59 research outputs found
Energy Saving in QoS Fog-supported Data Centers
One of the most important challenges that cloud providers face in the explosive growth of data is to reduce the energy consumption of their designed, modern data centers. The majority of current research focuses on energy-efficient resources management in the infrastructure as a service (IaaS) model through "resources virtualization" - virtual machines and physical machines consolidation. However, actual virtualized data centers are not supporting communication–computing intensive real-time applications, big data stream computing (info-mobility applications, real-time video co-decoding). Indeed, imposing hard-limits on the overall per-job computing-plus-communication delays forces the overall networked computing infrastructure to quickly adopt its resource utilization to the (possibly, unpredictable and abrupt) time fluctuations of the offered workload.
Recently, Fog Computing centers are as promising commodities in Internet virtual computing platform that raising the energy consumption and making the critical issues on such platform. Therefore, it is expected to present some green solutions (i.e., support energy provisioning) that cover fog-supported delay-sensitive web applications. Moreover, the usage of traffic engineering-based methods dynamically keep up the number of active servers to match the current workload. Therefore, it is desirable to develop a flexible, reliable technological paradigm and resource allocation algorithm to pay attention the consumed energy. Furthermore, these algorithms could automatically adapt themselves to time-varying workloads, joint reconfiguration, and orchestration of the virtualized computing-plus-communication resources available at the computing nodes. Besides, these methods facilitate things devices to operate under real-time constraints on the allowed computing-plus-communication delay and service latency.
The purpose of this thesis is: i) to propose a novel technological paradigm, the Fog of Everything (FoE) paradigm, where we detail the main building blocks and services of the corresponding technological platform and protocol stack; ii) propose a dynamic and adaptive energy-aware algorithm that models and manages virtualized networked data centers Fog Nodes (FNs), to minimize the resulting networking-plus-computing average energy consumption; and, iii) propose a novel Software-as-a-Service (SaaS) Fog Computing platform to integrate the user applications over the FoE. The emerging utilization of SaaS Fog Computing centers as an Internet virtual computing commodity is to support delay-sensitive applications.
The main blocks of the virtualized Fog node, operating at the Middleware layer of the underlying protocol stack and comprises of: i) admission control of the offered input traffic; ii) balanced control and dispatching of the admitted workload; iii) dynamic reconfiguration and consolidation of the Dynamic Voltage and Frequency Scaling (DVFS)-enabled Virtual Machines (VMs) instantiated onto the parallel computing platform; and, iv) rate control of the traffic injected into the TCP/IP connection.
The salient features of this algorithm are that: i) it is adaptive and admits distributed scalable implementation; ii) it has the capacity to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rate of the traffic delivered to the client, instantaneous goodput and total processing delay; and, iii) it explicitly accounts for the dynamic interaction between computing and networking resources in order to maximize the resulting energy efficiency. Actual performance of the proposed scheduler in the presence of: i) client mobility; ii) wireless fading; iii) reconfiguration and two-thresholds consolidation costs of the underlying networked computing platform; and, iv) abrupt changes of the transport quality of the available TCP/IP mobile connection, is numerically tested and compared to the corresponding ones of some state-of-the-art static schedulers, under both synthetically generated and measured real-world workload traces
Telecommunications Networks
This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing
Opportunistic device-to-device communication in cellular networks: from theory to practice
MenciĂłn Internacional en el tĂtulo de doctorCellular service providers have been struggling with users’ demand since the emergence of mobile Internet. As a result, each generation of cellular network prevailed over its predecessors mainly in terms of connection speed. However, the fifth generation (5G) of cellular network promises to go beyond this trend by revolutionizing the network architecture. Device-to-Device (D2D) communication is one of the revolutionary changes that enables mobile users to communicate directly without traversing a base station. This feature is being actively studied in 3GPP with special focus on public safety as it allows mobiles to operate in adhoc mode. Although under the (partial) control of the network, D2D communications open the door to many other use-cases.
