Methodologies for Comparing Clustering Algorithms in Wireless Sensor Networks
This paper presents general methodologies for comparing distributed algorithms, which are exemplified by clustering algorithms in sensor networks. Significant metrics for evaluating the algorithms are introduced including aspects of a structural, analytical and simulative comparison. Finally a short, exemplary comparison of two clustering algorithms HEED and WCA is made. In some practical areas a large-scale, non-invasive observation of physical or ecological state variables like temperature, air pressure or movement is necessary. Wired sensors are an inappropriate technology in such scenarios. This motivates the usage of tiny wireless sensor nodes. These devices are forming large, self-organizing Wireless Sensor Networks (WSN) transferring sensed data to predefined base stations.