An On-the-fly Provenance Tracking Mechanism for Stream Processing Systems

Applications that operate over streaming data withhigh-volume and real-time processing requirements are becomingincreasingly important. These applications process streamingdata in real-time and deliver instantaneous responses to supportprecise and on-time decisions. In such systems, traceability -the ability to verify and investigate the source of a particularoutput - in real-time is extremely important. This ability allowsraw streaming data to be checked and processing steps to beverified and validated in timely manner. Therefore, it is crucialthat stream systems have a mechanism for dynamically trackingprovenance - the process that produced result data - at executiontime, which we refer to as on-the-fly stream provenance tracking.In this paper, we propose a novel on-the-fly provenance trackingmechanism that enables provenance queries to be performeddynamically without requiring provenance assertions to be storedpersistently. We demonstrate how our provenance mechanismworks by means of an on-the-fly provenance tracking algorithm.The experimental evaluation shows that our provenance solutiondoes not have a significant effect on the normal processing ofstream systems given a 7% overhead. Moreover, our provenancesolution offers low-latency processing (0.3 ms per additionalcomponent) with reasonable memory consumption.<br/

Event tracking for real-time unaware sensitivity analysis (EventTracker)

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This paper introduces a platform for online Sensitivity Analysis (SA) that is applicable in large scale real-time data acquisition (DAQ) systems. Here we use the term real-time in the context of a system that has to respond to externally generated input stimuli within a finite and specified period. Complex industrial systems such as manufacturing, healthcare, transport, and finance require high quality information on which to base timely responses to events occurring in their volatile environments. The motivation for the proposed EventTracker platform is the assumption that modern industrial systems are able to capture data in real-time and have the necessary technological flexibility to adjust to changing system requirements. The flexibility to adapt can only be assured if data is succinctly interpreted and translated into corrective actions in a timely manner. An important factor that facilitates data interpretation and information modelling is an appreciation of the affect system inputs have on each output at the time of occurrence. Many existing sensitivity analysis methods appear to hamper efficient and timely analysis due to a reliance on historical data, or sluggishness in providing a timely solution that would be of use in real-time applications. This inefficiency is further compounded by computational limitations and the complexity of some existing models. In dealing with real-time event driven systems, the underpinning logic of the proposed method is based on the assumption that in the vast majority of cases changes in input variables will trigger events. Every single or combination of events could subsequently result in a change to the system state. The proposed event tracking sensitivity analysis method describes variables and the system state as a collection of events. The higher the numeric occurrence of an input variable at the trigger level during an event monitoring interval, the greater is its impact on the final analysis of the system state. Experiments were designed to compare the proposed event tracking sensitivity analysis method with a comparable method (that of Entropy). An improvement of 10% in computational efficiency without loss in accuracy was observed. The comparison also showed that the time taken to perform the sensitivity analysis was 0.5% of that required when using the comparable Entropy based method.EPSR

MODELING THE INFORMATION QUALITY OF OBJECT TRACKING SYSTEMS

Advances in information and communication technologies, such as Radio Frequency Identification (RFID), mobile and wireless mesh networks, bring us closer to the vision of “Internet of Things”, a global network of people, products or objects that can be easily readable, recognizable, locatable, and manageable over the world wide web. Such a network can provide ubiquitous and real-time information on movements of objects; and object tracking systems monitor the moving objects and register their on-going location in the context of higher-level applications, such as supply chain management, food traceability and retail, where monitoring of objects is required. This paper investigates information quality of object tracking systems and proposes an analytical model that measures the degree of information completeness of object tracking systems based on the scope and depth of their data capturing capabilities. We demonstrate that the information completeness of object tracking systems is influenced by the configuration of object tracking systems. The model may be used for both ex-ante and ex-post evaluations of object tracking systems, under the auspices of their information quality requirements, considering that their use is expected to blossom in the “Internet-of- Things” era

An autonomous rendezvous and docking system using cruise missile technologies

In November 1990 the Autonomous Rendezvous & Docking (AR&D) system was first demonstrated for members of NASA's Strategic Avionics Technology Working Group. This simulation utilized prototype hardware from the Cruise Missile and Advanced Centaur Avionics systems. The object was to show that all the accuracy, reliability and operational requirements established for a space craft to dock with Space Station Freedom could be met by the proposed system. The rapid prototyping capabilities of the Advanced Avionics Systems Development Laboratory were used to evaluate the proposed system in a real time, hardware in the loop simulation of the rendezvous and docking reference mission. The simulation permits manual, supervised automatic and fully autonomous operations to be evaluated. It is also being upgraded to be able to test an Autonomous Approach and Landing (AA&L) system. The AA&L and AR&D systems are very similar. Both use inertial guidance and control systems supplemented by GPS. Both use an Image Processing System (IPS), for target recognition and tracking. The IPS includes a general purpose multiprocessor computer and a selected suite of sensors that will provide the required relative position and orientation data. Graphic displays can also be generated by the computer, providing the astronaut / operator with real-time guidance and navigation data with enhanced video or sensor imagery

