Advanced Engineering Mathematics: Maple Computer Guide
Advanced Engineering Mathematics: Maple Computer Guide
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Space-based communication data management in scalable distributed simulation
Journal of Parallel and Distributed Computing - Parallel and Distributed Discrete Event Simulation--An Emerging Technology
Dynamic grid-based approach to data distribution management
Journal of Parallel and Distributed Computing - Parallel and Distributed Discrete Event Simulation--An Emerging Technology
Oporto: A Realistic Scenario Generator for Moving Objects
Geoinformatica
Grid-Based Data Management in Distributed Simulation
SS '00 Proceedings of the 33rd Annual Simulation Symposium
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
A Traveling Salesman Mobility Model and Its Location Tracking in PCS Networks
ICDCS '01 Proceedings of the The 21st International Conference on Distributed Computing Systems
Optimized Dynamic Grid-Based DDM Protocol for Large-Scale Distributed Simulation Systems
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 15 - Volume 16
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Hi-index | 0.01 |
Communication data management (CDM) is an important issue in high performance distributed computing where a massive amount of data eXchange frequently occurs among geographically distributed components. In this paper, we review eXisting CDM schemes in distributed computing systems and we propose more efficient CDM schemes. Three types of quantization-based CDM schemes are proposed: the fiXed quantization-based CDM (FQ-CDM), the adaptive quantization-based CDM (AQ-CDM), and the mobility-predictive quantization-based CDM (MPQ-CDM). The FQ-CDM applies a basic theory of quantized systems to the distributed computing environment. The AQ-CDM uses a communication object clustering mechanism, which operates a pattern recognition clustering algorithm. The MPQ-CDM predicts the neXt states of communication objects by using past and current data and controls data communication among communication objects. The mobile object location monitoring system (MOLMS), based on High Level Architecture, is designed and developed to apply these CDM schemes to distributed computing. In this paper we conduct eXperiments by comparing these CDM schemes with each other on the MOLMS. The eXperimental results show that the AQ-CDM is the more effective scheme for communication message reduction and the MPQ-CDM is the more suitable scheme for mobile location error reduction.