CN112187342A - Satellite traffic routing method and system based on energy perception and load balancing - Google Patents

Satellite traffic routing method and system based on energy perception and load balancing Download PDF

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CN112187342A
CN112187342A CN202011068484.5A CN202011068484A CN112187342A CN 112187342 A CN112187342 A CN 112187342A CN 202011068484 A CN202011068484 A CN 202011068484A CN 112187342 A CN112187342 A CN 112187342A
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任品毅
郝林春
杜清河
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Xian Jiaotong University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
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    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851—Systems using a satellite or space-based relay
    • H04B7/18513—Transmission in a satellite or space-based system
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851—Systems using a satellite or space-based relay
    • H04B7/18519—Operations control, administration or maintenance
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The invention discloses a satellite flow routing method and a system based on energy perception and load balancing, wherein a topological adjacency matrix is pre-calculated and stored, satellite congestion and energy information are updated through a broadcast packet, then a routing table is calculated according to routing schemes of different services, transmission requirements of different service flows are considered, transmission with the shortest path can be ensured on the premise of reliable transmission, and through simulation verification, the routing algorithm can prolong the service life of a network, enable the network to have more uniform energy, reduce packet loss rate, improve throughput and effectively ensure the transmission of reliable services in a network with limited energy; the proposed flow classification routing algorithm adopts different routing schemes according to service characteristics, and can meet the QoS requirements of different services, realize network load balancing and optimize the utilization of network resources particularly under the conditions of network congestion and low network energy level.

Description

Satellite traffic routing method and system based on energy perception and load balancing
Technical Field
The invention belongs to the technical field of satellite network routing, and particularly relates to a satellite traffic routing method and system based on energy perception and load balancing.
Background
With the rapid development of aerospace technology, the role of satellite communication in military and civil fields is increasingly prominent. The satellite mobile communication system is widely covered in real time, the characteristic of large transmission capacity becomes an extension of a ground mobile communication network, and the satellite mobile communication system is an important link in a future world-space integrated scene.
In the existing routing algorithm, Werner et al proposes a snapshot switching model, and converts a dynamic network topology into a static discrete snapshot to calculate a route. The iridium satellite system divides snapshots at equal time intervals, calculates routes in a centralized manner, uploads updates at certain time intervals between ground stations, and stores off-line calculated routing tables in the satellite. However, uploading different routing tables to each satellite not only increases the complexity of the algorithm and causes the waste of satellite-to-ground link bandwidth, but also the uploading and updating mode is difficult to cope with the emergencies such as sudden increase of traffic, satellite failure and the like.
With the development of network and multimedia technologies, the service demands of people in various aspects are gradually increased, and higher requirements are put on the comprehensive service quality of the communication system. Different services have different requirements on network transmission, low-delay service requires low-delay and best-effort network transmission, and reliable service has low requirements on transmission delay and needs to ensure reliable transmission. Especially, under the condition of network resource shortage, routing transmission is carried out aiming at the characteristics of various services, network load balance can be effectively realized, the utilization of network resources is optimized, all services are transmitted as far as possible in a comprehensive mode, and network congestion can be caused.
In recent years, the volume and the cost of a single satellite are gradually reduced, a plurality of microsatellite constellation networks appear, the number of satellites is large, and the volume of the satellite is smaller. Starlink, as propelled by spaceX, consists of nearly 12000 satellites, with a double-layer structure and inter-satellite links. And the Oneweb system built by a network company is also composed of more than 2000 small satellites. In these constellations, a group of small satellites can take on the similar functions of a large satellite, but the data transmission and reception requires a large amount of energy, and the small satellites have certain limits in terms of energy and computational processing, especially when the satellites are in earth shadow and solar eclipse, the energy consumption of the satellites is large, and the interruption of data transmission is caused when the energy of the satellites is exhausted. For some service data needing reliable transmission, whether the residual energy of the satellite is sufficient or not should be considered in route calculation, and data packets are reduced to be sent to the satellite with the energy to be exhausted. The existing satellite routing strategy does not fully consider the application scene of the network, most satellite routes aim at single service, and in the energy-limited microsatellite network, the characteristics of maximizing the service life of the network and not considering different service flows are only considered, so that effective transmission among satellites cannot be realized.
Disclosure of Invention
The invention aims to provide a satellite traffic routing method and a satellite traffic routing system based on energy perception and load balancing, which are used for overcoming the defects of the prior art and can realize network load balancing and optimize the utilization of network resources.
