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| Content Provider | ACM Digital Library |
|---|---|
| Author | Dietzel, Stefan Bako, Boto Kargl, Frank Schoch, Elmar |
| 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 structure-free 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. |
| Starting Page | 79 |
| Ending Page | 88 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781605587370 |
| DOI | 10.1145/1614269.1614283 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-09-25 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Data aggregation Vanet Fuzzy reasoning |
| Content Type | Text |
| Resource Type | Article |
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