In post-disaster recovery scenarios, Unmanned Aerial Vehicles (UAVs) are widely deployed as aerial base stations to ensure deterministic communication services for time-sensitive (TS) flows requiring strict latency and reliability requirements. However, dynamic network topologies may render existing schedules invalid, and newly arriving flows can cause time-slot conflicts with ongoing transmissions, resulting in low resource utilization. To address these challenges, we propose a Depth-First Search-based Proximal Policy Optimization (DFS-PPO) approach for robust data flow routing and scheduling. The proposed method aims to balance link loads while satisfying reliability and latency constraints. A pruned DFS algorithm is used to determine the candidate routing set. To capture the spatial dependencies of all link states in the network, a Graph Attention Network (GAT) is employed to extract the global network state. In addition, a Transformer is adopted to model the nonlinear relationship between candidate routes and the network state. A PPO agent then makes routing decisions based on the high-level representation generated by the Transformer, enabling the model to adapt dynamically to changing network conditions and effectively mitigate bottlenecks. Simulation results demonstrate that the proposed DFS-PPO approach significantly outperforms benchmark algorithms in terms of network load balancing, reliability, and the number of successfully scheduled TS flows.

Time-sensitive missions in LEO satellite networks, such as fast position reporting, emergency communication, and surveillance, impose strict requirements on end-to-end delay and jitter. Early approaches like Satellite Formation Flying (SFF) relied on stable physical formations but suffered from tight coupling between orbits and services, limiting scalability and flexibility. This paper introduces a Virtual Satellite Formation (VSF) paradigm that decouples physical resources from service logic and dynamically selects virtual satellites to construct temporary formations. A two-layer network model is developed to quantify inter-satellite link stability, and an end-to-end deterministic transmission model is established by incorporating the characteristics of time-sensitive missions. Based on these models, we define a Deterministic Service Index (DSI) and formulate the corresponding optimization problem. To solve it, we propose a dynamic multi-objective evolutionary algorithm (DMO-VSF) that adapts to network dynamics in real time. Simulations in STK demonstrate that DMO-VSF reduces end-to-end delay by 15–18% and jitter by 35–40% compared with traditional routing, enabling resilient and deterministic services in large-scale constellations.

Routing, working with scheduling cooperatively to ensure the deterministic low-latency communication, plays a critical role in Time-Sensitive Networking (TSN). The multi-level spatial correlation among network nodes may greatly impact the forwarding paths of flows and is yet to be well investigated to improve the paths selecting process. In this letter, hypergraph is first introduced to model the time-sensitive networks, which can capture group features and higher-dimensional relationships for nodes. Then, the forwarding process for flows on a hyperedge and the end-to-end hyperpaths of flows are analyzed and studied. Finally, a hypergraph-based routing algorithm is designed to provide efficient routing decisions for time-sensitive flows. Simulation results show that the proposed routing algorithm can enhance the efficiency of paths planning and provide satisfiable global schedule for time-sensitive networks.

With the development of wireless communications, the 6G network is evolving toward dynamics, complexity, and integration. The mobility of nodes and intermittently of links lead to frequent variations in the network topology. When constructing the topology model, the reliability of topology is not only affected by the physical properties of wireless links but also related to the evolution process of nodes and links states, which is indispensable for improving the accuracy of the topology model. In this paper, we propose the evolution model based on dynamic bond percolation to characterize the reliable topology evolution. Firstly, key factors that cause the network topology changes are analyzed, integrating the characteristics of the node mobility and link channel conditions. Especially signal interference, buffer of nodes, and link availability are modeled for wireless link states. Then, the interactions between adjacent links are formulated by an extended Dynamic Bond Percolation (DBP) model to obtain the topology state transition matrix, which can accurately depict the change of link connection. Based on the quantitative analysis of wireless link states, Markov chain and master equation are employed to build the Dynamic Topology Evolution (DTE) model. Meanwhile, the network topology prediction problem is transformed into a linear system solution problem to obtain the steady-state network topology based on the DTE algorithm. Finally, the results suggest that utilizing the DTE model can significantly improve the accuracy of topology prediction and overall network performance.

With the explosive growth of real-time applications in satellite systems, Time Sensitive Networking (TSN) is explored to be introduced to provide bounded low latency network services. Nevertheless, some efforts in delay ensuring techniques are ongoing, guaranteeing deterministic low latency communication in satellite networks is still a significant problem. In the article, we first present a Digital Twin-based TSN framework in which digital twin technology is introduced for the purpose of reducing the management cost and optimizing the performance of satellite networks. The virtual model of the scheduling method working in satellite systems is explored and created for the simulation and prediction of the forwarding delay results. Deep convolution generative adversarial network (DCGAN) is adopted to train the scheduling model. The simulation experiments verified that the digital twin could mirror the scheduling behavior and predict the delay in dynamic environments.

