In low-altitude Internet of Things (IoT) systems, uncrewed aerial vehicles (UAVs) are increasingly deployed as agile and distributed platforms. In scenarios where infrastructure support is limited or unavailable, UAVs can form ad hoc networks that enable flexible and self-organizing communication, making them well-suited for delivering real-time edge intelligence. A key challenge in such UAV ad hoc networks lies in edge server placement to ensure low-latency data transmission while balancing the computation load among servers. In this article, we provide insights into the design of UAV ad hoc network-assisted IoT systems by characterizing the tradeoff between data transmission latency and computational load. To this end, we formulate a bi-objective optimization problem that jointly minimizes the worst-case transmission latency and the load imbalance, subject to constraints on edge UAV server selection and data assignment. To solve this problem, we propose a directed-evolution nondominated sorting genetic algorithm (DNSGA) that removes conventional crossover operations and incorporates two problem-specific heuristics: 1) a $K$ -means-based task assignment module to reduce latency, and 2) an efficiency-driven load migration strategy to balance server-side workloads. Simulation results verify that the proposed DNSGA converges significantly faster than nondominated sorting genetic algorithm II (NSGA-II), while providing a more diverse set of nondominated solutions with up to 13.3% broader result range. Compared to multiobjective particle swarm optimization (MOPSO), DNSGA achieves up to 18.8% reduction in worst-case latency, and compared to NSGA-II, it reduces the load imbalance by up to 41.2%. These advantages highlight its effectiveness for high-efficiency UAV ad hoc network-assisted IoT systems.

To tackle the address aggregation problem for Low Earth Orbit (LEO) satellite communication system, a global geographical Internet Protocol (IP) subnet division model for space-ground integrated network addressing scheme is proposed in this paper. A two-dimensional spherical coordinate system based on spherical distance is applied to describe the LEO satellite track and the location information of geographical subnet zone. A mathematical framework for abnormal addressing users is constructed under the system. The size and division of geographical zone influence the expectation of abnormal user number through the ratio of logically covered and fully covered time. When the terrestrial regions are divided into small cells, the number of abnormal users reduces, as well as the partial routing cost. The simulation results confirm that the ratio of logically covered and fully covered time increase and the number of abnormal users decreases when the size of ground cells declines. The origin regions could be divided into smaller ground cells in order to reduce abnormal addressing users, balancing the cost on partial routing mechanism, mobility management, and satellite routing table items. The work presented a solution and direction of addressing scheme and mobility management design for the space-terrestrial hybrid network.

Low-Earth-Orbit (LEO) satellite networks are a hotspot in the communication industry as they can provide global high-capacity and low-latency communication services. However, the constellation system’s high construction cost and limited resources like computation and storage, coupled with the uneven distribution of ground communication users, make it essential to optimize the constellation configuration to match the uneven communication needs of different regions. This paper focuses on the Walker-Delta configuration constellation and uses a global approximate equal-area partition method to establish the terrestrial communication population distribution model. A constellation configuration optimization method is proposed to match the uneven distribution of global communication users. This paper mathematically characterizes the relationship between the change rule of the constellation’s coverage with latitude and the orbital parameters to obtain the model of the visible satellite number for ground users at any latitude under any constellation configuration. The terrestrial communication population distribution model is constructed based on global population data, and the Spearman correlation coefficient (SCC) is used to measure the match between the constellation coverage performance and the global communication user distribution. With the constellation coverage model, this paper optimizes the constellation configuration. Compared with the core layer of Starlink phase I, the SCC of the optimized constellation proposed in this paper is improved by 29.5%. A program simulation is carried out, and the results indicate that the network access capacity of the optimized constellation is improved by 12.6% compared to the Starlink phase I. The load balancing degree is improved by 25.9%, and the packet loss rate is reduced by 66.6%.

Due to the global coverage and real-time access advantages of the Tracking and Data Relay Satellite System (TDRSS), the demonstration platform based on TDRSS can satisfy the new technology verification and demonstration needs of the space information network (evolution from sensorweb). However, the comprehensive evaluation research of this demonstration platform faces many problems: complicated and diverse technical indicators in various areas, coupling redundancy between indicators, difficulty in establishing the number of indicator system layers, and evaluation errors causing by subjective scoring. Concerning the difficulties, this paper gives a method to construct this special index system, and improves the consistency of evaluation results with Analytic Hierarchy Process in Group Decision-Making (AHP-GDM). A comprehensive evaluation index system including five criterions, 11 elements, more than 30 indicators is constructed according to the three-step strategy of initial set classification, hierarchical optimization, and de-redundancy. For the inconsistent scoring of AHP-GDM, a high-speed convergence consistency improvement strategy is proposed in this paper. Moreover, a method for generating a comprehensive judgment matrix (the aggregation of each judgment matrix) aggregation coefficient is provided. Numerical experiments show that this strategy effectively improves the consistency of the comprehensive judgment matrix. Finally, taking the evaluation of TDRSS development as an example, the versatility and feasibility of the new evaluation strategy are demonstrated.

The geographic information-based subnet partitioning scheme provides the basis for satellite-ground integrated addressing. Meanwhile, this scheme will inevitably cause addressing abnormal users (AAUs), i.e., the satellite which has address convergence relationship with users’ co-subnet and the satellite which users actual access to may be different. This problem will decrease the network communication efficiency. With the aim of quantifying the statistical variation pattern of AAUs to reduce the impact, this paper constructs a statistical model of AAUs under the general closed geographic partition shape. Further, considering the orbit characteristics and the uniform rotation of Earth, this paper derives an analytic formula for the average addressing abnormal user rate (AAUR) under circle and polygon geographic partition. Meanwhile, by simulating a specific LEO satellite constellation, this paper obtains the temporal average of AAUR in spherical trapezoidal partition during one orbital period, which is sufficiently approximated to the result of analytic formula, verifying the validity of this model. The model shows that the average of the AAUR decreases gradually as the ratio of satellite coverage area to geographic partition area increases. When the ratio is greater than 1.6, the average AAUR is less than 5%. The research work in this thesis quantifies the relationship between the average of the AAUR and satellite to earth communication range, geographic subnet range, geographic subnet shape, which can provide a reference for the matching design of geographic partitioning under any constellation configuration.