Context-Aware Pending Interest Table Management Scheme for NDN-Based VANETs

Sensors (Basel). 2022 May 31;22(11):4189. doi: 10.3390/s22114189.

Abstract

In terms of delivery effectiveness, Vehicular Adhoc NETworks (VANETs) applications have multiple, possibly conflicting, and disparate needs (e.g., latency, reliability, and delivery priorities). Named Data Networking (NDN) has attracted the attention of the research community for effective content retrieval and dissemination in mobile environments such as VANETs. A vehicle in a VANET application is heavily reliant on information about the content, network, and application, which can be obtained from a variety of sources. The information gathered can be used as context to make better decisions. While it is difficult to obtain the necessary context information at the IP network layer, the emergence of NDN is changing the tide. The Pending Information Table (PIT) is an important player in NDN data retrieval. PIT size is the bottleneck due to the limited opportunities provided by current memory technologies. PIT overflow results in service disruptions as new Interest messages cannot be added to PIT. Adaptive, context-aware PIT entry management solutions must be introduced to NDN-based VANETs for effective content dissemination. In this context, our main contribution is a decentralised, context-aware PIT entry management (CPITEM) protocol. The simulation results show that the proposed CPITEM protocol achieves lower Interest Satisfaction Delay and effective PIT utilization based on context when compared to existing PIT entry replacement protocols.

Keywords: NDN; Named Defined Networking (NDN); PIT; Pending Information Table; VANETs; context-aware naming; non-safety content; safety content dissemination.

MeSH terms

  • Computer Communication Networks*
  • Computer Simulation
  • Information Storage and Retrieval
  • Reproducibility of Results
  • Wireless Technology*

Grants and funding

“Research Center of the Female Scientific and Medical Colleges”, Deanship of Scientific Research, King Saud University.