Using Geographic Location for Optimal Service Selection

Nowadays, a multitude of functionally equal web services are available. By thisbroad offer, the need of a service recommendation based on non-functional characteristics(e.g. price, response time, availability) is increasing. The static ServiceLevel Agreements (SLAs) of service providers cannot suffice this need. SLAs arenot reliable enough, due to the fact that they do not cover the dynamic performanceand quality changes of services during their lifetime. This bachelor’s thesis waswritten within a research project of the Linnaeus University in Sweden and the KarlsruheUniversity of Applied Science in Germany. The goal of this research projectis to eliminate the issues as described above. For this reason, a framework for anoptimized service selection was developed. Instead of using the static SLAs, measurementsof each service call are taken. On the basis of the measurements and therequirements of the consumer, the framework then provides an automated best-fitservice selection. The purpose of this thesis is to involve the geographic location of each serviceconsumer in the automated service selection. Therefore, a mobile app was developedto get a sufficient amount of real world test data. This app measures service calls andadditionally records the geographic location of the user. Based on the geographiclocation, the collected measurement data then were grouped into regions. Thereby,it could be shown that the geographic location of the user can be used to improve theoptimal service selection.Service-Oriented Computin