This dissertation studies different aspects of D2D communications and its impact on the key performance indicators of the network. We design an architecture for the collaboration of cellular users by means of timely exploited D2D opportunities. We begin by presenting the analytical study on opportunistic outband D2D communications. The study reveals the great potential of opportunistic outband D2D communications for enhancing energy efficiency, fairness, and capacity of cellular networks when groups of D2D users can be form and managed in the cellular network. Then we introduce a protocol that is compatible with the latest release of IEEE and
3GPP standards and allows for implementation of our proposal in a today’s cellular network. To validate our analytical findings, we use our experimental Software Defined Radio (SDR)-based testbed to further study our proposal in a real world scenario. The experimental results confirm the outstanding potential of opportunistic outband D2D communications. Finally, we investigate the performance merits and disadvantages of different D2D “modes”. Our investigation reveals, despite the common belief, that all D2D modes are complementary and their merits are scenario based.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en IngenierĂa TelemáticaPresidente: Douglas Leith.- Secretario: Albert Banchs Roca.- Vocal: Carla Fabiana Chiasserin
Efficient Passive Clustering and Gateways selection MANETs
Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets
Machine Learning for Unmanned Aerial System (UAS) Networking
Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale.
With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring.
This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS
Advanced Signal Processing Techniques for Two-Way Relaying Networks and Full-Duplex Communication Systems
Sehr hohe Datenraten und ständig verfügbare Netzabdeckung in
zukĂĽnftigen drahtlosen Netzwerken erfordern neue Algorithmen auf der
physischen Schicht. Die Nutzung von Relais stellt ein vielversprechendes
Verfahren dar, da die Netzabdeckung gesteigert werden kann. Zusätzlich
steht hierdurch im Vergleich zu Kupfer- oder Glasfaserleitungen eine
preiswerte Lösung zur Anbindung an die Netzinfrastruktur zur Verfügung.
Traditionelle Einwege-Relais-Techniken (One-Way Relaying [OWR]) nutzen
Halbduplex-Verfahren (HD-Verfahren), welche das Ăśbertragungssystem
ausbremst und zu spektralen Verlusten fĂĽhrt. Einerseits erlauben es
Zweiwege-Relais-Techniken (Two-Way Relaying [TWR]), simultan sowohl an das
Relais zu senden als auch von diesem zu empfangen, wodurch im Vergleich zu
OWR das Spektrum effizienter genutzt wird. Aus diesem Grunde untersuchen
wir Zweiwege-Relais und im Speziellen TWR-Systeme fĂĽr den
Mehrpaar-/Mehrnutzer-Betrieb unter Nutzung von Amplify-and-forward-Relais
(AF-Relais). Derartige Szenarien leiden unter Interferenzen zwischen Paaren
bzw. zwischen Nutzern. Um diesen Interferenzen Herr zu werden, werden
hochentwickelte Signalverarbeitungsalgorithmen – oder in anderen Worten
räumliche Mehrfachzugriffsverfahren (Spatial Division Multiple Access
[SDMA]) – benötigt. Andererseits kann der spektrale Verlust durch den
HD-Betrieb auch kompensiert werden, wenn das Relais im Vollduplexbetrieb
