Precise: Predictive Content Dissemination Scheme exploiting realistic mobility patterns Articles uri icon

authors

  • Perez Palma, Noelia
  • Dressler, Falko
  • MANCUSO, VINCENZO

publication date

  • October 2021

start page

  • 1

end page

  • 16

volume

  • 201

International Standard Serial Number (ISSN)

  • 1389-1286

Electronic International Standard Serial Number (EISSN)

  • 1872-7069

abstract

  • Device-to-Device (D2D) communications have expanded the way of managing available network resources to efficiently distribute data between users. D2D exploits communication alternatives, in Opportunistic Networks, based on short range wireless radio technologies such as Bluetooth and WiFi-Direct. Besides, nowadays in most urban areas, realistic human mobility is characterized by often repeated patterns that can be used to accurately predict the next visited regions┬┐we call these regions hotspots (or Replication Zones (RZs)). In this work, we present Predictive Content Dissemination Scheme (Precise), to explore and combine the D2D paradigm along with real mobility and predictions focused on the dissemination of content among hotspots. To analyze the viability of such scheme, we show simulation results and evaluate the average content availability, lifetime and delivery delay, storage usage and network utilization metrics. We compare the performance of Precise with state-of-the-art approaches, such as Epidemic, restricted Epidemic, and Proximity-Interest-Social (PIS) routing protocols. Our results underline the need for smart usage of communication opportunities and storage. We demonstrate that Precise allows for a neat reduction in network activity by decreasing the number of data exchanges by up to 92%, requiring the use of up to 50% less of on-device storage. This comes at negligible costs. In particular, the delivery delay with Precise shows an increase with respect to epidemic dissemination schemes that varies from 0.03 s in the most dynamic case to at most 1.91 s for the least dynamic case, and which however does not hinder the possibility to use Precise for real-time applications. Regarding how contents are spread, we observe that Precise requires 2% to 20% less mobile users to carry them within a target hotspot, especially under slow dynamics. This however does not impact on the probability that mobile users entering the hotspots obtain contents, and barely shortens the lifetime of contents in our experiments from 100 min down to about 95, in the worst case. This demonstrates that the reduction of content availability among mobile users with Precise is either negligible or not impactful, thus guaranteeing the dissemination of contents as with legacy epidemic dissemination protocols.

subjects

  • Computer Science

keywords

  • content dissemination; mobility pattern; opportunistic networks; predictive communication scheme