In order to achieve the purpose, the invention adopts the following technical scheme:
a satellite traffic routing method based on energy perception and load balancing comprises the following steps:
step 1), calculating and storing the topological information of each satellite on each satellite in the form of an adjacent matrix;
step 2), utilizing a link broadcast packet to regularly broadcast queuing delay, link and satellite energy information on each satellite to the whole network through a link information exchange mechanism, and updating information parameters for route calculation on each satellite;
step 3), updating the routing table on each satellite according to the routing schemes of different service types according to the adjacent matrix and the updated information parameters on each satellite;
in the process of route transmission, when flow occurs, according to the service type label in the data packet header and the on-satellite routing table, sending data packets of different services into different buffer queues on a satellite transmission link corresponding to the data packets, and waiting for sending;
when the capacity of the buffer queue of each service reaches the upper limit, temporarily storing the data packet into a public waiting queue, and distributing different survival times according to different service types; when the data packet in the public waiting queue is empty corresponding to the exit buffer queue of the next hop, the data packet enters the buffer queue to wait for forwarding, otherwise, the value of the self survival time is reduced by 1, and the data packet is discarded when the survival time is 0;
for the satellite with the energy to be exhausted, informing a neighbor satellite to reduce sending data packets to the satellite, forwarding the data packets to the neighbor satellite with relatively sufficient energy, and updating the topology information of the network; if the number of the links which are not failed is reduced to 1, the satellite connected with the satellite only transmits the data packet of the last hop to the satellite, if the links are not recovered in a long time or the satellite links are all failed, the whole network topology information and the on-satellite information are updated, the global routing recalculation is triggered, and the step 1) is returned, so that the satellite traffic classification routing is completed.
Further, each satellite recovers the static topology data corresponding to each satellite when the snapshot is switched.
Further, the continuously changing topology of the satellite is discretized into a plurality of time periods [ t ]0,t1]，[t1,t2]，…，[tn-1,tn]The topology of each time segment is treated as invariant and abstracted as an undirected graph Gi＝(Vi,Ei) In which V isiRepresenting a set of satellite nodes, EiAn adjacency matrix X [ k ] representing the set of all inter-satellite links on which topology information is pre-stored][i][j]It represents the inter-satellite link transmission delay from satellite s (i) to satellite s (j) at the time of the kth snapshot.
Further, the traffic types include real-time traffic, reliability traffic, and no QoS traffic.
Furthermore, the route of the real-time service updates the on-satellite queuing delay and the link propagation delay through a link information exchange mechanism, calculates a link path loss function, and finally calculates the real-time service propagation route by utilizing a Dijkstra shortest path algorithm.
Further, the queuing delay is calculated by using an exponential smoothing function, and the link path loss function is as follows:
costA(t)＝Td(t)+Tq(t) (4)
wherein, Td(T) and Tq(t) respectively represent links at time tThe propagation delay and the average queuing delay are updated respectively at the interval of topology updating and flow updating; wherein the average queuing delay TqThe calculation formula of (t) is as follows:
Tq(t)＝(1-α)×ToldQ+α×TnewQ (5)
wherein, the weight factor alpha represents the average queuing delay T of the last snapshot and the current snapshotQInfluence of specific gravity, TQThe calculation formula of (a) is as follows:
Figure BDA0002711321460000041
qi(t) is the number of packets in the buffer queue at time t, PavgIs the length of the data packet, C is the inter-satellite link capacity; t is tnIs the start time of a time interval.
Furthermore, the reliability service adopts a routing method based on satellite energy perception, satellite energy information is broadcasted to the whole network by using a link broadcast packet after satellite energy at the time t is obtained by calculation of a satellite energy model, relevant information on the satellite is updated, and a route is calculated;
when the ratio of the satellite residual energy R (t) to the satellite battery capacity B at the moment t satisfies
Figure BDA0002711321460000042
And then, calculating a route by using a weighted path loss function of the link propagation delay and the residual energy, wherein the weighted function is as follows:
Figure BDA0002711321460000043
Figure BDA0002711321460000044
wherein Dl(i, j) is the link propagation delay between satellite i and satellite j at snapshot t, DmaxAnd DminRespectively, maximum propagation between any two satellite nodesTime delay and minimum propagation delay; el(i, j) represents the energy state of link ij;
the weighting factor mu needs to be updated every snapshot interval, using RiRepresenting the residual energy of the satellite, μ is calculated and updated as follows:
Figure BDA0002711321460000051
when it is satisfied with
Figure BDA0002711321460000052
And then adding alpha to the path weight of all the import and export links connected with the satellite, wherein the weight alpha is related to the energy consumption condition of the satellite nodes at two ends of the link ij and the time in the earth shadow, and the calculation formula is as follows:
Figure BDA0002711321460000053
where e denotes whether the satellite is in the shadow of the earth,
Figure BDA0002711321460000054
Ei(T) energy lost by satellite i at snapshot T, Ti(t) the time of the satellite i in the shadow, when the energy consumption of the satellite is larger and the duration time in the shadow is longer, the residual energy of the satellite is not enough to guarantee long-time data transmission, and the data packet is reduced to be sent to the satellite in the next route updating process;
when it is satisfied with
Figure BDA0002711321460000055
And informing the neighbor satellites to reduce the sending data packets according to the corresponding proportion, and forwarding the data packets to the neighbor satellites with relatively sufficient energy.
