Consensus-based local data aggregation in wireless sensor networks under node failures and transmission-power-based topology control

In wireless sensor networks (WSNs), transmission power adjustment has a direct impact on both node-level energy expenditure and overall network lifetime, while simultaneously shaping the communication conditions under which distributed data aggregation must operate. This coupling is especially important in energy-constrained settings with progressive node failures, where topology control affects not only connectivity but also the reliability of local information exchange. In this paper, we formulate the problem of distributed data aggregation in a WSN with strict local-information constraints, where nodes communicate only through one-hop broadcasts and adapt their transmission power according to the LINT protocol. The resulting communication graph is degree-regularized but not necessarily bidirectional, which makes the design and evaluation of aggregation protocols substantially different from the classical fixed-topology consensus setting. Within this formulation, we investigate the interplay between adaptive transmission power control and decentralized aggregation by comparing two local aggregation protocols, Metropolis and the Local Voting Protocol (LVP), under both adaptive-range and fixed-range communication regimes. Our contribution is twofold. First, we provide a problem formulation for joint adaptive communication and distributed aggregation in locally informed, energy-constrained WSNs. Second, using a simulation framework with a standard radio energy model, probabilistic reporting to a base station, and multiple node deployment scenarios, we show that the relative performance of aggregation protocols depends on the communication regime induced by power adjustment. In particular, Metropolis is competitive, and in some cases preferable, under fixed-range symmetric communication, whereas LVP yields more stable aggregation quality under LINT-based adaptive transmission power control while maintaining comparable network lifetime and energy efficiency.