In vehicular networks, the Point of Interest (POI) query was widely used in Location-Based Services (LBS) for vehicle applications. However, since the attackers can easily access the location, query content, and other information, it is difficult to protect the LBS privacy of vehicle users only using location privacy protection or query privacy protection independently. Therefore, we propose a location privacy and query privacy joint protection scheme based on dummy sequences. According to the limitations of the POI query, we model the correlations between location privacy and query privacy into semantic correlation, temporal correlation, and spatial-temporal attribute correlation, characterized by the Euclidean distance and the association rule algorithm. Moreover, we formulate the dummy sequence selection as a constrained multi-objective optimization problem to obtain the query sequence with a high level of anonymity and a big cloaking region. Experimental results demonstrate that our scheme can resist joint attacks on location privacy and query privacy and protect users' LBS privacy more efficiently compared to the existing schemes.

Location-based services (LBSs) are widely used in vehicular networks. Privacy leakage from LBS is a key issue to be solved. However, the existing schemes fail to provide differentiated protection for users’ different locations, which may lead to the leakage of location information. In this paper, we propose a personalized location privacy protection scheme based on differential privacy to protect the privacy of location-based services in vehicular networks. Firstly, we propose a normalized decision matrix to describe the efficiency and the privacy effect of navigation recommendations. We then establish a utility model integrated with users’ privacy preferences to compute the effective driving route. Secondly, for different service request locations in the driving route, we define sensitivity distance as an index to quantify their privacy requirements. The privacy budget will be added to the service request location to generate a false location. Moreover, due to the limitation of road range in the driving route, if the privacy budget value allocated is small enough, the false location generated by the Plane Laplace will be deviated. As a result, the attacker can deduce users’ real request locations. Consequently, considering the factors of trajectory leakage, attack strategy and QoS, we establish a multi-objective optimization model to optimize the false location. Based on the real data set, we conduct a series of comparison simulations to evaluate the performance of the proposed scheme. The experimental results demonstrate that our scheme can satisfy users’ personalized services needs and provide an optimal solution to privacy and QoS.

The Satellite Terrestrial Integrated Network(STIN) has become an indispensable part of the future network. However, the limited resources, long delay communications and highly exposed channels of SGIN are vulnerable to network attacks, which make the access authentication scheme as the first line of defense in network security. Most of the existing access authentication schemes are based on discrete logarithm and large integer factorization problems, which cannot resist quantum attacks, and the number of interactions between entities are too large. Therefore, we propose a lightweight and certificateless anonymous access authentication scheme based on lattice to solve this problem. We introduce Number Theory Research Unit (NTRU) scheme into the key generation process, to improve the utilization rate of equipment resources and ensure the legitimacy of the communication entity. The performance evaluation results demonstrate that our scheme only needs twice satellite-ground interactions to complete mutual authentication.

Satellite formation flying with functional payloads can provide flexibility and real-time services for time sensitive missions through the cooperation of intra-satellite wired and inter-satellite wireless communication systems. However, the difference between wired and wireless scheduling mechanisms will increase the instability of forwarding delay at satellite. To solve this problem, we propose a wired and wireless converged scheduling scheme. Firstly, we construct the transmission rate and time division multiple access scheduling model to describe the inter-satellite link, and the IEEE 802.1Qbv scheduling model for wired link respectively. Secondly, we analyze the influence of the position of packet in different time slots on the forwarding delay, to model the relationship between the converged scheduling and forwarding delay. Finally, we formulate the converged scheduling as a zero-one programming problem with minimum jitter, and adopt the genetic-tabu search algorithm to solve it. Simulation results demonstrate that the delay is reduced by 20%, the jitter is not higher than$40\mu\mathrm{s}$.

The software-defined Low Earth Orbit (LEO) satellite network can effectively improve the flexibility of the inter-satellite networking. However, the impact of Inter-Satellite Link (ISL) attributes on the network topology has not been well investigated in existed works, which leads to the loss of topology information and the unreliability of routing path. In this paper, we propose a dynamic routing algorithm based on ISL attributes to improve the adaptability and reliability of routing in LEO satellite network. Firstly, we construct the utility function of ISL attributes to quantify the link utility. Then, the maximum deviation algorithm is introduced to adaptively calculate the weight of attribute parameters in link utility function, which can quantify the impact of each attribute on link quality. Finally, the mathematical model of path utility is established, the routing path with highest path utility is selected as the optimal routing path. The simulation results show that the proposed scheme can improve the network performance by about 35%, 10% and 20% in terms of packet drop rate, end-to-end delay and throughput.

