Real-time distributed information systems (RDIS) are designed to process, manage, and deliver data across interconnected components in distributed environments under strict timing constraints. In the context of public transportation, RDIS gathers information from heterogeneous data sources, such as buses and stations, to provide passengers with timely updates on schedules, delays, and operational changes through user interfaces on web, mobile apps, and onboard displays. Although research has extensively addressed data fusion from diverse sources; challenges such as ensuring consistent and synchronized data delivery across multiple user-facing interfaces while maintaining low latency, remain relatively underexplored in both research and practical implementations. This thesis seeks to address these challenges by analyzing the specific requirements of public transportation systems, developing tailored consistency metrics, and designing synchronization protocols for RDIS output interfaces. By combining theoretical insights with hands-on experimentation, this thesis aims to propose effective approaches for enhancing data synchronization and delivery in real-world distributed systems.
Thesis Type |
|
Student |
Thu Van Dao |
Status |
Running |
Supervisor(s) |
Stefan Decker |
Advisor(s) |
Johannes Theissen-Lipp |
Contact |
theissen-lipp@dbis.rwth-aachen.de |
Background
Real-time distributed Information Systems in public transportation rely on data from diverse sources, including GPS devices, ticketing systems, sensors, and scheduling platforms. These inputs are aggregated at centralized components, where they are consolidated into unified data formats for further propagation to output interfaces such as passenger displays, mobile apps, and control center dashboards. While the aggregation and consolidation process often employs synchronization mechanisms to maintain data consistency at the central level, the subsequent propagation to output interfaces frequently lacks structured synchronization protocols, leading to potential inconsistencies in the real-time updates presented to users.
Current synchronization approaches for these systems are often ad-hoc, failing to address challenges such as delays, network failures, and dynamic disruptions effectively. Additionally, the lack of standardized metrics for measuring system-wide consistency complicates the evaluation and optimization of synchronization processes. These shortcomings undermine the reliability, scalability, and operational efficiency of passenger information systems, ultimately reducing passenger satisfaction and trust in the service.
Objectives
- Develop a metrics framework for system consistency
- Create metrics to measure system-wide consistency, focusing on the propagation of unified data from centralized aggregation points to output interfaces.
- Design synchronization protocols for data propagation
- Develop scalable and robust synchronization protocols tailored to heterogeneous communication methods (e.g., Request/Response, Streaming, Pub/Sub) used between centralized components and output interfaces.
- Evaluate and validate the system using the proposed metrics
- Test and validate the synchronization protocols and consistency metrics through simulated real-world scenarios, ensuring alignment with dynamic system demands.
- Validate both the protocols and the metrics by benchmarking against baseline approaches.
Tasks
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Metrics Design and Evaluation
- Identify key consistency metrics, including timeliness, data freshness, and synchronization accuracy, relevant to distributed transportation systems.
- Analyze existing synchronization frameworks (e.g., Probabilistically Bounded Staleness, DDSN) for their potential application in measuring consistency.
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Synchronization Protocol Development
- Create synchronization protocols for data propagation from centralized aggregation points to distributed output interfaces.
- Ensure protocols are adaptable to various communication paradigms and resilient against disruptions.
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System Implementation and Integration
- Implement synchronization protocols within a simulated transportation network.
- Integrate consistency metrics into a monitoring framework to continuously evaluate system performance.
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Validation and Testing
- Simulate operational scenarios, including network delays and disruptions, to assess protocol robustness.
- Use the consistency metrics to benchmark the performance of the system and compare it to existing approaches.