A Taxonomy of Self-configuring Service Discovery Systems

We analyze the fundamental concepts and issues in service discovery. This analysis places service discovery in the context of distributed systems by describing service discovery as a third generation naming system. We also describe the essential architectures and the functionalities in service discovery. We then proceed to show how service discovery fits into a system, by characterizing operational aspects. Subsequently, we describe how existing state of the art performs service discovery, in relation to the operational aspects and functionalities, and identify areas for improvement

Exploiting web technologies to build autonomic wireless sensor networks

Most of the current wireless sensor networks are built for specific applications, with a tight coupling between them and the underlying communication protocols. We present a more flexible architectural approach for building WSNs, in which application-specific features are decoupled from the underlying communication infrastructure, although affecting the network behavior. We propose a framework based on Web technologies that provides a standard interface for accessing the network and configurable service components tailored to meet different application requirements, while optimizing the network scarce resources. Also, a set of ontologies is defined as part of the framework for representing shared knowledge of the WSN domain.8th IFIP/IEEE International conference on Mobile and Wireless CommunicationRed de Universidades con Carreras en Informática (RedUNCI

Secure and Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks

This chapter discusses the need of security and privacy protection mechanisms in aggregation protocols used in wireless sensor networks (WSN). It presents a comprehensive state of the art discussion on the various privacy protection mechanisms used in WSNs and particularly focuses on the CPDA protocols proposed by He et al. (INFOCOM 2007). It identifies a security vulnerability in the CPDA protocol and proposes a mechanism to plug that vulnerability. To demonstrate the need of security in aggregation process, the chapter further presents various threats in WSN aggregation mechanisms. A large number of existing protocols for secure aggregation in WSN are discussed briefly and a protocol is proposed for secure aggregation which can detect false data injected by malicious nodes in a WSN. The performance of the protocol is also presented. The chapter concludes while highlighting some future directions of research in secure data aggregation in WSNs.Comment: 32 pages, 7 figures, 3 table

Self-Configuration and Self-Optimization Process in Heterogeneous Wireless Networks

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network’s scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed

Air Force Institute of Technology Research Report 2007

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Transferability of Car-Following Models Between Driving Simulator and Field Traffic

During the past few decades, there have been two parallel streams of driving behavior research: models using trajectory data collected from the field (using video recordings, GPS, etc.) and models using data from driving simulators (in which the behavior of the drivers is recorded in controlled laboratory conditions). Although the former source of data is more realistic, it lacks information about the driver and is typically not suitable for testing effects of future vehicle technologies and traffic scenarios. In contrast, driving behavior models developed with driving simulator data may lack behavioral realism. However, no previous study has compared these two streams of mathematical models and investigated the transferability of the models developed with driving simulator data to real field conditions in a rigorous manner. The current study aimed to fill this research gap by investigating the transferability of two car-following models between a driving simulator and two comparable real-life traffic motorway scenarios, one from the United Kingdom and the other one from the United States. In this regard, stimulus–response–based car-following models were developed with three microscopic data sources: (a) experimental data collected from the University of Leeds driving simulator, (b) detailed trajectory data collected from UK Motorway 1, and (c) detailed trajectory data collected from Interstate 80 in California. The parameters of these car-following models were estimated by using the maximum likelihood estimation technique, and the transferability of the models was investigated by using statistical tests of parameter equivalence and transferability test statistics. Estimation results indicate transferability at the model level but not fully at the parameter level for both pairs of scenarios