Further, a parameter E of energy rating1And E2Dependent on energy depletionThe probability of causing the data packet to be discarded, I and O are respectively the input and output data rates on the satellite,tfor the time that the satellite is energy depleted, the following is calculated:
Figure BDA0002711321460000056
the satellite broadcasts packets to update the satellite energy information at intervals, and the interval of the energy updating is deltatIf, ift≤+ΔtAt this time, the probability of discarding the data packet is 1; if it ist>+ΔtThe probability of packet dropping is
Figure BDA0002711321460000057
The probability of packet dropping can therefore be expressed as:
Figure BDA0002711321460000061
so parameter E of energy rating1And E2Is set as1＝p，
Figure BDA0002711321460000062
When the remaining energy level of the satellite is low,tsmaller, then p takes a larger value, E1And correspondingly, the satellite with higher energy consumption takes measures as soon as possible, disperses the data packet to the satellite with sufficient energy and informs the neighbor satellite to reduce the data transmission.
Further, the specific routing method of the QoS-free service comprises the following steps: calculating N link disjoint candidate multi-path sets; selecting the optimal path in the candidate multi-path set according to the energy consumption and the link utilization condition of the satellite nodes on the candidate multi-path for forwarding, wherein the routing weight is calculated as follows:
Figure BDA0002711321460000063
Figure BDA0002711321460000064
Figure BDA0002711321460000065
where mu still represents the energy situation of the entire satellite network, Ep(t) energy consumption of the satellite nodes on the shortest path concentration path p in the snapshot t, EaveFor the average energy loss, L, of all satellite nodes on the path pp(t) is the number of times one of the intersatellite links on path p is utilized, LaveThe average utilization number of all the interstellar links on the path.
A satellite traffic routing system based on energy perception and load balancing comprises a satellite network topology matrix module, a satellite network parameter updating module and a routing module;
the satellite network topology matrix module is used for calculating, transmitting and storing the topology information of each satellite on each satellite in the form of an adjacent matrix; the satellite network parameter updating module broadcasts queuing delay, link and satellite energy information on each satellite to the whole network at regular time through a link information exchange mechanism by using a link broadcast packet, and updates information parameters used for route calculation on each satellite;
the routing module updates the routing table on each satellite according to the adjacent matrix and the updated information parameters on each satellite and the routing schemes of different service types; when the flow occurs, sending data packets of different services into different buffer queues on a satellite transmission link corresponding to the data packets according to the service type labels in the data packet headers and the on-satellite routing table, and waiting for transmission;
when the capacity of the buffer queue of each service reaches the upper limit, temporarily storing the data packet into a public waiting queue, and distributing different survival times according to different service types; when the data packet in the public waiting queue is empty corresponding to the exit buffer queue of the next hop, the data packet enters the buffer queue to wait for forwarding, otherwise, the value of the self survival time is reduced by 1, and the data packet is discarded when the survival time is 0;
for the satellite with the energy to be exhausted, informing a neighbor satellite to reduce sending data packets to the satellite, forwarding the data packets to the neighbor satellite with relatively sufficient energy, and updating the topology information of the network; if the number of the links which are not failed by the satellite is reduced to 1, the satellite connected with the satellite only transmits a data packet of the last hop to the satellite, and if the links are not recovered or the satellite links are all failed within a long time, the whole network topology information and the on-satellite information are updated, and the global routing recalculation is triggered.
