기관회원 [로그인]
소속기관에서 받은 아이디, 비밀번호를 입력해 주세요.
개인회원 [로그인]

비회원 구매시 입력하신 핸드폰번호를 입력해 주세요.
본인 인증 후 구매내역을 확인하실 수 있습니다.

회원가입
서지반출
An Adaptive FEC Mechanism Using Crosslayer Approach to Enhance Quality of Video Transmission over 802.11 WLANs
[STEP1]서지반출 형식 선택
파일형식
@
서지도구
SNS
기타
[STEP2]서지반출 정보 선택
  • 제목
  • URL
돌아가기
확인
취소
  • An Adaptive FEC Mechanism Using Crosslayer Approach to Enhance Quality of Video Transmission over 802.11 WLANs
  • An Adaptive FEC Mechanism Using Crosslayer Approach to Enhance Quality of Video Transmission over 802.11 WLANs
저자명
Han. Long-Zhe,Park. Sung-Jun,Kang. Seung-Seok,In. Hoh-Peter
간행물명
KSII Transactions on internet and information systems : TIIS
권/호정보
2010년|4권 3호|pp.341-357 (17 pages)
발행정보
한국인터넷정보학회
파일정보
정기간행물|ENG|
PDF텍스트
주제분야
기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Forward Error Correction (FEC) techniques have been adopted to overcome packet losses and to improve the quality of video delivery. The efficiency of the FEC has been significantly compromised, however, due to the characteristics of the wireless channel such as burst packet loss, channel fluctuation and lack of Quality of Service (QoS) support. We propose herein an Adaptive Cross-layer FEC mechanism (ACFEC) to enhance the quality of video streaming over 802.11 WLANs. Under the conventional approaches, FEC functions are implemented on the application layer, and required feedback information to calculate redundancy rates. Our proposed ACFEC mechanism, however, leverages the functionalities of different network layers. The Automatic Repeat reQuest (ARQ) function on the Media Access Control (MAC) layer can detect packet losses. Through cooperation with the User Datagram Protocol (UDP), the redundancy rates are adaptively controlled based on the packet loss information. The experiment results demonstrate that the ACFEC mechanism is able to adaptively adjust and control the redundancy rates and, thereby, to overcome both of temporary and persistent channel fluctuations. Consequently, the proposed mechanism, under various network conditions, performs better in recovery than the conventional methods, while generating a much less volume of redundant traffic.