PROJECT TITLE :

Delay-Constrained Data Aggregation in VANETs

ABSTRACT:

Data aggregation has been recognized as an effective technique for reducing communication costs while obtaining helpful aggregated data. During this paper, we have a tendency to study the crucial downside of delay-constrained knowledge aggregation in vehicular accidental networks (VANETs), that has not been well studied in the literature. With the analysis primarily based on real traces, we have a tendency to observe that there's heterogeneity with node contact patterns, that indicates that some nodes contact different nodes additional frequently. Motivated by this observation, we propose an approach referred to as aTree. The centralized aTree first constructs a information aggregation tree based mostly on the shortest path tree and then assigns a waiting time budget to each node on the tree based on dynamic programming. We further develop a distributed aTree, in which a shortest path tree is made in a very distributed fashion, and nodes determine their waiting time budgets collaboratively. We have a tendency to have performed in depth simulations on real taxi traces, and results show that our aTree schemes incur a lot of lower transmission overhead whereas achieving the identical performance compared with alternative schemes.