arbeitet. Nichtsdestotrotz ist ein FD-Gerät in der Praxis aufgrund starker
interner Selbstinterferenz (SI) und begrenztem Dynamikumfang des
Tranceivers schwer zu realisieren. Aus diesem Grunde sollten
fortschrittliche Verfahren zur SI-ĂśnterdrĂĽckung entwickelt werden. Diese
Dissertation trägt diesen beiden Zielen Rechnung, indem optimale und/oder
effiziente algebraische Lösungen entwickelt werden, welche verschiedenen
Nutzenfunktionen, wie Summenrate und minimale Sendeleistung, maximieren.Im
ersten Teil studieren wir zunächst Mehrpaar-TWR-Netzwerke mit einem
einzelnen Mehrantennen-AF-Relais. Dieser Anwendungsfall kann auch so
betrachtet werden, dass sich mehrere verschiedene Dienstoperatoren Relais
und Spektrum teilen, wobei verschiedene Nutzerpaare zu verschiedenen
Dienstoperatoren gehören. Aktuelle Ansätzen zielen auf
InterferenzunterdrĂĽckung ab. Wir schlagen ein auf Projektion basiertes
Verfahren zur Trennung mehrerer Dienstoperatoren (projection based
separation of multiple operators [ProBaSeMO]) vor. ProBaSeMO ist leicht
anpassbar fĂĽr den Fall, dass jeder Nutzer mehrere Antennen besitzt oder
unterschiedliche Systemdesignkriterien angewendet werden mĂĽssen. Als
BewertungsmaĂźstab fĂĽr ProBaSeMO entwickeln wir optimale Algorithmen zur
Maximierung der Summenrate, zur Minimierung der Sendeleistung am Relais
oder zur Maximierung des minimalen
Signal-zu-Interferenz-und-Rausch-Verhältnisses (Signal to Interference and
Noise Ratio [SINR]) am Nutzer. Zur Maximierung der Summenrate wurden
spezifische gradientenbasierte Methoden entwickelt, die unabhängig davon
sind, ob ein Nutzer mit einer oder mehr Antennen ausgestattet ist. Um im
Falle eines „Worst-Case“ immer noch eine polynomielle Laufzeit zu
garantieren, entwickelten wir einen Algorithmus mit polynomieller Laufzeit.
Dieser ist inspiriert von der „Polynomial Time Difference of Convex
Functions“-Methode (POTDC-Methode). Bezüglich der Summenrate des Systems
untersuchen wir zuletzt, welche Bedingungen erfĂĽllt sein mĂĽssen, um einen
Gewinn durch gemeinsames Nutzen zu erhalten. Hiernach untersuchen wir die
Maximierung der Summenrate eines Mehrpaar-TWR-Netzwerkes mit mehreren
Einantennen-AF-Relais und Einantennen-Nutzern. Das daraus resultierende
Problem der Summenraten-Maximierung, gebunden an eine bestimmte
Gesamtsendeleistung aller Relais im Netzwerk, ist ähnlich dem des
vorangegangenen Szenarios. Dementsprechend kann eine optimale Lösung für
das eine Szenario auch fĂĽr das jeweils andere Szenario genutzt werden.
Weiterhin werden basierend auf dem Polynomialzeitalgorithmus global
optimale Lösungen entwickelt. Diese Lösungen sind entweder an eine
maximale Gesamtsendeleistung aller Relais oder an eine maximale
Sendeleistung jedes einzelnen Relais gebunden. Zusätzlich entwickeln wir
suboptimale Lösungen, die effizient in ihrer Laufzeit sind und eine
Approximation der optimalen Lösung darstellen. Hiernach verlegen wir unser
Augenmerk auf ein Mehrpaar-TWR-Netzwerk mit mehreren Mehrantennen-AF-Relais
und mehreren Repeatern. Solch ein Szenario ist allgemeiner, da die
vorherigen beiden Szenarien als spezielle Realisierungen dieses Szenarios
aufgefasst werden können. Das Interferenz-Management in diesem Szenario
ist herausfordernder aufgrund der vorhandenen Repeater.
