Mobile networks have rapidly evolved over decades, and have arrived at the fifth generation (5G) system in recent years. From 2019, companies started to bring 5G networks into business, providing higher data rates, lower latency, and larger network capacity to the world. One of the main advancements in 5G network systems is the use of millimetre waves for wireless transmission. This not only grants higher throughput with wide bandwidth but also introduces new challenges to the radio access networks in 5G systems. To tackle the challenges, a new type of network, which is called the Integrated Access and Backhaul (IAB) network, has been proposed as a deployment solution for 5G cellular networks. In this work, we investigate the routing mechanism of an IAB network and propose a novel load balancing algorithm that can be applied to the IAB network for improvement in throughput as well as load distribution. We extend the work from previous studies on IAB networks and evaluate the performance of the proposed algorithm in comparison to previous work. Through radio network simulations, we find that the shortest path routing outperforms a greedy algorithm in terms of path selection in the network and that the proposed algorithm achieves load balancing among the network, combined with an improvement in the user throughput. Finally, we conclude our work and suggest directions for future work in the study of IAB networks. / Mobilnäten har utvecklats snabbt de senaste decennierna och är nu framme vid femte generationens system (5G). Under 2019 började telekomföretag lansera 5G-nätverk, med högre datahastigheter, lägre fördröjningar och högre nätverkskapacitet. Ett av de största framstegen inom 5G-nätverkssystem är användningen av millimetervågor för trådlös överföring. Detta ger högre datahastigheter och större bandbredd, men leder också till nya utmaningar för radioaccessnätverket. För att hantera några av dessa har en ny typ av nätverk, kallat Integrated Access and Backhaul (IAB) föreslagits. I det här arbetet undersöker vi routingmekanismer för ett IAB-nätverk och föreslår en ny lastbalanseringsalgoritm som kan användas för att förbättra såväl genomströmning som lastfördelning. Arbetet är en utvidgning av tidigare studier av IAB-nätverk och jämför prestanda för den nya algoritmen med tidigare förslag. Genom simuleringar har vi funnit att shortest path routing överträffar en ”greedy” algoritm när det gäller vägval i nätverket och att den föreslagna algoritmen uppnår såväl lastbalansering som förbättrad genomströmning. Avslutningsvis ges förlag till fortsatt arbete inom studiet av IAB-nätverk.

Denna rapport behandlar en undersökning av olika lastbalanseringsalgoritmer i Linux Virtual Server. Undersökningen har gjorts i ett webbkluster (Apache var webbservern som användes) med tre heterogena noder, där operativsystemet var den detalj som skiljde dem åt. Operativsystemen som ingick i undersökningen var Windows Server 2008 R2, CentOS 6.2 och FreeBSD 9.0. De faktorer som undersöktes mellan de olika algoritmerna var klustrets genomsnittliga svarstid vid olika belastning och hur många anslutningar som kunde hanteras av klustret, detta gjordes med verktyget httperf. Undersökningen ger svar på hur ett heterogent webbklusters genomsnittligasvarstid och arbetskapacitet kan skilja sig åt beroende på vilken algoritm som används för lastbalansering. Resultatet visar att den genomsnittliga svarstiden håller sig låg tills en hastig stigning inträffar. Shortest Expected Delay och Weighted Least-Connection Scheduling kunde hantera störst antal anslutningar. / This report covers an investigation of different load balancing algorithms in Linux Virtual Server. The investigation was done in a web cluster (with Apache as the software being used) consisting of three heterogeneous nodes, where the operating system was the detail that differentiated the nodes. The operating systems that were used in the investigation were Windows Server 2008 R2, CentOS 6.2 and FreeBSD 9.0. The factors examined were average response time at different load and how many connections the cluster could cope with, these factors were examined by measurements taken with the tool httperf. The investigation gives an answer to how a heterogeneous web clustersaverage response time and working capacity can be affected by the choice of load balancing algorithm. The result shows that the average response time stays low until a sudden rise occurs. Shortest Expected Delay and Weighted Least-Connection Scheduling could handle the largest number of connections.

