TY - THES A1 - Klein, Alexander T1 - Performance Issues of MAC and Routing Protocols in Wireless Sensor Networks T1 - Leistungsbeschränkende Faktoren von MAC und Routingprotokollen in drahtlosen Sensornetzen N2 - The focus of this work lies on the communication issues of Medium Access Control (MAC) and routing protocols in the context of WSNs. The communication challenges in these networks mainly result from high node density, low bandwidth, low energy constraints and the hardware limitations in terms of memory, computational power and sensing capabilities of low-power transceivers. For this reason, the structure of WSNs is always kept as simple as possible to minimize the impact of communication issues. Thus, the majority of WSNs apply a simple one hop star topology since multi-hop communication has high demands on the routing protocol since it increases the bandwidth requirements of the network. Moreover, medium access becomes a challenging problem due to the fact that low-power transceivers are very limited in their sensing capabilities. The first contribution is represented by the Backoff Preamble-based MAC Protocol with Sequential Contention Resolution (BPS-MAC) which is designed to overcome the limitations of low-power transceivers. Two communication issues, namely the Clear Channel Assessment (CCA) delay and the turnaround time, are directly addressed by the protocol. The CCA delay represents the period of time which is required by the transceiver to detect a busy radio channel while the turnaround time specifies the period of time which is required to switch between receive and transmit mode. Standard Carrier Sense Multiple Access (CSMA) protocols do not achieve high performance in terms of packet loss if the traffic is highly correlated due to the fact that the transceiver is not able to sense the medium during the switching phase. Therefore, a node may start to transmit data while another node is already transmitting since it has sensed an idle medium right before it started to switch its transceiver from receive to transmit mode. The BPS-MAC protocol uses a new sequential preamble-based medium access strategy which can be adapted to the hardware capabilities of the transceivers. The protocol achieves a very low packet loss rate even in wireless networks with high node density and event-driven traffic without the need of synchronization. This makes the protocol attractive to applications such as structural health monitoring, where event suppression is not an option. Moreover, acknowledgments or complex retransmission strategies become almost unnecessary since the sequential preamble-based contention resolution mechanism minimizes the collision probability. However, packets can still be lost as a consequence of interference or other issues which affect signal propagation. The second contribution consists of a new routing protocol which is able to quickly detect topology changes without generating a large amount of overhead. The key characteristics of the Statistic-Based Routing (SBR) protocol are high end-to-end reliability (in fixed and mobile networks), load balancing capabilities, a smooth continuous routing metric, quick adaptation to changing network conditions, low processing and memory requirements, low overhead, support of unidirectional links and simplicity. The protocol can establish routes in a hybrid or a proactive mode and uses an adaptive continuous routing metric which makes it very flexible in terms of scalability while maintaining stable routes. The hybrid mode is optimized for low-power WSNs since routes are only established on demand. The difference of the hybrid mode to reactive routing strategies is that routing messages are periodically transmitted to maintain already established routes. However, the protocol stops the transmission of routing messages if no data packets are transmitted for a certain time period in order to minimize the routing overhead and the energy consumption. The proactive mode is designed for high data rate networks which have less energy constraints. In this mode, the protocol periodically transmits routing messages to establish routes in a proactive way even in the absence of data traffic. Thus, nodes in the network can immediately transmit data since the route to the destination is already established in advance. In addition, a new delay-based routing message forwarding strategy is introduced. The forwarding strategy is part of SBR but can also be applied to many routing protocols in order to modify the established topology. The strategy can be used, e.g. in mobile networks, to decrease the packet loss by deferring routing messages with respect to the neighbor change rate. Thus, nodes with a stable neighborhood forward messages faster than nodes within a fast changing neighborhood. As a result, routes are established through nodes with correlated movement which results in fewer topology changes due to higher link durations. N2 - Im Rahmen dieser Arbeit werden leistungsbeschränkende Faktoren von Medium Access Control (MAC) und Routingprotokollen im Kontext von drahtlosen Sensornetzen untersucht. Zunächst werden typische Probleme des Funkkanals diskutiert. Anschließend führen eine Einteilung von MAC Protokollen, sowie eine Gegenüberstellung relevanter Protokolle in die Thematik ein. Daraufhin werden hardwarelimitierende Faktoren und deren Auswirkung auf die Effizienz von Kanalzugriffsprotokollen untersucht. Des Weiteren wird das vom Autor entwickelte Backoff Preamble-based MAC Protokoll (BPS-MAC) vorgestellt, welches auf die limitierten Fähigkeiten sensortypischer Hardware eingeht und für dichte Sensornetze mit korreliertem Datenverkehr optimiert ist. Ein weiterer Schwerpunkt dieser Arbeit stellt das Thema Routing dar. Hier wird ebenfalls mit einer Einteilung der Protokolle in die Thematik eingeführt. Darüber hinaus werden die wichtigsten Aufgaben von Routingprotokollen vorgestellt. Ein Überblick über häufig verwendete Routingmetriken und Routingprotokolle schließen die Einführung in diesen Themenkomplex ab. Abschließend wird das im Rahmen der Dissertation entwickelte Statistic-Based-Routing (SBR) Protokoll vorgestellt, welches ebenfalls für drahtlose Sensornetze optimiert ist. Der letzte Schwerpunkt beschreibt die Problematik der Leistungsbewertung von Routingprotokollen hinsichtlich klassischer Leistungsparameter wie Paketverlust und Verzögerung. Ebenfalls werden weitere Leistungsparameter wie zum Beispiel die vom Nutzer wahrgenommene Netzqualität genauer untersucht. T3 - Würzburger Beiträge zur Leistungsbewertung Verteilter Systeme - 03/10 KW - Routing KW - Drahtloses Sensorsystem KW - Leistungsbewertung KW - Diskrete Simulation KW - MAC KW - Kanalzugriff KW - Medium KW - MAC KW - routing KW - sensor KW - networks KW - simulation Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-52870 ER - TY - THES A1 - Mäder, Andreas T1 - Performance Models for UMTS 3.5G Mobile Wireless Systems T1 - Leistungsmodelle für UMTS 3.5G Mobilfunksysteme N2 - Mobile telecommunication systems of the 3.5th generation (3.5G) constitute a first step towards the requirements of an all-IP world. As the denotation suggests, 3.5G systems are not completely new designed from scratch. Instead, they are evolved from existing 3G systems like UMTS or cdma2000. 3.5G systems are primarily designed and optimized for packet-switched best-effort traffic, but they are also intended to increase system capacity by exploiting available radio resources more efficiently. Systems based on cdma2000 are enhanced with 1xEV-DO (EV-DO: evolution, data-optimized). In the UMTS domain, the 3G partnership project (3GPP) specified the High Speed Packet Access (HSPA) family, consisting of High Speed Downlink Packet Access (HSDPA) and its counterpart High Speed Uplink Packet Access (HSUPA) or Enhanced Uplink. The focus of this monograph is on HSPA systems, although the operation principles of other 3.5G systems are similar. One of the main contributions of our work are performance models which allow a holistic view on the system. The models consider user traffic on flow-level, such that only on significant changes of the system state a recalculation of parameters like bandwidth is necessary. The impact of lower layers is captured by stochastic models. This approach combines accurate modeling and the ability to cope with computational complexity. Adopting this approach to HSDPA, we develop a new physical layer abstraction model that takes radio resources, scheduling discipline, radio propagation and mobile device capabilities into account. Together with models for the calculation of network-wide interference and transmit powers, a discrete-event simulation and an analytical model based on a queuing-theoretical approach are proposed. For the Enhanced Uplink, we develop analytical models considering independent and correlated other-cell interference. N2 - Die vorliegende Arbeit beschäftigt sich mit Mobilfunksystemen der Generation 3.5 im Allgemeinen, und mit den UMTS-spezifischen Ausprägungen HSDPA (High Speed Downlink Packet Access) und HSUPA (High Speed Uplink Packet Access) bzw. Enhanced Uplink im speziellen. Es werden integrierte Systeme betrachtet, d.h. 3.5G Datenkanäle koexistieren mit "klassischen" UMTS Datenkanälen wie in den Spezifikationen von UMTS Release ´99 beschrieben. T3 - Würzburger Beiträge zur Leistungsbewertung Verteilter Systeme - 02/08 KW - Mobilfunk KW - Leistungsbewertung KW - UMTS KW - HSPA KW - Funkressourcenverwaltung KW - Modellierungstechniken KW - Netzwerkplanung KW - UMTS KW - HSPA KW - radio resource management KW - modeling techniques KW - network planning Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-32525 ER - TY - THES A1 - Pries, Jan Rastin T1 - Performance Optimization of Wireless Infrastructure and Mesh Networks T1 - Leistungsoptimierung von drahtlosen Infrastruktur und Mesh Netzen N2 - Future broadband wireless networks should be able to support not only best effort traffic but also real-time traffic with strict Quality of Service (QoS) constraints. In addition, their available resources are scare and limit the number of users. To facilitate QoS guarantees and increase the maximum number of concurrent users, wireless networks require careful planning and optimization. In this monograph, we studied three aspects of performance optimization in wireless networks: resource optimization in WLAN infrastructure networks, quality of experience control in wireless mesh networks, and planning and optimization of wireless mesh networks. An adaptive resource management system is required to effectively utilize the limited resources on the air interface and to guarantee QoS for real-time applications. Thereby, both WLAN infrastructure and WLAN mesh networks have to be considered. An a-priori setting of the access parameters is not meaningful due to the contention-based medium access and the high dynamics of the system. Thus, a management system is required which dynamically adjusts the channel access parameters based on the network load. While this is sufficient for wireless infrastructure networks, interferences on neighboring paths and self-interferences have to be considered for wireless mesh networks. In addition, a careful channel allocation and route assignment is needed. Due to the large parameter space, standard optimization techniques fail for optimizing large wireless mesh networks. In this monograph, we reveal that biology-inspired optimization techniques, namely genetic algorithms, are well-suitable for the planning and optimization of wireless mesh networks. Although genetic algorithms generally do not always find the optimal solution, we show that with a good parameter set for the genetic algorithm, the overall throughput of the wireless mesh network can be significantly improved while still sharing the resources fairly among the users. N2 - Die Anbindung an das Internet erfolgt zunehmend über drahtlose Netze. Deren Ressourcen sind allerdings limitiert, was die Anzahl der unterstützten Nutzer stark einschränkt. Zudem ist ein Trend dieser Nutzer weg von der Verwendung reiner Datendienste zu Diensten mit Echtzeitanforderungen wie Voice over IP (VoIP) zu erkennen, deren Dienstgüteanforderungen eingehalten werden müssen. Heutige drahtlose Zugangsnetze sind jedoch nur für den herkömmlichen Datenverkehr ausgelegt. Der IEEE 802.11 WLAN Standard unterscheidet zwar zwischen verschiedenen Dienstklassen, gibt aber keine Dienstgütegarantien. Um die Dienstgüte (Quality of Service, QoS), bzw. die vom Nutzer erfahrene Dienstgüte (Quality of Experience, QoE) zu garantieren, müssen die zukünftigen drahtlosen Netze daher sorgfältig geplant und optimiert werden. Um die limitierten Ressourcen auf der Luftschnittstelle effektiv zu nutzen und um Dienstgüteanforderungen für Echtzeitanwendungen einzuhalten, bedarf es eines adaptiven Ressourcenmanagements. Dabei sind sowohl drahtlose Infrastruktur, als auch drahtlose Mesh-Netze zu betrachten. Durch den randomisierten Medienzugriff und die hohe Dynamik im System ist eine a-priori Wahl der Zugangsparameter nicht sinnvoll. Vielmehr wird ein Managementsystem benötigt, das die Zugangsparameter dynamisch in Abhängigkeit der Last in einem Netz wählt. Während dies für drahtlose Infrastrukturnetze ausreicht, müssen in drahtlosen Mesh-Netzen zusätzlich noch Interferenzen von Nachbarpfaden und Eigeninterferenzen berücksichtigt werden. Desweiteren ist eine sorgfältige Planung der Kanalzuweisung und des Routings notwendig, um einerseits den Durchsatz in drahtlosen Mesh-Netzen zu maximieren und andererseits die Ressourcen fair zwischen den Stationen aufzuteilen. Da es dabei eine Vielzahl von Parametern zu berücksichtigen gilt, sind neue Optimierungsmethoden notwendig, die es ermöglichen, auch große Mesh-Netze in annehmbarer Zeit zu planen und zu optimieren. Diese Doktorarbeit arbeitet die folgenden drei Optimierungsmöglichkeiten für drahtlose Zugangsnetze aus: Optimierung der Zugangsparameter in drahtlosen Infrastrukturnetzen, Optimierung von drahtlosen Mesh-Netzen unter Berücksichtigung der QoE und Planung und Optimierung von drahtlosen Mesh-Netzen mit Berücksichtigung einer fairen Ressourcenallokation. Die Ergebnisse und Untersuchungen dieser Arbeit gliedern sich entsprechend dieser Optimierungsmöglichkeiten. T3 - Würzburger Beiträge zur Leistungsbewertung Verteilter Systeme - 01/10 KW - IEEE 802.11 KW - Leistungsbewertung KW - Optimierung KW - Dienstgüte KW - Netzplanung KW - Drahtloses lokales Netz KW - WLAN KW - Mesh Netze KW - Genetische Optimierung KW - WLAN KW - Optimization KW - Mesh Networks KW - Genetic Optimization Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-46097 ER -