DOI QR코드

DOI QR Code

데이터 액세스 확률의 제곱근 법칙을 이용한 상호 관련 데이터 할당 기법

An Interdependent Data Allocation Scheme Using Square Root Rule of Data Access Probability

  • 권혁민 (세명대학교 정보통신학부)
  • Kwon, Hyeokmin (School of Information and Communication System, Semyung University)
  • 투고 : 2015.08.15
  • 심사 : 2015.10.09
  • 발행 : 2015.10.31

초록

데이터 할당 기술은 데이터 방송 시스템의 성능을 향상시키기 위해서 필수적이다. 본 논문은 질의 프로파일과 질의 요청 확률이 주어진 환경에서 다중 데이터 질의를 처리하기 위하여 방송채널에 데이터를 할당하는 주제를 연구하여 IDAS(Interdependent Dta Allocation Scheme)로 명명된 새로운 데이터 할당 기법을 제안한다. 제안된 기법은 각 데이터의 방송빈도를 자신의 상대적 액세스 확률의 제곱근 값에 비례하게 설정하는 전략을 채택한다. IDAS 기법은 요청 확률이 높은 질의들을 빠르게 처리할 수 있고 적절한 수준의 질의 데이터 인접성을 보일 수 있기 때문에 질의 응답 시간의 성능을 향상시킬 수 있다. 제안된 기법의 성능 평가를 위해 시뮬레이션이 수행되었다. 실험 결과에 따르면, 평균 응답시간의 성능에서 IDAS는 다른 기법보다 우수한 성능을 보인다.

A data allocation technique is essential to improve the performance of data broadcast systems. This paper explores the issues for allocating data items on broadcast channels to process multiple-data queries in the environment where query profiles and query request rates are given, and proposes a new data allocation scheme named IDAS. The proposed scheme employs the strategy that the broadcast frequency of each data is determined by the square root value of its relative access probability. IDAS could enhance the performance of query response time since it can process queries of high request rate fast and show a resonable degree of query data adjacency. Simulation is performed to evaluate the performance of the proposed scheme. The simulation results show that IDAS outperforms other schemes in terms of the average response time.

키워드

참고문헌

  1. S. Acharya, "Broadcast Disks: Disseminationbased Data Management for Asymmetric Communication Environments," Ph.D. thesis, Brown University, 1998.
  2. W. G. Yee, S. Navathe, E. Omiecinski, and C. Jermaine, "Efficient Data Allocation over Multiple Channels at Broadcast Servers," IEEE Trans. on Computers, Vol. 51, No. 10, pp. 1231-1236, Oct. 2002. https://doi.org/10.1109/TC.2002.1039849
  3. S. Wang and H.L. Chen, "An O(N log K) Restricted Dynamic Programming Algorithm for Data Allocation over Multiple Channels," IEICE trans. on communications, Vol. E88-B, No. 9, pp. 3756-3764, Sep. 2005. https://doi.org/10.1093/ietcom/e88-b.9.3756
  4. H.M. Kwon, "TLDP: A New Broadcast Scheduling Scheme for Multiple Broadcast- Channel Environments," The Journal of the Institute of Webcasting, Internet and Telecommunication, Vol. 11, No. 2, pp. 63-72, 2011.
  5. H.M. Kwon, "A Near Optimal Data Allocation Scheme for Multiple Broadcast-Channel Environments," The Journal of the Institute of Webcasting, Internet and Telecommunication, Vol. 12, No. 1, pp. 17-27, 2012.
  6. H.P. Hung, J.W. Huang, J.L. Huang, and M.S. Chen, "Scheduling dependent items in data broadcasting environments," ACM SAC 2006.
  7. S.W. Park and S.W. Jung, "Interdependent Data Allocation a scheme over Multiple Wireless Vroadcast Channels," Journal of KIISE : Database, Vol. 36, No. 1, pp. 30-43, 2009.
  8. Y.D. Chung and M.H. Kim, "Effective Data Placement for Wireless Broadcast," Distributed and Parallel Databases, Vol 9, No. 2, 2001
  9. J.L. Huang and M.S. Chen, "Dependent data broadcasting for unordered queries in a multiple channel mobile environment," IEEE Trans. on Knowledge and Data Engr., Vol. 16, No. 6, 2004.
  10. H.M. Kwon, "A Broadcast Data Allocation Scheme for Multiple-Data Queries Using Moving Average of Data Access Probability," The Journal of the Institute of Webcasting, Internet and Telecommunication, Vol. 14, No. 5, pp. 35-43, 2014.
  11. C. Hsu, G. Lee, A.L.P. Chen, "A near optimal algorithm for generating broadcast programs on multiple channels," Proc. ACM 10th Int'l Conf. CIKM, Atlanta, Georgia, pp. 303-309, 2001.
  12. H. Schwetman, 'CSIM Users' Guide for Use with CSIM Revision 16', Microelectronics and Computer Technology Corporation, 1992.

피인용 문헌

  1. A Query-Based Data Allocation Scheme for Multiple Broadcast-Channel Environments vol.16, pp.6, 2016, https://doi.org/10.7236/JIIBC.2016.16.6.165