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Adaptive interest management via push-pull algorithms
- In Proceedings of the 10th International Symposium on Distributed Simulation and Real Time Systems. IEEE
, 2006
"... Interest Management in large-scale distributed applications aims to reduce the amount of extraneous broadcast communication between nodes in the system with the aim of increasing responsiveness and scalability. We present a middleware-layer interest management framework based on pattern prediction t ..."
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Cited by 3 (1 self)
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Interest Management in large-scale distributed applications aims to reduce the amount of extraneous broadcast communication between nodes in the system with the aim of increasing responsiveness and scalability. We present a middleware-layer interest management framework based on pattern prediction to inform the oscillation of the system’s protocol for the processing of state updates between two competing modes. This framework is transparent to the application itself. We discuss various algorithms for performing the prediction and experimentally evaluate the effectiveness of these algorithms against each other and a set of optimal and sub-optimal baselines. 1
A Dynamic Data Driven Application System for Vehicle Tracking
"... Tracking the movement of vehicles in urban environments using fixed position sensors, mobile sensors, and crowd-sourced data is a challenging but important problem in applications such as law enforcement and defense. A dynamic data driven application system (DDDAS) is described to track a vehicle’s ..."
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Tracking the movement of vehicles in urban environments using fixed position sensors, mobile sensors, and crowd-sourced data is a challenging but important problem in applications such as law enforcement and defense. A dynamic data driven application system (DDDAS) is described to track a vehicle’s movements by repeatedly identifying the vehicle under investigation from live image and video data, predicting probable future locations, and repositioning sensors or retargeting requests for information in order to reacquire the vehicle. An overview of the envisioned system is described that includes image processing algorithms to detect and recapture the vehicle from live image data, a computational framework to predict probable vehicle locations at future points in time, and a power aware data distribution management system to disseminate data and requests for information over ad hoc wireless communication networks. A testbed under development in the midtown area of Atlanta, Georgia in the United States is briefly described.
MGRID: A Modifiable-Grid Region Matching Approach for DDM in the HLA RTI
"... In a large-scale simulation Data Distribution Management (DDM) plays a prominent role in supporting simulation entities as many as possible. In order to provide a flexible solution of region matching to different simulation scenarios, we propose a region matching approach for DDM, MGRID. MGRID can g ..."
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In a large-scale simulation Data Distribution Management (DDM) plays a prominent role in supporting simulation entities as many as possible. In order to provide a flexible solution of region matching to different simulation scenarios, we propose a region matching approach for DDM, MGRID. MGRID can gather run-time information about regions, then evaluate the information by our region matching cost model and make adjustments for present situation accordingly. MGRID has been implemented in our HLA RTI system using C++ language, which follows IEEE Standard 1516. In addition, we have implemented region-based approach, hybrid-based approach and sort-based approach for comparison. In our experimental evaluations MGRID performed well in all test cases. 1.
PATIM: PROXIMITY AWARE TIME MANAGEMENT
, 2008
"... Date: I hereby declare that all information in this document has been ob-tained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this w ..."
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Date: I hereby declare that all information in this document has been ob-tained and presented in accordance with academic rules and ethical conduct. I also declare that, as required by these rules and conduct, I have fully cited and referenced all material and results that are not original to this work.
