9,716 research outputs found
Energy-delay bounds analysis in wireless multi-hop networks with unreliable radio links
Energy efficiency and transmission delay are very important parameters for
wireless multi-hop networks. Previous works that study energy efficiency and
delay are based on the assumption of reliable links. However, the unreliability
of the channel is inevitable in wireless multi-hop networks. This paper
investigates the trade-off between the energy consumption and the end-to-end
delay of multi-hop communications in a wireless network using an unreliable
link model. It provides a closed form expression of the lower bound on the
energy-delay trade-off for different channel models (AWGN, Raleigh flat fading
and Nakagami block-fading) in a linear network. These analytical results are
also verified in 2-dimensional Poisson networks using simulations. The main
contribution of this work is the use of a probabilistic link model to define
the energy efficiency of the system and capture the energy-delay trade-offs.
Hence, it provides a more realistic lower bound on both the energy efficiency
and the energy-delay trade-off since it does not restrict the study to the set
of perfect links as proposed in earlier works
Performance Modelling and Optimisation of Multi-hop Networks
A major challenge in the design of large-scale networks is to predict and optimise the
total time and energy consumption required to deliver a packet from a source node to a
destination node. Examples of such complex networks include wireless ad hoc and sensor
networks which need to deal with the effects of node mobility, routing inaccuracies, higher
packet loss rates, limited or time-varying effective bandwidth, energy constraints, and the
computational limitations of the nodes. They also include more reliable communication
environments, such as wired networks, that are susceptible to random failures, security
threats and malicious behaviours which compromise their quality of service (QoS) guarantees.
In such networks, packets traverse a number of hops that cannot be determined
in advance and encounter non-homogeneous network conditions that have been largely
ignored in the literature. This thesis examines analytical properties of packet travel in
large networks and investigates the implications of some packet coding techniques on both
QoS and resource utilisation.
Specifically, we use a mixed jump and diffusion model to represent packet traversal
through large networks. The model accounts for network non-homogeneity regarding
routing and the loss rate that a packet experiences as it passes successive segments of a
source to destination route. A mixed analytical-numerical method is developed to compute
the average packet travel time and the energy it consumes. The model is able to capture
the effects of increased loss rate in areas remote from the source and destination, variable
rate of advancement towards destination over the route, as well as of defending against
malicious packets within a certain distance from the destination. We then consider sending
multiple coded packets that follow independent paths to the destination node so as to
mitigate the effects of losses and routing inaccuracies. We study a homogeneous medium
and obtain the time-dependent properties of the packet’s travel process, allowing us to
compare the merits and limitations of coding, both in terms of delivery times and energy
efficiency. Finally, we propose models that can assist in the analysis and optimisation
of the performance of inter-flow network coding (NC). We analyse two queueing models
for a router that carries out NC, in addition to its standard packet routing function. The
approach is extended to the study of multiple hops, which leads to an optimisation problem
that characterises the optimal time that packets should be held back in a router, waiting
for coding opportunities to arise, so that the total packet end-to-end delay is minimised
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
A Joint Model for IEEE 802.15.4 Physical and Medium Access Control Layers
Many studies have tried to evaluate wireless networks and especially the IEEE
802.15.4 standard. Hence, several papers have aimed to describe the
functionalities of the physical (PHY) and medium access control (MAC) layers.
They have highlighted some characteristics with experimental results and/or
have attempted to reproduce them using theoretical models. In this paper, we
use the first way to better understand IEEE 802.15.4 standard. Indeed, we
provide a comprehensive model, able more faithfully to mimic the
functionalities of this standard at the PHY and MAC layers. We propose a
combination of two relevant models for the two layers. The PHY layer behavior
is reproduced by a mathematical framework, which is based on radio and channel
models, in order to quantify link reliability. On the other hand, the MAC layer
is mimed by an enhanced Markov chain. The results show the pertinence of our
approach compared to the model based on a Markov chain for IEEE 802.15.4 MAC
layer. This contribution allows us fully and more precisely to estimate the
network performance with different network sizes, as well as different metrics
such as node reliability and delay. Our contribution enables us to catch
possible failures at both layers.Comment: Published in the proceeding of the 7th International Wireless
Communications and Mobile Computing Conference (IWCMC), Istanbul, Turkey,
201
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
- …