Adaptive Quantization-based Communication Data Management for High- Performance Geo-computation in Grid Computing
Communication Data Management (CDM) is an important issue in complex and large-scale modern geo-computation applications. In this paper, we review existing CDM schemes and propose an efficient adaptive quantization-based CDM scheme for geocomputation in grid environment. This model is based on theory of quantization and uses distributed clusters which are concerned about the features and geographical adjacency of communication objects. And,this model uses various thresholds which are suitable for individual clusters and effectively reduces communication messages by clustering and diverse thresholds. For realization of this scheme, we design and develop a HLA (High LevelArchitecture)-based system for geo-computation in grid environment. For performance evaluation, this paper measures reduction rate of message traffic and location errors. This scheme has more effective message traffic reduction and less location errors with precise location accuracy rate than general quantization-based scheme. The empirical result apparently presents that adaptive quantization-based CDM scheme is a suitable scheme for high-performance geo-computation.
In Kee Kim Yong Beom Ma Jong Sik Lee
School of Computer Science and Information Engineering Inha University
国际会议
第五届网格与协同计算国际会议(The Fifth International Conference on Grid and Cooperative Computing GCC 2006)
长沙
英文
470-476
2006-10-21（万方平台首次上网日期，不代表论文的发表时间）