An Adaptive Loss-Aware Flow Control Scheme for Delay-Sensitive Applications in OBS Networks
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- JEONG Hongkyu
- Optical Internet Research Center, Information and Communications University The Institute of Electronics, Information and Communication Engineers
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- CHOI JungYul
- Platform Laboratory, KT Corporation The Institute of Electronics, Information and Communication Engineers
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- MO Jeonghoon
- Yonsei University The Institute of Electronics, Information and Communication Engineers
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- KANG Minho
- Optical Internet Research Center, Information and Communications University
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Abstract
Optical Burst Switching (OBS) is one of the most promising switching technologies for next generation optical networks. As delay-sensitive applications such as Voice-over-IP (VoIP) have recently become popular, OBS networks should guarantee stringent Quality of Service (QoS) requirements for such applications. Thus, this paper proposes an Adaptive Loss-aware Flow Control (ALFC) scheme, which adaptively decides on the burst offset time based on loss-rate information delivered from core nodes for assigning a high priority to delay-sensitive application traffic. The proposed ALFC scheme also controls the upper-bounds of the factors inducing delay and jitter for guaranteeing the delay and jitter requirements of delay-sensitive application traffic. Moreover, a piggybacking method used in the proposed scheme accelerates the guarantee of the loss, delay, and jitter requirements because the response time for flow control can be extremely reduced up to a quarter of the Round Trip Time (RTT) on average while minimizing the signaling overhead. Simulation results show that our mechanism can guarantee a 10-3 loss-rate under any traffic load while offering satisfactory levels of delay and jitter for delay-sensitive applications.
Journal
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- IEICE Transactions on Communications
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IEICE Transactions on Communications E91-B (7), 2152-2159, 2008
The Institute of Electronics, Information and Communication Engineers
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Details 詳細情報について
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- CRID
- 1390282679352795136
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- NII Article ID
- 10026830717
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- NII Book ID
- AA10826261
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- ISSN
- 17451345
- 09168516
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed