6,379 research outputs found
Collecting and Analyzing Failure Data of Bluetooth Personal Area Networks
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
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
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
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
- …