An Adaptable Destination-Based Dissemination Algorithm Using a Publish/Subscribe Model in Vehicular Networks
Author(s) -
Mildred Madai Caballeros Morales,
Rim Haw,
Eung-Jun Cho,
Choong Seon Hong,
Sungwon Lee
Publication year - 2012
Publication title -
journal of computing science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 16
eISSN - 2093-8020
pISSN - 1976-4677
DOI - 10.5626/jcse.2012.6.3.227
Subject(s) - computer science , scalability , dissemination , computer network , distributed computing , publication , vehicular ad hoc network , flooding (psychology) , context (archaeology) , wireless ad hoc network , cluster analysis , network topology , wireless , database , telecommunications , psychology , paleontology , machine learning , advertising , business , psychotherapist , biology
Vehicular Ad Hoc Networks (VANETs) are highly dynamic and unstable due to the heterogeneous nature of the communications, intermittent links, high mobility and constant changes in network topology. Currently, some of the most important challenges of VANETs are the scalability problem, congestion, unnecessary duplication of data, low delivery rate, communication delay and temporary fragmentation. Many recent studies have focused on a hybrid mechanism to disseminate information implementing the store and forward technique in sparse vehicular networks, as well as clustering techniques to avoid the scalability problem in dense vehicular networks. However, the selection of intermediate nodes in the store and forward technique, the stability of the clusters and the unnecessary duplication of data remain as central challenges. Therefore, we propose an adaptable destination-based dissemination algorithm (DBDA) using the publish/subscribe model. DBDA considers the destination of the vehicles as an important parameter to form the clusters and select the intermediate nodes, contrary to other proposed solutions. Additionally, DBDA implements a publish/subscribe model. This model provides a context-aware service to select the intermediate nodes according to the importance of the message, destination, current location and speed of the vehicles; as a result, it avoids delay, congestion, unnecessary duplications and low delivery rate.
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