Real-time control and management of distributed applications using ip-multicast

Abstract A central issue within any distributed computer environment is how to control and manage running applications. This paper presents an implementation of a framework for control and management of distributed applications and components using IPmulticast. The framework allows for easy and scalable control of single applications, groups of applications or parts of applications using a new agent based architecture. Messaging is done using the Control Bus and the Scalable Reliable Real-time Transfer Protocol for reliable distribution of data. The paper presents how this framework is integrated into Java based applications and how developers specify access points. The paper also presents an application called multicast Manager -mManager, a Java implementation that provides a user interface to the framework. The mManager allows administrators to get an overview of currently running applications and if necessary control these applications. The paper presents example usage scenarios where the framework is used to create bandwidth adaptive applications and better group awareness

Automatic Annotation for Human Activity Recognition in Free Living Using a Smartphone

Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, especially in the case of online and personalized approaches requiring user specific datasets to be labeled. The availability of such datasets has the potential to help address common problems of smartphone-based HAR, such as inter-person variability. In this work, we present (i) an automatic labeling method facilitating the collection of labeled datasets in free-living conditions using the smartphone, and (ii) we investigate the robustness of common supervised classification approaches under instances of noisy data. We evaluated the results with a dataset consisting of 38 days of manually labeled data collected in free living. The comparison between the manually and the automatically labeled ground truth demonstrated that it was possible to obtain labels automatically with an 80–85% average precision rate. Results obtained also show how a supervised approach trained using automatically generated labels achieved an 84% f-score (using Neural Networks and Random Forests); however, results also demonstrated how the presence of label noise could lower the f-score up to 64–74% depending on the classification approach (Nearest Centroid and Multi-Class Support Vector Machine)

Creating digital life stories through activity recognition with image filtering

Abstract. This paper presents two algorithms that enables the MemoryLane system to support persons with mild dementia through creation of digital life stories. The MemoryLane system consists of a Logging Kit that captures context and image data, and a Review Client that recognizes activities and enables review of the captured data. The image filtering algorithm is based on image characteristics such as brightness, blurriness and similarity, and is a central component of the Logging Kit. The activity recognition algorithm is based on the captured contextual data together with concepts of persons and places. The initial results indicate that the MemoryLane system is technically feasible and that activity-based creation of digital life stories for persons with mild dementia is possible

mMOD: the multicast Media-on-Demand system

This paper presents the multicast Media-onDemand system, mMOD, which is an on-demand system designed for recording and playback of not only audio and video but also other media that are being multicast on the Internet/MBone today. The system allows for users to request playback of recorded sessions containing MBone audio, video, whiteboard, NetText, mWeb (a distributed HTML presentation system) or any other UDP-multicast distributed session. It also allows for random access within these recordings. The system include a Web-interface for starting and controlling running sessions. To compensate for jitter and out-of-order packets, sessions distributed in RTPformat (RFC1889), can be reconstructed with new time-stamps. 1 Introduction A video-on-demand system (VOD) is a system that serves a number of clients with audio and video on their request, and that are usually limited to these two media. Normally one channel is allocated per request and receiver and this leads to resources being ti..

Real-Time Control and Management of Distributed Applications using IP-Multicast

A central issue within any distributed computer environment is how to control and manage installed software and running applications. With control and management, we mean both how to make permanent changes to installed software and real-time control of running applications. This paper presents a framework for control and management of distributed applications and components using IP-multicast. The framework allows for easy and scalable control of single applications, groups of applications or parts of applications using a new agent based architecture. Messaging is done using the Control Bus and the Scalable Reliable Real-time Transfer Protocol for reliable distribution of data. The paper also presents an application called multicast Manager - mManager, a prototype Java implementation that provides a user interface to the framework. The mManager allows administrators to get an overview of currently running applications and if necessary control these applications. The framework includes ..

Improving Wi-Fi based Indoor Positioning using Particle Filter based on Signal Strength

Indoor positioning is recognized as one of the upcoming major applications which can be used in wide variety of applications such as indoor navigation and enterprise asset tracking. The significance of localization in indoor environments have made the use of Wi-Fi based indoor positioning so that it can utilize available current wireless infrastructure and perform positioning very easily. In this paper we introduced a user friendly prototype for Wi-Fi based indoor positioning system where a user can identify its own position in indoor. Wi-Fi received signal strength (RSS) fluctuations over time introduce incorrect positioning To minimize the fluctuation of RSS, we developed Particle Filters with the prototype. A comparison between with and without Particle Filter for error performance is presented and at the same time it is also noticed that variation in number of particles could change the positioning accuracy. Moreover comparison between calibration data in all directions and in one direction while constructing a radio map is presented