Journal of Network and Systems Management

, Volume 22, Issue 1, pp 23–49 | Cite as

Location Prediction Based on a Sector Snapshot for Location-Based Services

  • Mohammad Sharif Daoud
  • Aladdin Ayesh
  • Mustafa Al-Fayoumi
  • Adrian A. Hopgood


In location-based services (LBSs), the service is provided based on the users’ locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique.


Mobility Mobile displacement Cell-based Map-based Markov chain model GPS UMTS 


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Mohammad Sharif Daoud
    • 1
  • Aladdin Ayesh
    • 1
  • Mustafa Al-Fayoumi
    • 2
  • Adrian A. Hopgood
    • 3
  1. 1.Faculty of TechnologyDe Montfort UniversityThe Gateway, LeicesterUK
  2. 2.College of Computer Engineering and SciencesSalman Bin Abdulaziz UniversityAl-KharjSaudi Arabia
  3. 3.Sheffield Business SchoolSheffield Hallam UniversitySheffieldUK

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