![]() We identify that the mixing parameter of Best Constant weights of a complete finite graph with an arbitrary order ensures the convergence in time-varying topologies without any reconfiguration of the edge weights. The presented theorems and lemmas are verified over evolving graphs with various parameters, whereby it is demonstrated that our approach ensures the convergence of the average consensus algorithm over mobile wireless sensor networks in spite of no edge reconfiguration.ฤก.1. information) have been becoming an increasingly valuable commodity in our technologically advanced society. However, possessing an unorganized large amount of data can be counterproductive to its owner therefore, the importance of data aggregation is gaining in importance nowadays. It is because data aggregation can ensure gathering and expressing a typically large data amount in a summary form appropriate for further processing/analyzing. Thus, data aggregation is an essential process not only in technical industries (e.g., wireless sensor networks (WSNs), the Internet of Things (IoT), etc.), but also in other fields, such as the financial sector, investments, travel industry, etc. ![]() In many modern multi-agent systems, data aggregation mechanisms are applied to process independently measured data from multiple sources that are often deployed in extensive geographical areas. ![]()
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