A novel routing algorithm based on dynamic clustering for LEO satellite networks

Due to dynamic changes in network topology and constant changes in links between satellites, the routing paths calculated by the traditional shortest multipath routing algorithm are not updated in time, resulting in that the problematic paths are still transmitting data, so a large number of problems such as packet loss and service failure exist in the network. This paper designs a multipath routing algorithm for the satellite network topology which changes frequently, constrained multipath routing algorithm (CMRA). By calculating all feasible path of the entire network topology, CMRA will choose the multiple paths which satisfy the constraint conditions. After that, it will choose the lowest cost value of these paths. Repeatedly performing these operations, select multiple high-quality paths which satisfy the constraint conditions for traffic. Simulation results show that compared with the traditional shortest multipath routing algorithm and single path routing algorithm, the proposed routing algorithm is better in packet loss rate and average time delay.

Satellite communication networks, as an effective complement to terrestrial communication networks, enable global coverage communications. The Low-orbit satellite network has the characteristics of low transmission delay, short operation period and global coverage communication, it has become a popular research direction in satellite communication networks. With the continuous development of digital and intelligent communication in the world, satellite network services continue to expand, and higher requirements are placed on network transmission performance. The traditional single-structure low-orbit satellite network using centralized routing has been unable to meet current needs.. Therefore, with the low-orbit satellite network as the core, people have conducted in-depth research on satellite communication network routing algorithms that meet the requirements of high-quality, high-efficiency and largecapacity communication. Especially in the three hot issues of low-orbit satellite network routing algorithms, a lot of research results have emerged, including: QoS-based artificial intelligence algorithm routing algorithm; multi-layer satellite network routing algorithm; satellite network multipath routing algorithm. Through the analysis and discussion of these problems and achievements, the idea of combining the three algorithms on demand is proposed, and the challenges are analyzed.

Aiming at the problems of high dynamic topology and limited on-board resources in Low Earth Orbit (LEO) satellite networks leading to poor performance of traditional routing algorithms, this paper combines the centralized control idea of Software-Defined Networking (SDN) with the collective learning ability of the Particle Swarm Optimization (PSO) algorithm to propose an adaptive potential field routing algorithm based on PSO. This algorithm models the network as a dynamic potential field, defines potential energy based on the cumulative congestion degree to guide data packet transmission; adaptively learns and optimizes link cost weights through the PSO mechanism, achieving dynamic evolution of the path evaluation criterion; and adopts a probability-based multi-path forwarding mechanism to achieve load balancing. Simulation results show that compared to traditional algorithms such as Dijkstra and ACO (Ant Colony Optimization), this algorithm significantly improves performance in terms of average end-to-end delay, network throughput, and load balancing, especially suitable for dynamic traffic scenarios.

Several IP-based routing algorithms have been developed for low-Earth orbit (LEO) satellite networks in recent years. The performance of the satellite IP networks can be improved drastically if multiple satellite constellations are used in the architecture. In this work, a multilayered satellite IP network is introduced that consists of LEO, medium-Earth orbit (MEO), and geostationary Earth orbit (GEO) satellites. A new multilayered satellite routing algorithm (MLSR) is developed that calculates routing tables efficiently using the collected delay measurements. The performance of the multilayered satellite network and MLSR is evaluated through simulations and analysis.

Due to the dynamic change of the opportunistic network topology and the lack of stable information transmission paths between nodes, the traditional topology-based routing algorithm cannot achieve the desired routing performance. To address of this problem, this paper proposes a routing algorithm based on trajectory prediction (RATP). The routing protocol based on trajectory prediction can efficiently and quickly adapt to the network link quality instability and the dynamic changes of network topology. RATP algorithm constructs a node mobility model by analyzing the historical mobility characteristics of the nodes. According to the node prediction information, the metric value of the candidate node is calculated, and the node with the smaller metric value is selected as the data forwarding node, which can effectively reduce the packet loss rate and avoids excessive consumption. Simulation results show that compared with other algorithms, the proposed algorithm has higher data delivery ratio, and end-to-end data delay and routing overhead are significantly reduced.

Robust PMU Placement in Branch Switching Power Networks for Minimum Variance State Estimation

With considering satellite networks' characteristic of few network nodes, limited on-board storage and processing ability etc., a distributed delay-constrained routing algorithm (DDCRA) with mechanism of probe packet is proposed. Based upon strategy of distributed routing and quality of service (QoS), DDCRA reduces the complexity of algorithm so as to lower requirements for the on-board processing equipments. Comparing with the minimum delay routing algorithm, better performances of DDCRA can be achieved.

Wireless Ad Hoc network routing algorithm is one of the core technologies of wireless Ad Hoc networks. Ad Hoc network is dynamic topology on characteristic, mainly reflected on the network node number and node movement, which lead to network topology changes, in order to study the Ad Hoc network size and topology changes influence on packet delivery, time delay and routing control, through experiment it is concluded that, the dynamic source routing protocol is an ideal choice.