Loading the functions of base station on satellite can improve the flexibility of user access and expand the effective coverage of Satellite-Terrestrial Integrated Network (STIN). However, the functions of management and control that supports the satellite networking have not been well investigated. A large amount of signaling needs to be forwarded to the ground control center for processing, which increases the delay of network control and management. In this paper, we propose a novel mobile core network architecture that loads the mobility management function of core network on the satellite, which can improve the flexibility of management and control of STIN. Firstly, considering the on-board computing capacity and the dynamic characteristic of satellites, we design the lightweight Satellite Mobile Core Network (SMCN) to improve the flexibility of the Satellite next-generation NodeB (Sat-gNB) networking. Then, the interactive protocol for user access control, mobility control of Sat-gNBs and the coordinated control between ter-restrial network and satellite network are designed to support the mobility management. Finally, in order to optimize the delay of Sat-gNBs networking, we construct the mathematical model for the multi-SMCN deployment. The simulation results show that compared to the architecture of Non-Terrestrial Networks (NTN), the proposed mobile core network architecture can improve the flexibility of mobility management and optimize the network delay.

Software defined satellite-terrestrial networking has been identified as a promising approach to support the diversity of network services. As the fundamental issue to improve the flexibility of network management, the controller placement problem has been attracted increasing attentions for the integration of satellite and terrestrial networking. However, the impact of the dynamic coverage demands on the controller placement have not been well investigated in existed works, which makes them fail to adjust the coverage dynamically according to the actual demands, and leads to an obvious increase of networking response latency to the terminals. Aiming to address this issue, we propose a novel on-demand dynamic controller placement scheme, which can optimize the placement of controllers to improve networking response latency while meeting the dynamic coverage demands. Firstly, to optimize the number of controllers and meet the dynamic coverage demands, we define the coverage redundancy and propose the redundancy-based satellite subnet division method to establish the reliable satellite subnets. Secondly, we quantify the networking response latency of the distributed satellite subnet, and build an optimization mathematical model to optimize the number and location of controllers. Then, we formulate the controller placement problem into the capacitated facility location problem and build the mathematical model for it. Moreover, the on-demand dynamic approximation algorithm is proposed to obtain the approximation solution. Finally, the simulation results demonstrate that the proposed algorithm can effectively optimize the network latency compared with related algorithms.

Summary The high‐bandwidth demands from variety of applications drive a dense wireless local access network (WLAN), which results in a complicated wireless network scene with serious co‐channel interference and energy waste. In this paper, to reveal the interactions between interference and energy efficiency, we propose an interference‐energy efficiency (IFEE) model to quantify the interference impact on the energy efficiency of 802.11 access point (AP) devices. Firstly, we introduce the channel separation and the difference of received signal strength indication (D‐RSSI) as two indicators to extend the classical signal to interference plus noise ratio (SINR) notion and rate adaptive mechanism. Then, these two parameters are integrated into the energy consumption model to establish the IFEE model. Lastly, we conduct extensive measurements with five typical WiFi interference scene in real network to validate the effectiveness of our model. The comparisons between simulation results and real data demonstrate that the proposed IFEE model can quantify the interference and energy efficiency with high accuracy, which can be used for wireless network optimization and protocol design.

Recently, a number of WiFi access points (APs) have been densely deployed to provide widely available, high-performance Internet services. As such, an energy efficiency issue becomes crucial toward the design of green wireless local area networks (WLANs). In this paper, we propose a resource and re-association scheduling algorithm (referred to RAS) based on Benders' decomposition to reduce the energy consumption. In particular, we endeavor to aggregate WLAN users on the small number of APs and turn off many APs without compromising users' quality of experience (QoE) and system coverage. We conduct the analysis by using real trace data and formulate the energy minimization as the mixed integer nonlinear programming (MINLP) problem. We then transform and solve the original problem through the RAS algorithm. For practical implementation, we further propose the fast RAS (Fast-RAS) algorithm to relax the binary integer constraints and transform the MINLP problem into the nonlinear programming (NLP) problem. The relaxed problem then can be solved by using Feasible Pump algorithm with the reduced computational complexity. We evaluate the performance of RAS and Fast-RAS algorithms via extensive simulations. The results demonstrate that the Fast-RAS algorithm can achieve up to 20% improvement of energy saving comparing with existed methods.

