<p>In this thesis centralized routing methods for wireless sensor networks have been studied. The aim has been to prolong network lifetime by reducing the energy consumed by sensor-node communication.</p><p>Wireless sensor networks are rapidly becoming common in application areas where information from many sensors is to be collected and acted upon. The use of wireless sensor networks adds flexibility to the network, and the cost of cabling can be avoided.</p><p>Wireless sensor networks may consist of several hundreds of small devices, equipped with sensors (e.g. acoustic, seismic or image) that form a wireless network. Each sensor node collects information from its surroundings and sends it to a base station, either from sensor node to sensor node, or directly to the base station.</p><p>We have made simulations that show that asymmetric communication with multihop extends the lifetime of large wireless sensor networks. We have also investigated the usefulness of enforcing a minimum separation distance between cluster heads in a cluster based wireless sensor network. The results show that our sensor network performs up to 150% better when introducing a minimum separation distance between cluster heads. The simulations also show that the minimum separation distance resulting in the lowest energy consumption in our network varies with the number of clusters. We have also made an initial study of maximum lifetime routing in sparse wireless sensor networks to be able to see how different heuristic routing algorithms influence the energy consumption of individual sensor nodes, and thus the lifetime of a sparse sensor network. We have also compared the maximum lifetime of the heuristic algorithms to the maximum lifetime of an optimal routing solution. These simulations showed that for some types of applications the choice of heuristic algorithm is more important to prolong network lifetime, than for other types of applications.</p>

In this thesis centralized routing methods for wireless sensor networks have been studied. The aim has been to prolong network lifetime by reducing the energy consumed by sensor-node communication. Wireless sensor networks are rapidly becoming common in application areas where information from many sensors is to be collected and acted upon. The use of wireless sensor networks adds flexibility to the network, and the cost of cabling can be avoided. Wireless sensor networks may consist of several hundreds of small devices, equipped with sensors (e.g. acoustic, seismic or image) that form a wireless network. Each sensor node collects information from its surroundings and sends it to a base station, either from sensor node to sensor node, or directly to the base station. We have made simulations that show that asymmetric communication with multihop extends the lifetime of large wireless sensor networks. We have also investigated the usefulness of enforcing a minimum separation distance between cluster heads in a cluster based wireless sensor network. The results show that our sensor network performs up to 150% better when introducing a minimum separation distance between cluster heads. The simulations also show that the minimum separation distance resulting in the lowest energy consumption in our network varies with the number of clusters. We have also made an initial study of maximum lifetime routing in sparse wireless sensor networks to be able to see how different heuristic routing algorithms influence the energy consumption of individual sensor nodes, and thus the lifetime of a sparse sensor network. We have also compared the maximum lifetime of the heuristic algorithms to the maximum lifetime of an optimal routing solution. These simulations showed that for some types of applications the choice of heuristic algorithm is more important to prolong network lifetime, than for other types of applications.

Internet of Things utvecklas och växer konstant. Det blir allt vanligare att applikationer och enheter kopplas samman via nätverk. En av teknikerna som används för att trådlöst sammankoppla enheter är Bluetooth Low Energy. Preferenser för kvaliteten i en kommunikation kan variera. Det är därför viktigt att utföra prestandamätningar för att veta vilka fördelar och nackdelar en nätverksteknik har.  Detta examensarbete handlar om prestandamätningar vid datasändningar mellan mobila enheter och trådlösa sensorer, och övervakning av parametrar som fås under mätningarna. En metod med monitoreringspaket inspirerad från tidigare forskning, utformades och implementerades i ett system för Bluetooth Low Energy, vilken därefter har utvärderats.  Resultatet blev att två system skapades som visade dataförluster, fördröjningsvariation och genomströmning, löpande på en mobil enhet. Det ena systemet använde metoden med monitoreringspaket. Det andra systemet använde en egengjord metod som gjorde mätningar med hög precision, men som ställde högre krav på funktioner och prestanda på sensornoden, och på den mobila enheten. Experiment med hjälp av systemen utfördes och resulterande värden analyserades. / Internet of Things develops and grows constantly. It becomes increasingly common that applications and units are connected through a network. One of the technologies used for wirelessly linking together units is Bluetooth Low Energy. Preferences for the quality of a connection can vary. It is therefore important to conduct measurements of performance in order to know advantages and disadvantages that a networking technology has.  This thesis is about measurements of performance during data transfers between mobile devices and wireless sensors, as well as monitoring parameters that are given during the measurements. One method using monitoring packets inspired from previously made research, were designed and implemented in a system for Bluetooth Low Energy, which was then evaluated. The result was that two systems were created that presented data loss, delay variation and throughput, continuously on a mobile device. One system used the method with monitoring packets. The other system used a self-made method which made measurements with high precision, but that places higher demands on functions and performance of the sensor node, and on the mobile device. Experiments were conducted by using the systems and resulting values were analyzed.