Interferenzneutralisierung (IN) stellt eine Lösung dar, um diese Art
Interferenz zu handhaben. Im Zuge dessen werden notwendige und ausreichende
Bedingungen zur Aufhebung der Interferenz hergeleitet. Weiterhin wird ein
Framework entwickelt, dass verschiedene Systemnutzenfunktionen optimiert,
wobei IN im jeweiligen Netzwerk vorhanden sein kann oder auch nicht. Dies
ist unabhängig davon, ob die Relais einer maximalen Gesamtsendeleistung
oder einer individuellen maximalen Sendeleistung unterliegen. Letztendlich
entwickeln wir ein Ăśbertragungsverfahren sowie ein Vorkodier- und
Dekodierverfahren fĂĽr Basisstationen (BS) in einem TWR-assistierten
Mehrbenutzer-MIMO-Downlink-Kanal. Im Vergleich mit dem
Mehrpaar-TWR-Netzwerk leidet dieses Szenario unter Interferenzen zwischen
den Kanälen. Wir entwickeln drei suboptimale Algorithmen, welche auf
Kanalinversion basieren. ProBaSeMO und „Zero-Forcing Dirty Paper
Coding“ (ZFDPC), welche eine geringe Zeitkomplexität aufweisen, schaffen
eine Balance zwischen Leistungsfähigkeit und Komplexität. Zusätzlich
gibt es jeweils nur geringe EinbrĂĽche in stark beanspruchten
Kommunikationssystemen.Im zweiten Teil untersuchen wir Techniken zur
SI-UnterdrĂĽckung, um den FD-Gewinn in einem Punkt-zu-Punkt-System
auszunutzen. Zunächst entwickeln wir ein Übertragungsverfahren, dass auf
SI RĂĽcksicht nimmt und die SI-UnterdrĂĽckung gegen den Multiplexgewinn
abwägt. Die besten Ergebnisse werden durch die perfekte Kenntnis des
Kanals erzielt, was praktisch nicht genau der Fall ist. Aus diesem Grund
werden Übertragungstechniken für den „Worst Case“ entwickelt, die den
Kanalschätzfehlern Rechnung tragen. Diese Fehler werden deterministisch
modelliert und durch Ellipsoide beschränkt. In praktischen Szenarien ist
der HF-Schaltkreise nicht perfekt. Dies hat Einfluss auf die Verfahren zur
SI-UnterdrĂĽckung und fĂĽhrt zu einer Restselbstinterferenz. Wir entwickeln
effiziente Ăśbertragungstechniken mittels Beamforming, welche auf dem
Signal-zu-Verlust-und-Rausch-Verhältnis (signal to leakage plus noise
ratio [SLNR]) aufbauen, um Unvollkommenheiten der HF-Schaltkreise
auszugleichen. Zusätzlich können alle Designkonzepte auf FD-OWR-Systeme
erweitert werden.To enable ultra-high data rate and ubiquitous coverage in future wireless
networks, new physical layer techniques are desired. Relaying is a
promising technique for future wireless networks since it can boost the
coverage and can provide low cost wireless backhauling solutions, as
compared to traditional wired backhauling solutions via fiber and copper.