On-road visual vehicle tracking using Markov chain Monte Carlo with metropolis sampling

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method

Configuration management issues and objectives for a real-time research flight test support facility

Presented are some of the critical issues and objectives pertaining to configuration management for the NASA Western Aeronautical Test Range (WATR) of Ames Research Center. The primary mission of the WATR is to provide a capability for the conduct of aeronautical research flight test through real-time processing and display, tracking, and communications systems. In providing this capability, the WATR must maintain and enforce a configuration management plan which is independent of, but complimentary to, various research flight test project configuration management systems. A primary WATR objective is the continued development of generic research flight test project support capability, wherein the reliability of WATR support provided to all project users is a constant priority. Therefore, the processing of configuration change requests for specific research flight test project requirements must be evaluated within a perspective that maintains this primary objective

Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics

Recently several hierarchical inverse dynamics controllers based on cascades of quadratic programs have been proposed for application on torque controlled robots. They have important theoretical benefits but have never been implemented on a torque controlled robot where model inaccuracies and real-time computation requirements can be problematic. In this contribution we present an experimental evaluation of these algorithms in the context of balance control for a humanoid robot. The presented experiments demonstrate the applicability of the approach under real robot conditions (i.e. model uncertainty, estimation errors, etc). We propose a simplification of the optimization problem that allows us to decrease computation time enough to implement it in a fast torque control loop. We implement a momentum-based balance controller which shows robust performance in face of unknown disturbances, even when the robot is standing on only one foot. In a second experiment, a tracking task is evaluated to demonstrate the performance of the controller with more complicated hierarchies. Our results show that hierarchical inverse dynamics controllers can be used for feedback control of humanoid robots and that momentum-based balance control can be efficiently implemented on a real robot.Comment: appears in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 201

Design and Implementation Of Vehicle Tracking System Using GPS

Surveillance system using phone line for security and tracking. Based on the above statement, it is targeted that this project will serve as good indication of how important it is to curb car theft in the country. Surveillance is specified to car alarm system and the means of sending the data to the owner of the vehicle using SMS when the alarm is triggered. Due to the inefficient conventional car security system, the possibility of the car can be stolen is high. The main reason is that the alarm is limited to the audible distance. Somehow if there is another way of transmitting the alarm to the car owner ,tracking the vehicle ,knowing the exactly that the car is been stolen at the same time that is not limited to the audible and line of sight, the system can be upgraded. SMS is a good choice of the communication to replace the conventional alarm, because it can be done and does not require much cost. Although most of people know  GPS can provide more security for the car but the main reason people does not apply it because the cost. Advance car security system is too expensive. Cost for the gadget is too high. Beside that, people also must pay for the service monthly. Tracking systems were first developed for the shipping industry because they wanted to determine where each vehicle was at any given time. Passive systems were developed in the beginning to fulfill these requirements. For the applications which require real time location information of the vehicle, these systems can't be employed because they save the location information in the internal storage and location information can only be accessed when vehicle is available. To achieve automatic Vehicle Location system that can transmit the location information in real time. Active systems are developed. Real time vehicular tracking system incorporates a hardware device installed in the vehicle (In-Vehicle Unit) and a remote Tracking server. The information is transmitted to Tracking server using GSM/GPRS modem on GSM network by using SMS or using direct TCP/IP connection with Tracking server through GPRS. Tracking server also has GSM/GPRS modem that receives vehicle location information via GSM network and stores this information in database. This information is available to authorized users of the system via website over the internet. Keywords: GPS,GPRS,Sensor

Real-time multitarget tracking for sensor-based sorting – A new implementation of the auction algorithm for graphics processing units

Utilizing parallel algorithms is an established way of increasing performance in systems that are bound to real-time restrictions. Sensor-based sorting is a machine vision application for which firm real-time requirements need to be respected in order to reliably remove potentially harmful entities from a material feed. Recently, employing a predictive tracking approach using multitarget tracking in order to decrease the error in the physical separation in optical sorting has been proposed. For implementations that use hard associations between measurements and tracks, a linear assignment problem has to be solved for each frame recorded by a camera. The auction algorithm can be utilized for this purpose, which also has the advantage of being well suited for parallel architectures. In this paper, an improved implementation of this algorithm for a graphics processing unit (GPU) is presented. The resulting algorithm is implemented in both an OpenCL and a CUDA based environment. By using an optimized data structure, the presented algorithm outperforms recently proposed implementations in terms of speed while retaining the quality of output of the algorithm. Furthermore, memory requirements are significantly decreased, which is important for embedded systems. Experimental results are provided for two different GPUs and six datasets. It is shown that the proposed approach is of particular interest for applications dealing with comparatively large problem sizes