With the ever-growing presence of electronic devices that permeate the world we live in, enabling them to communicate with one another and share domain-specific information each device can provide has become the forefront of future technologies and solutions to every-day problems, making our life richer and helping the society to grow. The Internet of Things, as this network of computers and other devices is commonly referred to, is being constantly exposed to various solutions that aim to make it more coherent and simplify further advancement. One such solution to the problem of standardized interconnectedness is presented by the IEEE 802.15 working group, covering a large range of projects concerning the development of wireless personal networks and standards to which they should adhere. An important role is given to the way information is relayed through the network since in many cases distant devices are unable to communicate directly. For this purpose, various routing algorithms are being used and making them better is an active field of research. The Ad hoc On-Demand Distance Vector routing algorithm is a common target of experimentation, both because of its simplicity and because it is the preferred choice by many implementations of the IEEE 802.15 standards, such as Zigbee. However, it has its shortcomings, one of which is the fact that when generating routes it does not take into account any quality of service measurements. To address this, two modifications of the aforementioned routing protocol are specified, in the effort to enable the application of genetic programming as a tool for optimizing targeted quality of service measurements. In this thesis, a comprehensive study of these modifications is presented, as well as the distributed computer system that enables the optimization of two distinct targeted quality of service specifications.