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Detail
Journal Article
CANCORE: Context-Aware Network COded REpetition for VANETs
- Authors
- Hyunwoo Kang, Hongseok Yoo, Dongkyun Kim, Yun-Su Chung
- Issue Date
- 2017-03
- Citation
- IEEE Access, v.5, pp.3504-3512
- ISSN
- 2169-3536
- Publisher
- IEEE
- Language
- English
- Type
- Journal Article
- Abstract
- In vehicular networks, safety applications allow people to avoid hazardous situations based on the state of the vehicles in their proximity. Such proximity awareness is realized by allowing each vehicle to collect safety messages called beacons, which are periodically and locally broadcasted from its neighboring vehicles. Hence, the reliability of beacon transmissions is a crucial factor that makes safety applications effective in practice. Particularly, in respect of avoiding risky situations, lossy and scarce vehicular channel should be utilized primarily for reliable delivery of beacons from neighboring vehicles, which are more likely to cause dangerous situations such as collision. However, without consideration to such a requirement of safety applications, existing retransmission schemes treat every vehicles equally and are focusing on improving the retransmission performance in terms of loss recovery. In this paper, we therefore propose a new network coding-based repetition scheme called Context-Aware Network COded REpetition (CANCORE) for maximizing the effectiveness of safety applications. Using knowledge of contextual information (i.e., position, heading, and so on) of vehicles, CANCORE generates coded repetitions allowing more receivers to acquire beacons useful for avoiding impending dangerous situations. Our simulation study verified that CANCORE outperforms existing schemes in terms of its impact on the application-level performance (i.e., the accuracy of proximity awareness).
- KSP Keywords
- Context aware, Contextual information, Existing schemes, Loss recovery, Network Coding, Proximity awareness, Reliable delivery, Safety applications, Safety messages, Simulation study, Vehicular Networks
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC ND)
(CC BY NC ND)