Traditional one-way relaying (OWR) techniques suffer from the spectral loss
due to the half-duplex (HD) operation at the relay. On one hand, two-way
relaying (TWR) allows the communication partners to transmit to and/or
receive from the relay simultaneously and thus uses the spectrum more
efficiently than OWR. Therefore, we study two-way relays and more
specifically multi-pair/multi-user TWR systems with amplify-and-forward
(AF) relays. These scenarios suffer from inter-pair or inter-user
interference. To deal with the interference, advanced signal processing
algorithms, in other words, spatial division multiple access (SDMA)
techniques, are desired. On the other hand, if the relay is a full-duplex
(FD) relay, the spectral loss due to a HD operation can also be
compensated. However, in practice, a FD device is hard to realize due to
the strong loop-back self-interference and the limited dynamic range at the
transceiver. Thus, advanced self-interference suppression techniques should
be developed. This thesis contributes to the two goals by developing
optimal and/or efficient algebraic solutions for different scenarios
subject to different utility functions of the system, e.g., sum rate
maximization and transmit power minimization. In the first part of this
thesis, we first study a multi-pair TWR network with a multi-antenna AF
relay. This scenario can be also treated as the sharing of the relay and
the spectrum among multiple operators assuming that different pairs of
users belong to different operators. Existing approaches focus on
interference suppression. We propose a projection based separation of
multiple operators (ProBaSeMO) scheme, which can be easily extended when
each user has multiple antennas or when different system design criteria
are applied. To benchmark the ProBaSeMO scheme, we develop optimal relay
transmit strategies to maximize the system sum rate, minimize the required
transmit power at the relay, or maximize the minimum signal to interference
plus noise ratio (SINR) of the users. Specifically for the sum rate
maximization problem, gradient based methods are developed regardless
whether each user has a single antenna or multiple antennas. To guarantee a
worst-case polynomial time solution, we also develop a polynomial time
algorithm which has been inspired by the polynomial time difference of
convex functions (POTDC) method. Finally, we analyze the conditions for
obtaining the sharing gain in terms of the sum rate. Then we study the sum
rate maximization problem of a multi-pair TWR network with multiple single
antenna AF relays and single antenna users. The resulting sum rate
maximization problem, subject to a total transmit power constraint of the
relays in the network, yields a similar problem structure as in the
previous scenario. Therefore the optimal solution for one scenario can be
used for the other. Moreover, a global optimal solution, which is based on
the polyblock approach, and several suboptimal solutions, which are more
computationally efficient and approximate the optimal solution, are
developed when there is a total transmit power constraint of the relays in
the network or each relay has its own transmit power constraint. We then
shift our focus to a multi-pair TWR network with multiple multi-antenna AF
relays and multiple dumb repeaters. This scenario is more general because
the previous two scenarios can be seen as special realizations of this
scenario. The interference management in this scenario is more challenging
due to the existence of the repeaters. Interference neutralization (IN) is
a solution for dealing with this kind of interference. Thereby, necessary
and sufficient conditions for neutralizing the interference are derived.
Moreover, a general framework to optimize different system utility
functions in this network with or without IN is developed regardless
whether the AF relays in the network have a total transmit power limit or
individual transmit power limits. Finally, we develop the relay transmit
strategy as well as base station (BS) precoding and decoding schemes for a
TWR assisted multi-user MIMO (MU-MIMO) downlink channel. Compared to the
multi-pair TWR network, this scenario suffers from the co-channel
interference. We develop three suboptimal algorithms which are based on
channel inversion, ProBaSeMO and zero-forcing dirty paper coding (ZFDPC),
which has a low computational complexity, provides a balance between the
performance and the complexity, and suffers only a little when the system
is heavily loaded, respectively.In the second part of this thesis, we
investigate self-interference (SI) suppression techniques to exploit the FD
gain for a point-to-point MIMO system. We first develop SI aware transmit
strategies, which provide a balance between the SI suppression and the
multiplexing gain of the system. To get the best performance, perfect
channel state information (CSI) is needed, which is imperfect in practice.
Thus, worst case transmit strategies to combat the imperfect CSI are
developed, where the CSI errors are modeled deterministically and bounded
by ellipsoids. In real word applications, the RF chain is imperfect. This
affects the performance of the SI suppression techniques and thus results
in residual SI. We develop efficient transmit beamforming techniques, which
are based on the signal to leakage plus noise ratio (SLNR) criterion, to
deal with the imperfections in the RF chain. All the proposed design
concepts can be extended to FD OWR systems
Efficient Resource Management for Cloud Computing Environments
Cloud computing has recently gained popularity as a cost-effective model for hosting and delivering services over the Internet. In a cloud computing environment, a cloud provider packages its physical resources in data centers into virtual resources and offers them to service providers using a pay-as-you-go pricing model. Meanwhile, a service provider uses the rented virtual resources to host its services. This large-scale multi-tenant architecture of cloud computing systems raises key challenges regarding how data centers resources should be controlled and managed by both service and cloud providers.
