19 research outputs found
Structured P2P Technologies for Distributed Command and Control
The utility of Peer-to-Peer (P2P) systems extends far beyond traditional file sharing. This paper provides an overview of how P2P systems are capable of providing robust command and control for Distributed Multi-Agent Systems (DMASs). Specifically, this article presents the evolution of P2P architectures to date by discussing supporting technologies and applicability of each generation of P2P systems. It provides a detailed survey of fundamental design approaches found in modern large-scale P2P systems highlighting design considerations for building and deploying scalable P2P applications. The survey includes unstructured P2P systems, content retrieval systems, communications structured P2P systems, flat structured P2P systems and finally Hierarchical Peer-to-Peer (HP2P) overlays. It concludes with a presentation of design tradeoffs and opportunities for future research into P2P overlay systems
Large-Scale Distributed Coalition Formation
The CyberCraft project is an effort to construct a large scale Distributed Multi-Agent System (DMAS) to provide autonomous Cyberspace defense and mission assurance for the DoD. It employs a small but flexible agent structure that is dynamically reconfigurable to accommodate new tasks and policies. This document describes research into developing protocols and algorithms to ensure continued mission execution in a system of one million or more agents, focusing on protocols for coalition formation and Command and Control. It begins by building large-scale routing algorithms for a Hierarchical Peer to Peer structured overlay network, called Resource-Clustered Chord (RC-Chord). RC-Chord introduces the ability to efficiently locate agents by resources that agents possess. Combined with a task model defined for CyberCraft, this technology feeds into an algorithm that constructs task coalitions in a large-scale DMAS. Experiments reveal the flexibility and effectiveness of these concepts for achieving maximum work throughput in a simulated CyberCraft environment
How To Touch a Running System
The increasing importance of distributed and decentralized software architectures entails more and more attention for adaptive software. Obtaining adaptiveness, however, is a difficult task as the software design needs to foresee and cope with a variety of situations. Using reconfiguration of components facilitates this task, as the adaptivity is conducted on an architecture level instead of directly in the code. This results in a separation of concerns; the appropriate reconfiguration can be devised on a coarse level, while the implementation of the components can remain largely unaware of reconfiguration scenarios.
We study reconfiguration in component frameworks based on formal theory. We first discuss programming with components, exemplified with the development of the cmc model checker. This highly efficient model checker is made of C++ components and serves as an example for component-based software development practice in general, and also provides insights into the principles of adaptivity. However, the component model focuses on high performance and is not geared towards using the structuring principle of components for controlled reconfiguration. We thus complement this highly optimized model by a message passing-based component model which takes reconfigurability to be its central principle.
Supporting reconfiguration in a framework is about alleviating the programmer from caring about the peculiarities as much as possible. We utilize the formal description of the component model to provide an algorithm for reconfiguration that retains as much flexibility as possible, while avoiding most problems that arise due to concurrency. This algorithm is embedded in a general four-stage adaptivity model inspired by physical control loops. The reconfiguration is devised to work with stateful components, retaining their data and unprocessed messages. Reconfiguration plans, which are provided with a formal semantics, form the input of the reconfiguration algorithm. We show that the algorithm achieves perceived atomicity of the reconfiguration process for an important class of plans, i.e., the whole process of reconfiguration is perceived as one atomic step, while minimizing the use of blocking of components. We illustrate the applicability of our approach to reconfiguration by providing several examples like fault-tolerance and automated resource control
Visual Data Association: Tracking, Re-identification and Retrieval
As there is a rapid development of the information society, large amounts of multimedia data are generated, which are shared and transferred on various electronic devices and the Internet every minute. Hence, building intelligent systems capable of associating these visual data at diverse locations and different times is absolutely essential and will significantly facilitate understanding and identifying where an object came from and where it is going. Thus, the estimated traces of motions or changes increasingly make it feasible to implement advanced algorithms to real-world applications, including human-computer interaction, robotic navigation, security in surveillance, biological characteristics association and civil structure vibration detection.
However, due to the inherent challenges, such as ambiguity, heterogeneity, noisy data, large-scale property and unknown variations, visual data association is currently far from being established. Therefore, this thesis focuses on the studies of associating visual data at diverse locations and different times for the tasks of tracking, re-identification and retrieval. More specifically, three situations including single camera, across multiple cameras and across multiple modalities have been investigated and four algorithms have been developed at different levels.
Chapter 3 The first algorithm is to explore an ensemble system for robust object tracking, primarily considering the independence of classifier members. An empirical analysis is firstly given to show that object tracking is a non-i.i.d. sampling, under-sample and incomplete-dataset problem. Then, a set of independent classifiers trained sequentially on different small datasets is dynamically maintained to overcome the particular machine learning problem. Thus, for every challenge, an optimal classifier can be approximated in a subspace spanned by the selected competitive classifiers.
Chapter 4 The second method is to improve the object tracking by exploiting a winner-take-all strategy to select the most suitable trackers. This topic naturally extends the concept of ensemble in the first topic to a more general idea: a multi-expert system, in which members come from different function spaces. Thus, the diversity of the system is more likely to be amplified. Based on a large public dataset, a prediction model of performance for different trackers on various challenges can be obtained off-line. Then, the learned structural regression model can be directly used to efficiently select the winner tracker online.
Chapter 5 The third one is to learn cross-view identities for fast person re-identification, in a cross-camera setting, which significantly differs from the single-view object tracking in the first two topics. Two sets of discriminative hash functions for two different views are learned by simultaneously minimising their distance in the Hamming space, and maximising the cross-covariance and margin. Thus, similar binary codes can be found for images of the same person captured at different views by embedding the images into the Hamming space.
Chapter 6 The fourth model is to develop a novel Hetero-manifold regularisation framework for efficient cross-modal retrieval. Compared with the first two settings, this is a more general and complex topic, in which the samples can be relaxed to the images captured in the very far distance or very long time, even to text, voice and other formats. Taking advantage of the hetero-manifold, the similarity between each pair of heterogeneous data could be naturally measured by three order random walks on this hetero-manifold.
It is concluded that, by fully exploiting the algorithms for solving the problems in the three situations, an integrated trace for an object moving anywhere can be definitely discovered
Technology 2003: The Fourth National Technology Transfer Conference and Exposition, volume 2
Proceedings from symposia of the Technology 2003 Conference and Exposition, Dec. 7-9, 1993, Anaheim, CA, are presented. Volume 2 features papers on artificial intelligence, CAD&E, computer hardware, computer software, information management, photonics, robotics, test and measurement, video and imaging, and virtual reality/simulation
Demystifying Internet of Things Security
Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms
Intelligent Sensor Networks
In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts