A Survey of Distributed Data Aggregation Algorithms,” University of Minho

Distributed data aggregation is an important task, allowing the de-centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val-ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many different approaches have been pro-posed, with different trade-offs in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag-gregation algorithms, it can be difficult and time consuming to determine which techniques will be more appropriate to use in specific settings, jus-tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally defines the concept of aggrega-tion, characterizing the different types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal char-acteristics.