This thesis addresses several key challenges pertaining to resource management in cloud environments. From the perspective of service providers, we address the problem of selecting appropriate data centers for service hosting with consideration of resource price, service quality as well as dynamic reconfiguration costs. From the perspective of cloud providers, as it has been reported that workload in real data centers can be typically divided into server-based applications and MapReduce applications with different performance and scheduling criteria, we provide separate resource management solutions for each type of workloads. For server-based applications, we provide a dynamic capacity provisioning scheme that dynamically adjusts the number of active servers to achieve the best trade-off between energy savings and scheduling delay, while considering heterogeneous resource characteristics of both workload and physical machines. For MapReduce applications, we first analyzed
task run-time resource consumption of a large variety of MapReduce jobs and discovered it can vary significantly over-time, depending on the phase the task is currently executing. We then present a novel scheduling algorithm that controls task execution at the level of phases with the aim of improving both job running time and resource utilization. Through detailed simulations and experiments using real cloud clusters, we have found our proposed solutions achieve substantial gain compared to current state-of-art resource management solutions, and therefore have strong implications in the design of real cloud resource management systems in practice
Efficient Resource Management for Cloud Computing Environments
Cloud computing has recently gained popularity as a cost-effective model for hosting and delivering services over the Internet. In a cloud computing environment, a cloud provider packages its physical resources in data centers into virtual resources and offers them to service providers using a pay-as-you-go pricing model. Meanwhile, a service provider uses the rented virtual resources to host its services. This large-scale multi-tenant architecture of cloud computing systems raises key challenges regarding how data centers resources should be controlled and managed by both service and cloud providers.
This thesis addresses several key challenges pertaining to resource management in cloud environments. From the perspective of service providers, we address the problem of selecting appropriate data centers for service hosting with consideration of resource price, service quality as well as dynamic reconfiguration costs. From the perspective of cloud providers, as it has been reported that workload in real data centers can be typically divided into server-based applications and MapReduce applications with different performance and scheduling criteria, we provide separate resource management solutions for each type of workloads. For server-based applications, we provide a dynamic capacity provisioning scheme that dynamically adjusts the number of active servers to achieve the best trade-off between energy savings and scheduling delay, while considering heterogeneous resource characteristics of both workload and physical machines. For MapReduce applications, we first analyzed
task run-time resource consumption of a large variety of MapReduce jobs and discovered it can vary significantly over-time, depending on the phase the task is currently executing. We then present a novel scheduling algorithm that controls task execution at the level of phases with the aim of improving both job running time and resource utilization. Through detailed simulations and experiments using real cloud clusters, we have found our proposed solutions achieve substantial gain compared to current state-of-art resource management solutions, and therefore have strong implications in the design of real cloud resource management systems in practice
Proceedings of the Third Edition of the Annual Conference on Wireless On-demand Network Systems and Services (WONS 2006)
Ce fichier regroupe en un seul documents l'ensemble des articles accéptés pour la conférences WONS2006/http://citi.insa-lyon.fr/wons2006/index.htmlThis year, 56 papers were submitted. From the Open Call submissions we accepted 16 papers as full papers (up to 12 pages) and 8 papers as short papers (up to 6 pages). All the accepted papers will be presented orally in the Workshop sessions. More precisely, the selected papers have been organized in 7 session: Channel access and scheduling, Energy-aware Protocols, QoS in Mobile Ad-Hoc networks, Multihop Performance Issues, Wireless Internet, Applications and finally Security Issues. The papers (and authors) come from all parts of the world, confirming the international stature of this Workshop. The majority of the contributions are from Europe (France, Germany, Greece, Italy, Netherlands, Norway, Switzerland, UK). However, a significant number is from Australia, Brazil, Canada, Iran, Korea and USA. The proceedings also include two invited papers. We take this opportunity to thank all the authors who submitted their papers to WONS 2006. You helped make this event again a success
- …