Recent technological advances in electronics, sensors, and communications have accelerated the widespread deployment of Unmanned Aircraft System (UAS)-aided applications. Nevertheless, networks composed of multiple UAS and ground stations, referred to as UAS-aided communications networks, have yet to receive sufficient research attention. In this paper, we address a fundamental research challenge stunting such networks, which is how to fairly maximize the energy efficiency (throughput per energy) in networks comprising adaptive modulation-capable ground nodes. For the mobility pattern intrinsic to the UASs, we demonstrate how adaptive modulation is affected. Furthermore, we formulate the problem of maximizing fair energy efficiency as a potential game that is played between the multiple ground nodes and substantiate its stability, optimality, and convergence. Based on the formulated potential game, a data collection method is proposed to maximize the energy efficiency with a fairness constraint. Additionally, we analyze the Price of Anarchy of our proposed game-theoretic data collection method. Extensive simulations exhibit the effectiveness of our proposal under varying environments.

Recent technological advances in electronics, sensors, and communications devices have facilitated the proliferation of Unmanned Aircraft System (UAS)-aided applications. However, the UAS-aided communications networks are yet to receive sufficient research endeavor. In this paper, we address one of the most important research challenges pertaining to UAS-aided networks comprising adaptive modulation-capable nodes, namely how to fairly maximize the energy efficiency (throughput per energy). For the mobility pattern innate to the UAS, we demonstrate how the adaptive modulation behaves. Furthermore, we formulate the problem as a potential game that is played between the UAS and the network-nodes, and prove its stability, optimality, and convergence. Based upon the potential game, a data collection method is envisioned to maximize the energy efficiency with the fairness constraint. Additionally, we analyze the Price of Anarchy (PoA) of our proposed game. Extensive simulations exhibit the effectiveness of our proposal under varying environments.

Power-aware routing in Wireless Sensor Networks (WSNs) is designed to adequately prolong the lifetime of severely resource-constrained ad hoc wireless sensor nodes}. Recent research has identified the energy hole problem in single sink-based WSNs, a characteristic of the many-to-one (convergecast) traffic patterns. In this paper, we propose HYbrid Multi-hop routiNg (HYMN) algorithm, which is a hybrid of the two contemporary multi-hop routing algorithm architectures, namely, flat multi-hop routing that utilizes efficient transmission distances, and hierarchical multi-hop routing algorithms that capitalizes on data aggregation. We provide rigorous mathematical analysis for HYMN-optimize it and model its power consumption. In addition, through extensive simulations, we demonstrate the effective performance of HYMN in terms of superior connectivity.

Power aware routing in Wireless Sensor Networks (WSNs) focuses on the crucial issue of extending the network lifetime of WSNs, which are limited by low capacity batteries. However, most of the previously proposed power aware routing algorithms have an inherent problem, which is the isolation of the sink node due to the quick power exhaustion of nodes that are close to the sink. In this paper, we propose a solution, referred to as HYbrid Multi-hop routiNg (HYMN), which addresses this problem by combining two routing strategies, namely flat multi-hop routing and hierarchical multi-hop routing. The former method aims at minimizing the total power consumption in the network while the latter attempts to decrease the amount of transferred data traffic by utilizing data compression. We present a mathematical analysis on the effect of the hybrid location on the performance of HYMN, and also demonstrate the effectiveness of HYMN through extensive simulations.