Fast Timescale Traffic Engineering in MPLS Networks

Traffic engineering can be used to solve congestion through efficient traffic distribution. The network with differentiated classes of service is the main focus in this work. In general, providers offer QoS guaranteed in high priority class by serving the packets from that class before the packets from low-priority class. This strategy will work as long as the high priority traffic share is low (5-10%). We are interested in increasing that high priority traffic share. However, the large share of high priority class could lead to a QoS-violation risk. Moreover, it could decrease the goodput of the low-priority traffic as a result of its elastic nature, for example, from the congestion control in TCP. We present two works based on the fast timescale traffic engineering. The first work focuses on the flow migration among the parallel working paths. The potential usefulness of fast timescale migration control is explored with packet-level simulation and experimental testbed. The migration can improve the QoS of real-time traffic by shifting some of the flows out of the congested links. In the design of the migration controller, we will also consider the interaction between the controller and the TCP congestion control mechanism. We formulate the partially observed Markov Decision Process (MDP) problem and solve it using the dynamic programming technique. To cope with the well-known curse of dimensionality, we also present sub-optimal controllers, which scale well with our large network. Our second work tried to exploit the unused backup path for QoS improvement. Many network providers already setup a backup path for each working path. This backup path will protect the working path upon its failure. Without any failures, the providers fill the backup path with lower-priority traffic to increase their network's throughput. In general, the backup paths will not be used for high priority traffic in normal condition even with the congestion situation of the high priority traffic. We propose the scheme to duplicate the high priority packets to backup path in the congestion condition. With a small throughput degradation of low-priority traffic, we could gain significant QoS improvement of high priority class

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

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

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications