholar 

  6. M. Garetto, E. Leonardi, Restricted mobility improves delay-throughput tradeoffs in mobile ad hoc networks. IEEE Trans. Inf. Theory 56(10), 5016–5029 (2010)

    Article  MathSciNet  Google Scholar 

  7. N. Sarafijanovic-Djukic, M. Pidrkowski, M. Grossglauser, Island hopping: efficient mobility-assisted forwarding in partitioned networks, in Proceedings of IEEE SECON, Reston, Sept 2006

    Google Scholar 

  8. S. Kostof, R. Tobias, The City Shaped (Thames and Hudson, London, 1991)

    Google Scholar 

  9. A. Siksna, The effects of block size and form in North American and Australian city centres. Urban Morphol. 1, 19–33 (1997)

    Google Scholar 

  10. M. Neely, E. Modiano, C. Rohrs, Dynamic power allocation and routing for time-varying wireless networks. IEEE J. Sel. Areas Commun. 23(1), 89–103 (2005)

    Article  Google Scholar 

  11. R. Urgaonkar, M. Neely, Network capacity region and minimum energy function for a delay-tolerant mobile ad hoc network. IEEE/ACM Trans. Netw. 19(4), 1137–1150 (2011)

    Article  Google Scholar 

  12. D. Slaughter, Difference Equations to Differential Equations (University Press of Florida, Gainesville, FL, USA 2009)

    Google Scholar 

  13. R. Motwani, P. Raghavan, Randomized Algorithms (Chapman & Hall/CRC, Cambridge University Press, Cambridge, UK 1995)

    Book  MATH  Google Scholar 

  14. V. Vapnik, A. Chervonenkis, On the uniform convergence of relative frequencies of events to their probabilities. Theory Probab. Appl. 16, 264 (1971)

    Article  MATH  Google Scholar 

  15. V. Vapnik, Statistical Learning Theory (Wiley-Interscience, New York, 1998)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada

    Ning Lu & Xuemin (Sherman) Shen

Authors
  1. Ning Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xuemin (Sherman) Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2014 The Author(s)

About this chapter

Cite this chapter

Lu, N., Shen, X.(. (2014). Unicast Capacity of Vehicular Networks with Socialized Mobility. In: Capacity Analysis of Vehicular Communication Networks. SpringerBriefs in Electrical and Computer Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8397-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-8397-7_3

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-8396-0

  • Online ISBN: 978-1-4614-8397-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation