Interference in ad hoc wireless networks causes the performance of traditional networking protocols to suffer. However, some user applications in ad hoc networks demand high throughput and low end-user delay. In the literature, the backpressure policy, i.e. queue backlog differential-based joint routing and scheduling, is known to be throughput-optimal with robust support for traffic load fluctuations \cite{Tssailus92}. Unfortunately, many backpressure-based algorithms cannot be implemented due to high end-user delay, inaccurate assumptions for interference, and high control overhead in distributed scenarios. We develop new backpressure based approaches to address these issues. We first propose a heuristic packet forwarding scheme that solves the issue of high end-user delay and still provides near-optimal throughput. Next we develop a novel interference model that provides simple yet accurate interference relationships among users. Such a model is helpful in designing a simple backpressure scheduling algorithm that does not violate realistic interference constraints. Finally we develop distributed backpressure algorithms based on our proposed ideas. Our distributed algorithms provide throughput performance close to the optimal and have low control overhead and simple implementation. / Master of Science

Freshness of information has become of high importance with the emergence of many real- time applications like monitoring systems and communication networks. The main idea behind all of these scenarios is the same, there exists at least a monitor of some process to which the monitor does not have direct access. Rather, the monitor indirectly receives updates over time from a source that can observe the process directly. The common main goal in these scenarios is to guarantee that the updates at the monitor side are as fresh as possible. However, due to the contention among the nodes in the network over limited channel resources, it takes some random time for the updates before they are received by the monitor. These applications have motivated a line of research studying the Age of Information (AoI) as a new performance metric that captures timeliness of information. The first part of this dissertation focuses on the AoI problem in general multi-source multi-hop status update networks with slotted transmissions. Fundamental lower bounds on the instantaneous peak and average AoI are derived under general interference constraints. Explicit algorithms are developed that generate scheduling policies for status update dissem- ination throughout the network for the class of minimum-length periodic schedules under global interference constraints. Next, we study AoI in multi-access channels, where a number of sources share the same server with exponentially distributed service times to communicate to a monitor. Two cases depending on the status update arrival rates at the sources are considered: (i) random arrivals based on the Poisson point process, and (ii) active arrivals where each source can generate an update at any point in time. For each case, closed-form expressions are derived for the average AoI as a function of the system parameters. Next, the effect of energy harvesting on the age is considered in a single-source single- monitor status update system that has a server with a finite battery capacity. Depending on the server’s ability to harvest energy while a packet is in service, and allowing or blocking the newly-arriving packets to preempt a packet in service, average AoI expressions are derived. The results show that preemption of the packets in service is sub-optimal when the energy arrival rate is lower than the status update arrival rate. Finally, the age of channel state information (CSI) is studied in fully-connected wire- less networks with time-slotted transmissions and time-varying channels. A framework is developed that accounts for the amount of data and overhead in each packet and the CSI disseminated in the packet. Lower bounds on the peak and average AoI are derived and a greedy protocol that schedules the status updates based on minimizing the instantaneous average AoI is developed. Achievable average AoI is derived for the class of randomized CSI dissemination schedules.

Die Besonderheit der drahtlosen Kommunikation gegenüber den drahtgebundenen Netzwerken liegt im drahtlosen Übertragungsmedium. Aufgrund der Broadcast-Eigenschaft des Übertragungsmediums werden Nachrichten potentiell von allen Netzwerkstationen empfangen, welche sich in der Übertragungsreichweite des Senders aufhalten. Als Konsequenz können bei einem unsynchronisierten Medienzugriff mehrere Nachrichten beim Empfänger kollidieren und nicht korrekt empfangen werden. Dieses Phänomen wird auch als Interferenz bezeichnet. Um solche Interferenzen zu vermeiden, wurden spezielle Protokolle für den Medienzugriff in drahtlosen Netzen entwickelt. Ein solcher Ansatz für drahtlose Maschennetze ist die verteilte Kanalzuweisung. Bei der verteilten Kanalzuweisung werden sich nicht-überlappende Kanäle im verfügbaren Frequenzspektrum für Übertragungen verwendet, die auf dem gleichen Kanal Interferenzen erzeugen würden. Dieser Ansatz ist möglich, da die verwendeten Funktechnologien, wie zum Beispiel IEEE 802.11 (WLAN), mehrere nicht-überlappende Kanäle bereitstellen. Aufgrund der großen Verbreitung von IEEE 802.11, ist eine hohe Dichte von privaten wie kommerziellen Netzen im urbanen Raum die Norm. Diese räumlich überlappenden Netze konkurrieren um den Medienzugriff. Daher ist es für die Leistung von Kanalzuweisungsalgorithmen von großer Bedeutung, die Aktivität der externen Netze mit einzubeziehen. Die Leistung der vorgelegten Arbeit umfasst das Design, die Implementierung und Validierung von Modellen und Algorithmen zur Reduzierung von Interferenzen in drahtlosen Maschennetzen. Die Arbeit beinhaltet die Entwicklung eines Messungs-basierten Interferenzmodells, mit dem Interferenzabhängigkeiten der Maschenrouter untereinander effizient bestimmt werden können. Weiterhin wurde ein Algorithmus für die verteilte Kanalzuweisung entwickelt, der die Aktivität von externen Netzen berücksichtigt. Die Gesamtlösung wurde in einem großen drahtlosen Maschennetz experimentell validiert. / Due to the broadcast nature of the shared medium, wireless transmissions are potentially received by all network stations in the communication range of the sender. With an unsynchronized medium access, multiple transmissions may be active at the same time and thus interfere with each other. In consequence, multiple transmissions may collide at the receiver side and cannot be properly decoded. For this reason, protocols have been developed on the MAC layer to synchronize the medium access and thus reduce interference effects. One of these approaches in wireless mesh networks is channel assignment. The idea of channel assignment is to minimize the network-wide interference by utilizing non-overlapping channels for otherwise interfering wireless transmissions. This is feasible, since wireless mesh routers are usually equipped with multiple radios and commonly used wireless network technologies, such as IEEE 802.11, provide multiple non-overlapping channels. Since IEEE 802.11 operates in the unlicensed frequency spectrum, the dense distribution of private and commercial network deployments of WLANs in urban areas poses a new challenge. Co-located networks compete for the wireless medium, thus decreasing the achievable network performance in terms of throughput and latency. Therefore, an important issue for efficient channel assignment is to also address external interference The contributions of this dissertation comprise the design, implementation, and validation of models and algorithms to enable wireless multi-hop networks to become interference-aware. This includes a measurement-based interference model suitable for large-scale network deployments. A distributed channel assignment algorithm has been developed that considers external sources of interference. The overall solution has been experimentally validated in a large-scale wireless multi-hop multi-radio testbed and has significantly increased the network performance with regard to the network capacity.