Mobile Networks and Applications

, Volume 14, Issue 5, pp 590–610

Static Replication Strategies for Content Availability in Vehicular Ad-hoc Networks

  • Shyam Kapadia
  • Bhaskar Krishnamachari
  • Shahram Ghandeharizadeh
Article

DOI: 10.1007/s11036-008-0120-y

Cite this article as:
Kapadia, S., Krishnamachari, B. & Ghandeharizadeh, S. Mobile Netw Appl (2009) 14: 590. doi:10.1007/s11036-008-0120-y

Abstract

This study investigates replication strategies for reducing latency to desired content in a vehicular peer-to-peer network. We provide a general constrained optimization formulation for efficient replication and study it via analysis and simulations employing a discrete random walk mobility model for the vehicles. Our solution space comprises of a family of popularity based replication schemes each characterized by an exponent n. We find that the optimal replication exponent depends significantly on factors such as the total system storage, data item size, and vehicle trip duration. With small data items and long client trip durations, n ∼ 0.5 i.e., a square-root replication scheme provides the lowest aggregate latency across all data item requests. However, for short trip durations, n moves toward 1, making a linear replication scheme more favorable. For larger data items and long client trip durations, we find that the optimal replication exponent is below 0.5. Finally, for these larger data items, if the client trip duration is short, the optimal replication exponent is found to be a function of the total storage in the system. Subsequently, the above observations are validated with two real data sets: one based on a city map with freeway traffic information and the other employing encounter traces from a bus network.

Keywords

data replicationavailabilityvehicular ad-hoc networksoptimization

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Shyam Kapadia
    • 1
  • Bhaskar Krishnamachari
    • 1
    • 2
  • Shahram Ghandeharizadeh
    • 1
  1. 1.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA