3,563 research outputs found
Cross-layer design of multi-hop wireless networks
MULTI -hop wireless networks are usually defined as a collection of nodes
equipped with radio transmitters, which not only have the capability to
communicate each other in a multi-hop fashion, but also to route each others’ data
packets. The distributed nature of such networks makes them suitable for a variety of
applications where there are no assumed reliable central entities, or controllers, and
may significantly improve the scalability issues of conventional single-hop wireless
networks.
This Ph.D. dissertation mainly investigates two aspects of the research issues
related to the efficient multi-hop wireless networks design, namely: (a) network
protocols and (b) network management, both in cross-layer design paradigms to
ensure the notion of service quality, such as quality of service (QoS) in wireless mesh
networks (WMNs) for backhaul applications and quality of information (QoI) in
wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of
this Ph.D. dissertation, different network settings are used as illustrative examples,
however the proposed algorithms, methodologies, protocols, and models are not
restricted in the considered networks, but rather have wide applicability.
First, this dissertation proposes a cross-layer design framework integrating
a distributed proportional-fair scheduler and a QoS routing algorithm, while using
WMNs as an illustrative example. The proposed approach has significant performance
gain compared with other network protocols. Second, this dissertation proposes
a generic admission control methodology for any packet network, wired and
wireless, by modeling the network as a black box, and using a generic mathematical
0. Abstract 3
function and Taylor expansion to capture the admission impact. Third, this dissertation
further enhances the previous designs by proposing a negotiation process,
to bridge the applications’ service quality demands and the resource management,
while using WSNs as an illustrative example. This approach allows the negotiation
among different service classes and WSN resource allocations to reach the optimal
operational status. Finally, the guarantees of the service quality are extended to
the environment of multiple, disconnected, mobile subnetworks, where the question
of how to maintain communications using dynamically controlled, unmanned data
ferries is investigated
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
A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks
In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs
A new QoS routing algorithm based on self-organizing maps for wireless sensor networks
For the past ten years, many authors have focused
their investigations in wireless sensor networks. Different
researching issues have been extensively developed: power
consumption, MAC protocols, self-organizing network algorithms,
data-aggregation schemes, routing protocols, QoS
management, etc. Due to the constraints on data processing
and power consumption, the use of artificial intelligence
has been historically discarded. However, in some special
scenarios the features of neural networks are appropriate to
develop complex tasks such as path discovery. In this paper,
we explore and compare the performance of two very well
known routing paradigms, directed diffusion and Energy-
Aware Routing, with our routing algorithm, named SIR,
which has the novelty of being based on the introduction of
neural networks in every sensor node. Extensive simulations
over our wireless sensor network simulator, OLIMPO, have
been carried out to study the efficiency of the introduction
of neural networks. A comparison of the results obtained
with every routing protocol is analyzed. This paper attempts
to encourage the use of artificial intelligence techniques in
wireless sensor nodes
Using artificial intelligence in routing schemes for wireless networks
For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have
been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing
protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has
been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks
such as path discovery. In this paper, we explore the performance of two very well-known routing paradigms, directed diffusion and
Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks
in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study
the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This
paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes
Multi-Layer Cyber-Physical Security and Resilience for Smart Grid
The smart grid is a large-scale complex system that integrates communication
technologies with the physical layer operation of the energy systems. Security
and resilience mechanisms by design are important to provide guarantee
operations for the system. This chapter provides a layered perspective of the
smart grid security and discusses game and decision theory as a tool to model
the interactions among system components and the interaction between attackers
and the system. We discuss game-theoretic applications and challenges in the
design of cross-layer robust and resilient controller, secure network routing
protocol at the data communication and networking layers, and the challenges of
the information security at the management layer of the grid. The chapter will
discuss the future directions of using game-theoretic tools in addressing
multi-layer security issues in the smart grid.Comment: 16 page
- …