Edge cloud is a distributed computing architecture that is growing in popularity. It aims to bring the cloud closer to the edge of a network, reducing latency and improving performance through the use of distributed servers (edge nodes) spread out geographically. However, in the case of sudden increases in user requests, a node may run short of resources and need to implement a strategy that allows the node's service to degrade its service quality to a level that requires fewer resources so that the service can still be delivered. One such strategy is brownout, a control theory-based algorithm that dynamically controls the node's service quality in order to meet e.g., a latency goal. This thesis explores the use of brownout, previously used in combination with load balancing in the cloud, in conjunction with load balancing in an edge-cloud environment. In this thesis, four load-balancing strategies are evaluated in a Kubernetes-based edge-cloud environment, along with an application that implements the brownout feature. Two of the strategies are originally designed to be used with brownout but made for the regular cloud, one is a recently introduced strategy that performs well in the edge cloud but is brownout unaware, and the last is a random load balancer used as a baseline (also brownout unaware). The goal of the evaluation is to determine the efficiency of these strategies in different edge-cloud scenarios, with regard to service quality-weighted throughput, average latency, adherence to a set latency goal, and outsourcing (requests load balanced to another edge node). The results show that the first two strategies perform worse than the random load balancer in many regards. Their performance is also less predictable and tends to get worse with increasing network delays. The edge cloud strategy, however, shows an improvement in performance when the brownout is introduced in the majority of the test scenarios.  Furthermore, the thesis introduced three possible modifications to make one of the cloud-based strategies perform better in the edge cloud. These modifications were tested in the same environment as the other load-balancing strategies and compared against each other. The first modification consisted of making the load-balancing logic treat its own node differently from other edge nodes.  The second version was devised to only outsource when a certain resource threshold is exceeded and the last version was designed to prioritize its own node when below a certain resource threshold. The last version improved on the others and performed better than the base version in all measured metrics. Compared to the edge cloud strategy with brownout, it performed better with regard to service quality-weighted throughput but was outperformed in all other metrics.

Uninterrupted network connectivity is vital for real-time and mission-critical communication networks. The failure of Base Stations due to unforeseen circumstances such as natural disasters or emergencies can affect the coverage and capacity provided by terrestrial communication networks. The use of Unmanned Aerial Vehicles (UAVs) or drones in cellular networks is an upcoming area of research interest in 5G where the public sector and the communication service providers are fervently discussing it. The drones can be rapidly deployed to bridge the gaps in coverage or capacity of the network due to unforeseen circumstances. This thesis explores drone base stations' use for a simple hexagonal cell deployment scenario where the deployable base stations replace two failed macro base stations to improve the mean network capacity. Simulations show that the introduction of the deployable base stations indeed helps improve mean network capacity in case of one or multiple macro base station fail. The Genetic Algorithm is used to achieve Pareto optimality between downlink and uplink capacity of the simulated network. The simulation results show that introducing deployable nodes in a network can improve the network's capacity while also giving near-optimal transmit power values. / Oavbruten nätverksanslutning är avgörande för realtids- och missionskritiska kommunikationsnätverk. Fel på basstationer på grund av oförutsedda omständigheter som naturkatastrofer eller nödsituationer kan påverka täckningen och kapaciteten som tillhandahålls av markbundna kommunikationsnätverk. Användningen av Unmanned Aerial Vehicles (UAV) eller drönare i cellulära nätverk är ett kommande område av forskningsintresse inom 5G där den offentliga sektorn och leverantörerna av kommunikationstjänster ivrigt diskuterar det. Drönarna kan snabbt sättas in för att överbrygga klyftorna i nätverkets täckning eller kapacitet på grund av oförutsedda omständigheter. Denna avhandling utforskar drönarbasstationers användning för ett enkelt scenarie för hexagonal celldistribution där de utplacerbara basstationerna ersätter två misslyckade makrobasstationer för att förbättra den genomsnittliga nätverkskapaciteten. Simuleringar visar att introduktionen av de utplacerbara basstationerna verkligen hjälper till att förbättra den genomsnittliga nätverkskapaciteten i händelse av att en eller flera makrobasstationer misslyckas. Den genetiska algoritmen används för att uppnå Pareto-optimalitet mellan nedlänks- och upplänkkapaciteten i det simulerade nätverket. Simuleringsresultaten visar att införandet av utplacerbara noder i ett nätverk kan förbättra nätverkets kapacitet samtidigt som det ger nästan optimala värden för sändningseffekt.

Controlling the balance of production and consumption of electricity will become increasingly challenging as the transport sector gradually converts to electric vehicles along with a growing share of wind power in the Swedish electric power system. This puts greater demand on resources that maintain the balance to ensure stable grid operation. The balancing act is called frequency regulation which historically has been performed almost entirely by hydropower. As the power production becomes more intermittent with renewable energy sources, frequency regulation will need to be performed in higher volumes on the demand side by having a more flexible consumption. In this report, the electrification of 17 buses Svealandstrafiken bus depot in Västerås has been studied. The aim has been to assess different charging strategies to efficiently utilize the available time and power but also to investigate if Svealandstrafiken can participate in frequency regulation. A smart charging model was created that demonstrated how smart charging can be implemented to optimize the charging in four different cases. The simulated cases were: charging with load balancing, reduced charging power, frequency regulation, and electrifying more buses. The results show that the power capacity limit will be exceeded if the buses are being charged directly as they arrive at the depot and without scheduling the charging session. By implementing smart charging, Svealandstrafiken can fully charge the 17 buses within the power capacity limit of the depot with 82 minutes to spare. By utilizing this 82-minute margin in the four different charging strategies, it was found that Svealandstrafiken can save 88 200SEK per year by load balancing, save 30 000 SEK per year by reducing the charging power by 10 %, earn 111 900 SEK per year by frequency regulation or electrify five more buses. Reducing the charging power may also increase the lifetime of the batteries but quantifying this needs further studies. Conclusively, there is economic potential for Svealandstrafiken for implementing smart charging.