6,379 research outputs found

    Collecting and Analyzing Failure Data of Bluetooth Personal Area Networks

    Get PDF
    This work presents a failure data analysis campaign on Bluetooth Personal Area Networks (PANs) conducted on two kind of heterogeneous testbeds (working for more than one year). The obtained results reveal how failures distribution are characterized and suggest how to improve the dependability of Bluetooth PANs. Specically, we dene the failure model and we then identify the most effective recovery actions and masking strategies that can be adopted for each failure. We then integrate the discovered recovery actions and masking strategies in our testbeds, improving the availability and the reliability of 3.64% (up to 36.6%) and 202% (referred to the Mean Time To Failure), respectively

    In-Network Distributed Solar Current Prediction

    Get PDF
    Long-term sensor network deployments demand careful power management. While managing power requires understanding the amount of energy harvestable from the local environment, current solar prediction methods rely only on recent local history, which makes them susceptible to high variability. In this paper, we present a model and algorithms for distributed solar current prediction, based on multiple linear regression to predict future solar current based on local, in-situ climatic and solar measurements. These algorithms leverage spatial information from neighbors and adapt to the changing local conditions not captured by global climatic information. We implement these algorithms on our Fleck platform and run a 7-week-long experiment validating our work. In analyzing our results from this experiment, we determined that computing our model requires an increased energy expenditure of 4.5mJ over simpler models (on the order of 10^{-7}% of the harvested energy) to gain a prediction improvement of 39.7%.Comment: 28 pages, accepted at TOSN and awaiting publicatio

    Active security vulnerability notification and resolution

    Get PDF
    The early version of the Internet was designed for connectivity only, without the consideration of security, and the Internet is consequently an open structure. Networked systems are vulnerable for a number of reasons; design error, implementation, and management. A vulnerability is a hole or weak point that can be exploited to compromise the security of the system. Operating systems and applications are often vulnerable because of design errors. Software vendors release patches for discovered vulnerabilities, and rely upon system administrators to accept and install patches on their systems. Many system administrators fail to install patches on time, and consequently leave their systems vulnerable to exploitation by hackers. This exploitation can result in various security breaches, including website defacement, denial of service, or malware attacks. The overall problem is significant with an average of 115 vulnerabilities per week being documented during 2005. This thesis considers the problem of vulnerabilities in IT networked systems, and maps the vulnerability types into a technical taxonomy. The thesis presents a thorough analysis of the existing methods of vulnerability management which determine that these methods have failed to mange the problem in a comprehensive way, and show the need for a comprehensive management system, capable of addressing the awareness and patch deploymentp roblems. A critical examination of vulnerability databasess tatistics over the past few years is provided, together with a benchmarking of the problem in a reference environment with a discussion of why a new approach is needed. The research examined and compared different vulnerability advisories, and proposed a generic vulnerability format towards automating the notification process. The thesis identifies the standard process of addressing vulnerabilities and the over reliance upon the manual method. An automated management system must take into account new vulnerabilities and patch deploymentt o provide a comprehensives olution. The overall aim of the research has therefore been to design a new framework to address these flaws in the networked systems harmonised with the standard system administrator process. The approach, known as AVMS (Automated Vulnerability Management System), is capable of filtering and prioritising the relevant messages, and then downloading the associated patches and deploying them to the required machines. The framework is validated through a proof-of-concept prototype system. A series of tests involving different advisories are used to illustrate how AVMS would behave. This helped to prove that the automated vulnerability management system prototype is indeed viable, and that the research has provided a suitable contribution to knowledge in this important domain.The Saudi Government and the Network Research Group at the University of Plymouth

    Approximate Decoding Approaches for Network Coded Correlated Data

    Get PDF
    This paper considers a framework where data from correlated sources are transmitted with help of network coding in ad-hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth bottlenecks. We first show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples about the possible of our algorithms that can be deployed in sensor networks and distributed imaging applications. In both cases, the experimental results confirm the validity of our analysis and demonstrate the benefits of our low complexity solution for delivery of correlated data sources
    • …
    corecore