Compared with the prior art, the invention has the following beneficial technical effects:
the invention relates to a satellite flow routing method based on energy perception and load balancing, which updates queuing delay, link and satellite energy information through a broadcast packet by pre-calculating and storing an adjacent matrix of a topology, then calculates a routing table according to routing schemes of different services, considers the transmission requirements of different service flows, can ensure transmission with the shortest path on the premise of reliable transmission, and can prolong the service life of a network through simulation verification by a routing algorithm, so that the network has more uniform energy, the packet loss rate is reduced, the throughput is improved, and the transmission of reliable services is effectively ensured in a network with limited energy; the proposed flow classification routing algorithm adopts different routing schemes according to service characteristics, and can meet the QoS requirements of different services, realize network load balancing and optimize the utilization of network resources particularly under the conditions of network congestion and low network energy level.
Furthermore, queuing delay is considered in the routing of the low-delay service; a routing scheme based on satellite energy perception is provided for reliability service, parameters for satellite energy level division are defined, different measures are taken for routing according to different energy levels of a network, and reliable transmission of data is guaranteed; aiming at the QoS-free service, a loop-free candidate path set scheme is provided, under the condition of network resource shortage, the resource occupation with the high-priority service is avoided, and the forwarding of basic data is ensured.
Furthermore, the weighted average queuing time delay is calculated by using a smoothing factor, so that packet loss and time delay caused by congestion and burst flow are avoided.
Furthermore, in the process of route calculation, the energy consumption of the satellite and the propagation delay of the link are considered, and data are transmitted in the shortest path on the premise of ensuring reliable transmission, so that reliable transmission is ensured.
Drawings
Fig. 1 is a flowchart of a satellite traffic classification routing method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of virtual topology on a satellite according to an embodiment of the present invention.
FIG. 3 is a diagram illustrating the analysis of the average remaining power of the EA and LASER networks according to an embodiment of the present invention.
Fig. 4 is a graph comparing the EA packet loss rates with the LASER packet loss rates in the embodiment of the present invention.
FIG. 5 is a graph comparing throughput of EA and LASER in an embodiment of the present invention.
Fig. 6 is a graph comparing end-to-end delay of EA and LASER in an embodiment of the present invention.
Fig. 7 is a graph comparing the packet loss ratios of the EA-TCR and the DSP in the embodiment of the present invention.
FIG. 8 is a graph comparing EA-TCR to DSP throughput in accordance with an embodiment of the invention.
FIG. 9 is a graph comparing the end-to-end delay of the EA-TCR and the DSP in an embodiment of the invention.
Fig. 10 is a diagram illustrating a comparison of packet loss rate analysis of class B services in the EA-TCR in the embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
as shown in fig. 1, a satellite traffic routing method based on energy sensing and load balancing includes the following steps:
step 1), pre-calculating and storing the topological information of each satellite on each satellite in the form of an adjacent matrix X [ k ] [ i ] [ j ]; topology information, i.e., information predictable in the satellite network;
each satellite restores the static topological data corresponding to each satellite when the snapshots are switched; each routing method is independently calculated on each satellite, in order to reduce the occupied storage space on the satellite, discrete topology information is stored by adopting an adjacent matrix, and the adjacent matrix is updated when the topology is updated, as shown in fig. 2.
The satellite network model specifically comprises: discretizing a continuously changing topology of a satellite into time periods t0,t1]，[t1,t2]，…，[tn-1,tn]The topology of each time segment is treated as invariant and abstracted as an undirected graph Gi＝(Vi,Ei) In which V isiRepresenting a set of satellite nodes, EiRepresenting the set of all inter-satellite links. In order to simplify calculation and realize on-satellite self-adaptive routing, an on-satellite adjacent matrix X [ k ] with topology information stored in advance][i][j]It represents the inter-satellite link transmission delay from satellite s (i) to satellite s (j) at the time of the kth snapshot. Based on the divided snapshot and the adjacency matrix, routes of different services are calculated according to the collected network information and the predictable partial information of the satellite network, and data packet transmission with differentiated priority is carried out.
Step 2), utilizing a link broadcast packet to regularly broadcast queuing delay, link and satellite energy information on each satellite to the whole network through a link information exchange mechanism, and updating information parameters for route calculation on each satellite;
step 3), updating the routing table on each satellite according to the routing schemes of different service types according to the adjacent matrix X [ k ] [ i ] [ j ] and the updated information parameters on each satellite; in the process of route transmission, when flow occurs, according to the service type label in the data packet header and the on-satellite routing table, sending data packets of different services into different buffer queues on a satellite transmission link corresponding to the data packets, and waiting for sending;
when the capacity of the buffer queue of each service reaches the upper limit, temporarily storing the data packet into a public waiting queue, and distributing different survival times according to different service types; when the data packet in the public waiting queue is empty corresponding to the exit buffer queue of the next hop, the data packet enters the buffer queue to wait for forwarding, otherwise, the value of the self survival time is reduced by 1, and the data packet is discarded when the survival time is 0;
for the satellite with the energy to be exhausted, informing the neighbor satellite to transmit the data packet to the satellite according to the proportional reduction, forwarding the data packet to the neighbor satellite with relatively sufficient energy, updating the topology information of the network, and returning to the step 2); if the number of the links which are not failed is reduced to 1, the satellite connected with the satellite only transmits the data packet of the last hop to the satellite, if the links are not recovered in a long time or the satellite links are all failed, the whole network topology information and the on-satellite information are updated, the global routing recalculation is triggered, and the step 1) is returned, so that the satellite traffic classification routing is completed.
