A fuzzy logic based approach for structure-free aggregation in vehicular ad-hoc networks

Abstract

Information aggregation is used to merge correlated data items from different nodes before redistributing them. Thus, using aggregation the number of transmissions and the communication overhead can be reduced significantly. Especially for applications which require periodic dissemination of information into a large region, aggregation is a prerequisite. Consider for example a traffic information system where each vehicle periodically disseminates information about road conditions. The aim is to provide drivers with accurate information on traffic conditions for a large road section, so drivers can be informed in time and can take alternate routes in case of traffic congestion, for example. Many aggregation approaches for VANETs use a fixed or structured segmentation of roads for these applications. Based on such segments the aggregation function is applied to fuse data. We argue that such fixed bounds contradict the real situation on roads. Thus either the segments are too large, resulting in loss of accuracy or the segments are too small, resulting in high communication load. Therefore, we propose in this work a system for completely structurefree aggregation. We employ fuzzy reasoning to allow for aggregation decisions to be based on a flexible and extensible set of criteria. These criteria can be application specific and enable a dynamic fragmentation of the road according to the applications' requirements.

Evaluation and Comparative Study of Structure Free Aggregation Techniques for Duty Cycled Wireless Sensor Networks

“…it does not guarantee good aggregation gain as network grows and incur long delay in large networks. An another fuzzy based structure free aggregation technique was proposed by Dietzel et al [5] for Vehicle Ad hoc Networks. This approach is suitable for those applications, where periodic data dissemination takes place around a large field like traffic information system.…”

“…To integrate highly correlated data, data aggregation takes place based on fuzzy reasoning. This scheme performs better as compared to flooding, in terms of bandwidth and congestion [5]. Dynamic and Scalable Tree-DST: Dynamic and Scalable Tree protocol forwards data along the routing paths which have higher chances of data aggregation.…”

Location Aware Data Aggregation for Efficient Message Dissemination in Vehicular Ad Hoc Networks

“…Here, the aggregates are duplicate-insensitive and are based on square areas of different sizes: small, medium and large. A structure-free data aggregation scheme based on fuzzy reasoning, enabling the vehicles to reach the aggregation decision based on the application specific set of criteria is presented in [5]. Authors of [6] present a cluster-based data aggregation approach where they use compression to provide aggregation without losing accuracy.…”

“…In Traffic View [8], a congestion detection system is presented, including two proposed node-centric data aggregation mechanisms. Additionally, apart from being application specific, most schemes are scenario specific as well, thus considering only one type of scenario, for example highway traffic [5][6] [7][10] [11]. There is a clear need for a more universal data aggregation solution which can be deployed without restrictions on vehicle onboard systems, on any type of application and in any kind of scenario.…”

WIP: Towards optimal online approximation of data streams

“…Some approximation methods are more indirect when related to networking, such as fuzzy [5], [6] and aggregation [5], [7], [8] methods, but almost all perform some form of linear fit.…”