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED).

Uneven traffic demand in satellite networks can lead to link congestion and influence network communication quality. To tackle this problem, we propose a state‐aware routing algorithm based on traffic prediction to disperse network traffic. Reducing the onboard processing requirements, the routing algorithm in this paper introduces a software‐defined network to decouple the control plane and data plane of the satellite network. Also, to better sense the trend of network state, the routing algorithm devises a Spatial‐Temporal Attention Fusion Graph Neural Network (STAFGNN) to predict the future network state by capturing the spatial‐temporal correlation of satellite network traffic. In the control plane, the routing algorithm senses the network state by predicting the future satellite traffic and aggregates the real‐time states of neighboring satellites to identify the load level of the zone. The data plane forwards data based on the control information. Based on the routing algorithm in this paper, multipath routing is designed to reduce the probability of link congestion by dispersing each end‐to‐end traffic. The simulation results demonstrate that the routing algorithm in this paper reduces the number of congestion links and balances the load distribution. The proposed algorithm provides an idea to introduce deep learning to solve the load balancing problem in satellite networks.

To improve the performance of route overhead and packet dropped rate of routing algorithms in mobile ad hoc networks, a location-based grid routing (LBGR) algorithm is presented. By node position information, the LBGR algorithm employs a grid-constructed trajectory instead of node ID in forwarding packets. Based on the position relationship of nodes and downstream grids, each intermediate node infers the next hop to relay packets. Therefore, it can adapt to frequent and unpredictable topology changes in the presence of high mobility and greatly enhance the robustness of route maintenance. Simulation results show that the proposed algorithm can reduce route overhead, packet dropped rate and the average number of hops per path

In recent years, data center network is used for transmission, storage and processing of big data, which plays an important role for applications in cloud computing and CDN distribution. Network topology and routing algorithm are its core research content and key technical issues. The traditional network topology is difficult to guarantee the quality of service in scalability and fault tolerance. The server-centric data center network topology can ensure the scale of the data center network by recursively increasing the number of network nodes and links. relative to the Dcell, BCube, and BCCC typical network topology, PTNet network as a typical representative of a new type of the server-centric data center network topology, which has more advantages in scalability, fault tolerance and so on. Multicast and broadcast in data center network have more application scenarios and use value. For example, the video conference online, multimedia remote education and other development are inseparable from the application and promotion of network multicast and broadcast. So it is necessary to research the routing algorithms of multicast and broadcast in the network. Based on the deep research of PTNet network, this paper analyzes and researches the network topology, multicast and broadcast routing algorithm.

The model of indirect trust value is done further research in statistics principle and a new model of trust value is proposed. On this basis, the electoral method of cluster node is studied, and then a routing algorithm is given based on considering the trust value, the density, the distance between nodes and the forward capability. Experiment and simulation results show that the established trust value model is considerably reliable, and with the increase of cycles, the trust value gradually tends to 1. In a certain range about the number of nodes, in comparison with references 10 and 11, this algorithm improves convergence speed largely and is stable during the information transfer process. When the network topology changes, this algorithm can do fast rerouting, which shows this optimization algorithm has widely application.

The dynamics of Vehicular Ad-hoc Network (VANET) brings tremendous challenges to reliable routing. In the existing topology evolution schemes, the link connectivity and the interaction between links have yet to be well investigated, resulting in the inability to accurately describe the evolution of routing topology. In this letter, we propose a Dynamic Topology Evolution (DTE) based reliable routing algorithm to improve transmission reliability. The DTE model is constructed to formulate the evolution of network topology. Especially, we analyze the network topology changes from the perspective of nodes and links. Meanwhile, the Dynamic Bond Percolation (DBP) model is extended to describe link interaction. Then, the DTE model is completed by deriving the state transition matrix of the network topology based on the link change using Markov theory. Finally, the DTE-based Reliable Routing (DTE-RR) algorithm is designed to optimize routing paths. The experimental results demonstrate that DTE-RR outperforms the existing protocols regarding packet delivery ratio and end-to-end delay.

A preliminary integrated services digital network (ISDN) model is developed that incorporates basic features such as voice and data call generation, call setup for circuit-switched calls, packet-switched signaling, transmission of low-rate data on the signaling channel, and selectable number of nodes, link capacities, and connectivities. The model concentrates mainly on the basic call control procedures of the ISDN user part of the CCITT Signaling System No.7 in conjunction with D-channel protocols. The primary objective of the ISDN simulation model is to aid in understanding the performance of the ISDN protocols. In the design mode, it may be used to evaluate a number of potential architectures consisting of various message traffic/workload scenarios with different mix of voice and data traffic, resource additions and expansions and congestion handling. The model produces statistical measures of network utilization and call blockage that can be used to evaluate the effect of changes in network topology. routing algorithms, and traffic. The architecture and input/output formats of the model are described. Some numerical results from sample runs are given. >