The demands for high-bandwidth drives a dense wireless local access network (WLAN), which may result in severe co-channel interference and energy consumption increasing. To clearly quantify the effect of interference on energy consumption of 802.11 access devices, it is crucial to measure and model the effect of interference. This paper takes extensive measurements for five different WiFi interference types for downstream UDP transmission in actual environment. Based on experimental measurements, we establish a physical interference-energy efficiency (IFEE) model by reconstructing the signal to interference plus noise ratio (SINR) notion and the modulation and coding scheme (MCS) rate adaptive mechanism to accurately predict the interference impaction. Our experimental measurements demonstrate that interference leads to a decrease in energy efficiency and throughput. Compared with the transmit power, channel separation interference dominates. It is worth noting that the impact of interference with multiple interferers is less than single interferer scene. The simulation experiments verify that our IFEE model can achieve high accuracy of interference and energy efficiency modeling.

Application Layer Distributed Denial of Service (ALDDoS) attacks have been increasing rapidly with the growth of Botnets and Ubiquitous computing. Differentiate to the former DDoS attacks, ALDDoS attacks cannot be efficiently detected, as attackers always adopt legitimate requests with real IP address, and the traffic has high similarity to legitimate traffic. In spite of that, we think, the attackers' browsing behavior will have great disparity from that of the legitimate users'. In this paper, we put forward a novel user behavior-based method to detect the application layer asymmetric DDoS attack. We introduce an extended random walk model to describe user browsing behavior and establish the legitimate pattern of browsing sequences. For each incoming browser, we observe his page request sequence and predict subsequent page request sequence based on random walk model. The similarity between the predicted and the observed page request sequence is used as a criterion to measure the legality of the user, and then attacker would be detected based on it. Evaluation results based on real collected data set has demonstrated that our method is very effective in detecting asymmetric ALDDoS attacks.

With the rapid development of smartphones and mobile Internet technology, we witness an overwhelming growth of mobile social networks (MSN), which is a type of social network, forming virtual communities among people with similar interests or commonalities. In MSNs, users play a crucial role for their development, deployment and success. Understanding the MSN user behavior therefore attracts interests of different entities — ISPs, service providers, and researchers. However, it is hard to gather a comprehensive real data set, little is known and even less has been published about MSN user activities. In this paper, we focus on analyzing MSN user behavior from the perspective of ISP network, which is seldom reported in literature. Based on the real data set collected from the mobile network gateway of a major mobile carrier who has more than five million subscribers, we present an in-depth user behavior analysis of four popular social networks. We study the MSN user behavior from six aspects: user requests, active online time, sessions, inter-session, the number of requests in a session, and inter-request. We found that power law and lognormal are two popular features of the studied objects, and exposed some interesting findings as well. We hope our work could be helpful for ISPs, MSN content providers, and researchers.

With the popularization of mobile network and smart phone, the number of mobile Internet users has been growing rapidity and various kinds of services have emerged. It is significant for both academia and industries to understand its user behavior. This paper firstly constructs a user-service weighted bipartite network model, according to the methodology in complex network, and then groups the present services in mobile Internet into 12 categories, in order to research user access characteristics for different kinds of services. Using this model, we analyze the user behavior mainly from user interest range, user interest intensity, user access characteristics and user access relevance four aspects. Our click stream data sets, which contain two 1-week periods, one is in 2010 and the other in 2011, were collected from a WAP gateway of one main Mobile Telecom Carrier in Chongqing Province, China, then, based on the two data sets, we show the characteristics of service access behavior and expose the changes of user behavior during two years.

Distributed denial of service (DDoS) attack is a continuous critical threat to the Internet. Derived from the low layers, new application-layer-based DDoS attacks utilizing legitimate HTTP requests to overwhelm victim resources are more undetectable. The case may be more serious when such attacks mimic or occur during the flash crowd event of a popular Website. In this paper, we present the design and implementation of CALD, an architectural extension to protect Web servers against various DDoS attacks that masquerade as flash crowds. CALD provides real-time detection using mess tests but is different from other systems that use resembling methods. First, CALD uses a front-end sensor to monitor the traffic that may contain various DDoS attacks or flash crowds. Intense pulse in the traffic means possible existence of anomalies because this is the basic property of DDoS attacks and flash crowds. Once abnormal traffic is identified, the sensor sends ATTENTION signal to activate the attack detection module. Second, CALD dynamically records the average frequency of each source IP and check the total mess extent. Theoretically, the mess extent of DDoS attacks is larger than the one of flash crowds. Thus, with some parameters from the attack detection module, the filter is capable of letting the legitimate requests through but the attack traffic stopped. Third, CALD may divide the security modules away from the Web servers. As a result, it keeps maximum performance on the kernel web services, regardless of the harassment from DDoS. In the experiments, the records from www.sina.com and www.taobao.com have proved the value of CALD.