371 research outputs found
Biologically inspired, self organizing communication networks.
PhDThe problem of energy-efficient, reliable, accurate and self-organized target tracking in
Wireless Sensor Networks (WSNs) is considered for sensor nodes with limited physical
resources and abrupt manoeuvring mobile targets. A biologically inspired, adaptive
multi-sensor scheme is proposed for collaborative Single Target Tracking (STT) and
Multi-Target Tracking (MTT). Behavioural data obtained while tracking the targets
including the targetsâ previous locations is recorded as metadata to compute the target
sampling interval, target importance and local monitoring interval so that tracking
continuity and energy-efficiency are improved. The subsequent sensor groups that track
the targets are selected proactively according to the information associated with the
predicted target location probability such that the overall tracking performance is
optimized or nearly-optimized. One sensor node from each of the selected groups is
elected as a main node for management operations so that energy efficiency and load
balancing are improved. A decision algorithm is proposed to allow the âconflictâ nodes
that are located in the sensing areas of more than one target at the same time to decide
their preferred target according to the target importance and the distance to the target. A
tracking recovery mechanism is developed to provide the tracking reliability in the
event of target loss.
The problem of task mapping and scheduling in WSNs is also considered. A
Biological Independent Task Allocation (BITA) algorithm and a Biological Task
Mapping and Scheduling (BTMS) algorithm are developed to execute an application
using a group of sensor nodes. BITA, BTMS and the functional specialization of the
sensor groups in target tracking are all inspired from biological behaviours of
differentiation in zygote formation.
Simulation results show that compared with other well-known schemes, the
proposed tracking, task mapping and scheduling schemes can provide a significant
improvement in energy-efficiency and computational time, whilst maintaining
acceptable accuracy and seamless tracking, even with abrupt manoeuvring targets.Queen Mary university of London full Scholarshi
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of todayâs industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
Throughput-Optimal Random Access with Order-Optimal Delay
In this paper, we consider CSMA policies for scheduling of multihop wireless
networks with one-hop traffic. The main contribution of this paper is to
propose Unlocking CSMA (U-CSMA) policy that enables to obtain high throughput
with low (average) packet delay for large wireless networks. In particular, the
delay under U-CSMA policy becomes order-optimal. For one-hop traffic, delay is
defined to be order-optimal if it is O(1), i.e., it stays bounded, as the
network-size increases to infinity. Using mean field theory techniques, we
analytically show that for torus (grid-like) interference topologies with
one-hop traffic, to achieve a network load of , the delay under U-CSMA
policy becomes as the network-size increases, and hence,
delay becomes order optimal. We conduct simulations for general random
geometric interference topologies under U-CSMA policy combined with congestion
control to maximize a network-wide utility. These simulations confirm that
order optimality holds, and that we can use U-CSMA policy jointly with
congestion control to operate close to the optimal utility with a low packet
delay in arbitrarily large random geometric topologies. To the best of our
knowledge, it is for the first time that a simple distributed scheduling policy
is proposed that in addition to throughput/utility-optimality exhibits delay
order-optimality.Comment: 44 page
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Delay performance in random-access grid networks
We examine the impact of torpid mixing and meta-stability issues on the delay
performance in wireless random-access networks. Focusing on regular meshes as
prototypical scenarios, we show that the mean delays in an toric
grid with normalized load are of the order . This
superlinear delay scaling is to be contrasted with the usual linear growth of
the order in conventional queueing networks. The intuitive
explanation for the poor delay characteristics is that (i) high load requires a
high activity factor, (ii) a high activity factor implies extremely slow
transitions between dominant activity states, and (iii) slow transitions cause
starvation and hence excessively long queues and delays. Our proof method
combines both renewal and conductance arguments. A critical ingredient in
quantifying the long transition times is the derivation of the communication
height of the uniformized Markov chain associated with the activity process. We
also discuss connections with Glauber dynamics, conductance and mixing times.
Our proof framework can be applied to other topologies as well, and is also
relevant for the hard-core model in statistical physics and the sampling from
independent sets using single-site update Markov chains
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
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
ATAMM enhancement and multiprocessing performance evaluation
The algorithm to architecture mapping model (ATAAM) is a Petri net based model which provides a strategy for periodic execution of a class of real-time algorithms on multicomputer dataflow architecture. The execution of large-grained, decision-free algorithms on homogeneous processing elements is studied. The ATAAM provides an analytical basis for calculating performance bounds on throughput characteristics. Extension of the ATAMM as a strategy for cyclo-static scheduling provides for a truly distributed ATAMM multicomputer operating system. An ATAAM testbed consisting of a centralized graph manager and three processors is described using embedded firmware on 68HC11 microcontrollers
Analytical characterization of inband and outband D2D Communications for network access
MenciĂłn Internacional en el tĂtulo de doctorCooperative short-range communication schemes provide powerful tools to solve interference
and resource shortage problems in wireless access networks. With such schemes, a mobile node
with excellent cellular connectivity can momentarily accept to relay traffic for its neighbors experiencing
poor radio conditions and use Device-to-Device (D2D) communications to accomplish
the task. This thesis provides a novel and comprehensive analytical framework that allows evaluating
the effects of D2D communications in access networks in terms of spectrum and energy
efficiency. The analysis covers the cases in which D2D communications use the same bandwidth
of legacy cellular users (in-band D2D) or a different one (out-band D2D) and leverages on the
characterization of underlying queueing systems and protocols to capture the complex intertwining
of short-range and legacy WiFi and cellular communications.
The analysis also unveils how D2D affects the use and scope of other optimization techniques
used for, e.g., interference coordination and fairness in resource distribution. Indeed, characterizing
the performance of D2D-enabled wireless access networks plays an essential role in the optimization
of system operation and, as a consequence, permits to assess the general applicability of
D2D solutions. With such characterization, we were able to design several mechanisms that improve
system capabilities. Specifically, we propose bandwidth resource management techniques
for controlling interference when cellular users and D2D pairs share the same spectrum, we design
advanced and energy-aware access selection mechanisms, we show how to adopt D2D communications
in conjunction with interference coordination schemes to achieve high and fair throughputs,
and we discuss on end-to-end fairnessâbeyond the use of access network resourcesâwhen
D2D communications is adopted in C-RAN. The results reported in this thesis show that identifying
performance bottlenecks is key to properly control network operation, and, interestingly,
bottlenecks may not be represented just by wireless resources when end-to-end fairness is of
concern.Programa Oficial de Doctorado en IngenierĂa TelemĂĄticaPresidente: Marco Ajmone Marsan.- Secretario: Miquel PayarĂł Llisterri.- Vocal: Omer Gurewit
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