Featuring wide coverage and high data rate, LEO satellite networks will be an important supplement to the traditional terrestrial networks, enabling the space-air-ground integrated network service. However, effective load balancing routing strategies for LEO satellite networks need to be designed, due to the bursty characteristic of the network traffic and imbalanced regional communication load. To achieve that, we propose a Distance-based Back-Pressure Routing (DBPR) strategy for LEO satellite networks. DBPR calculates the link weights based on a novel distance-based metric, which can select uncongested short-distance paths to the destinations and distribute network traffic dynamically with low delay. To control the number of forwardings in the network, we restrict the transmission range to a rectangle region between each source-destination pair. We design DBPR in the distributed fashion without collecting the global network load information, which is suitable for LEO satellite networks with limited resources, long propagation delay, dynamic topology, etc. We analyze the network stability and prove the throughput optimality of DBPR. Simulation results demonstrate that DBPR can achieve higher throughput and lower delay, compared with the state-of-the-art strategies, especially in the environments with limited cache resource.

The efficiency and safety issues caused by cell differences are the key factor to hinder the use of retired batteries. The reconfigurable battery technique is an effective method to break through the bottleneck. However, the potential short-circuit paths increase exponentially with the number of cells, which makes manual analysis unapplicable and brings serious risks in large scale reconfigurable battery systems. Existing researches are about topology and energy efficiency optimization, but the problem of short circuit is ignored. In this article, a systematic approach based on the sneak circuit theory is proposed to fundamentally avoid the short-circuit problem of reconfigurable battery systems. A novel sneak circuit theory based approach is creating a short circuit path table, which will be indexed to avoid connecting the anode and cathode of a battery cell/string. In addition, all the paths are further studied and analyzed, and the simplest path table can be obtained to improve the energy efficiency. To validate the theoretical foundation and feasibility of proposed approach, a reconfigurable battery system containing two kinds of batteries is developed. All experimental results well verify the effectiveness and feasibility of proposed approach. This work provides theoretical foundation for avoiding short-circuit paths in reconfigurable battery systems, which will break through the bottleneck in scale application.

Satellite networks can provide a wider service range and lower delay than traditional terrestrial optical fiber networks. However, due to the bursty characteristic of the Internet traffic and the distributive feature of satellite links, traffic‐intensive areas often suffer from link congestion while links in other areas are underutilized, i.e., the traffic imbalance problem in LEO satellite networks. In this paper, an ant colony optimization routing algorithm with window reduction for LEO satellite networks, ACORA‐WR, is proposed to achieve load balancing. ACORA‐WR limits the movement of the ant colony to a specific range and comprehensively considers the path distance, transmission direction, and link load to find a path with low delay and overhead. Simulation results verify that the proposed ACORA‐WR scheme demonstrates high data delivery ratio and network throughput, while ensuring low average delay and network transmission overhead.

Edge computing pushes computation and storage resources to the network edge, which is close to end users, and thus, is critical for latency-sensitive applications, e.g., intelligent vehicular ad hoc networks (VANETs). To enable these services, a set of edge servers needs to be deployed to the roadsides. Such deployment should offer low-latency services to end users, while keeping a low deployment or maintenance cost, which is a nontrivial task. In this article, we study the edge server placement problem in a metropolitan area. This problem is composed of two parts to determine: 1) the locations of the servers and 2) the coverage of each server, with multiple optimization objectives. First, we study the Shanghai Taxi Trace to gain insights into the traffic pattern of taxis, especially how vehicles move between different locations. Second, we build multiobjective optimization models to characterize the tradeoff among three critical performance metrics, namely, the initial deployment cost, the runtime cost (i.e., number of hand-offs between different servers), and the average delay of tasks. Due to the intractability of these NP-hard problems, we propose a heuristic multiobjective optimization method to decompose the global problem into a set of local problems with tractable scale. Numerical results verify that our heuristic strategy achieves a desirable balance among the three performance metrics, e.g., a 5% compromise of the delay can reduce up to 50% of the hand-offs for small local areas, and 10%+ for the entire global area, compared with the best existing algorithms.

With the rapid development of satellite technology and the high transmission efficiency of LEO satellites, LEO satellite communication has received increasing attention. However, the frequent switching of satellite-earth links imposes a great challenge in LEO communication authentication. To tackle this challenge, this paper proposes a Blockchain-based Authentication Protocol Using Cryptocurrency Technology (BAPC), which solves the problem of a long pause time of satellite services caused by user access authentication in a scenario of frequent switching between satellites and ground users. First, we design three stages of the authentication process and introduce the cryptocurrency technology. Using currency transactions as the certificate of authentication improves not only the security of authentication, but also the efficiency of switching authentication. Next, in the network topology, the satellite cluster is divided into multiple regions to improve the efficiency of block consensus. Finally, the protocol is tested through extensive NS2-based simulations, and the results verify that BAPC can greatly shorten the response time of switching authentication and significantly reduce the time of block generation and the network throughput. As the number of users increases, the block generation time and network throughput can be further reduced.

In future Internet of Vehicles (IoV), edge servers will be deployed to the proximity of vehicles on road to offer realtime computation offloading services. However, servers deployed at fixed sites are static, while the traffic load on road is highly dynamic, incurring the mismatch between the demand and supply from time to time. In this paper, we study using multiple Unmanned Aerial Vehicles (UAVs) to act as edge servers for the IoV in a city-wide area. We first build a model on how to dispatch multiple UAVs to multiple hovering locations where they can cover a maximum number of user requests on discretized time slots. As the problem is NP-hard, we design a heuristic algorithm to solve it in polynomial time, namely the UAV pie-eating dispatching algorithm. Next, we propose a matching-based strategy to reduce the total travel distance of the UAVs when they move between the hovering locations, with the purpose of saving energy. We run extensive trace-driven experiments on the trajectory data of the taxicabs in Shanghai. The results verify that our UAV pie-eating algorithm effectively dispatches the UAVs to different locations at different time to adapt to the spatio-temporal demand variation, and our matching-based path planning strategy also reduces the total travel distance significantly compared with other popular strategies.