Calculating a routing table according to different routing schemes by different services, wherein the service types comprise real-time services (A-type services), reliable services (B-type services) and QoS-free services (C-type services);
the path delay of the real-time service considers the satellite link propagation delay and the processing delay, requires real-time communication and has low delay; the link propagation delay and the queuing delay on the satellite cannot be ignored, and the link propagation delay can be calculated in advance by using an adjacent matrix of the topology; and the on-satellite queuing delay reflects the approximate link traffic load condition.
Updating the on-satellite queuing delay and the link propagation delay through a link information exchange mechanism, calculating a link path loss function, and finally calculating the route by utilizing a Dijkstra shortest path algorithm. The link propagation delay can be pre-calculated by using an adjacency matrix of the topology; the queuing time delay is calculated by adopting an exponential smoothing function, and the link path loss function is as follows:
costA(t)＝Td(t)+Tq(t) (4)
wherein, Td(T) and Tq(t) respectively representing the propagation delay and the average queuing delay of the link at the time t, and respectively updating at the interval of topology updating and flow updating; wherein the average queuing delay TqThe calculation formula of (t) is as follows:
Tq(t)＝(1-α)×ToldQ+α×TnewQ (5)
wherein, the weight factor alpha represents the average queuing delay T of the last snapshot and the current snapshotQInfluence of specific gravity, TQThe calculation formula of (a) is as follows:
Figure BDA0002711321460000111
qi(t) is the number of packets in the buffer queue at time t, PavgIs the length of the data packet, C is the inter-satellite link capacity; t is tnIs the start time of a time interval; and calculating weighted average queuing time delay by using the smoothing factor, thereby avoiding packet loss and time delay caused by congestion and burst flow.
The reliability service adopts a routing scheme based on satellite energy perception; reliable data transmission is required for reliable services, packet loss caused by inter-satellite link interruption and congestion needs to be considered in routing calculation, and particularly in a microsatellite network with limited energy, the transmission is interrupted due to satellite energy depletion, so that the packet loss is caused. In order to ensure reliable transmission, satellite energy consumption and propagation delay of a link are considered in the route calculation process, and data are transmitted in the shortest path on the premise of ensuring reliable transmission;
after the satellite energy at the time t is obtained through calculation of the satellite energy model, the satellite energy information is broadcasted to the whole network by using a link broadcast packet, relevant information on the satellite is updated, and a route is calculated by using a Dijkstra shortest path algorithm. In order to take different measures according to different energy levels of the network, the satellite residual energy is divided into three levels on the basis of energy perception, and when the time t is up, the ratio of the satellite residual energy R (t) to the satellite battery capacity B meets the requirement
Figure BDA0002711321460000112
And when the satellite energy is sufficient, calculating a route by using a weighted path loss function of the link propagation delay and the residual energy, wherein the weighted function is as follows:
Figure BDA0002711321460000113
Figure BDA0002711321460000114
whereinDl(i, j) is the link propagation delay between satellite i and satellite j at snapshot t, DmaxAnd DminRespectively, the maximum propagation delay and the minimum propagation delay between any two satellite nodes. El(i, j) represents the energy state of the link ij, which is related to the remaining energy condition of the satellite nodes at both ends of the link, as shown in equation 8.
The weight factor mu reflects the energy condition of the whole satellite network, when the mu is larger, the condition is good, and the path with the minimum transmission delay tends to be selected during route calculation. When mu is smaller, the network energy is about to be exhausted, and a satellite with sufficient residual energy is selected as far as possible to forward the data packet, so that the data packet is ensured not to be lost. The weight factor mu needs to be updated at each snapshot interval to reflect the energy consumption condition of the network in time, and R is utilizediRepresenting the residual energy of the satellite, μ is calculated and updated as follows:
Figure BDA0002711321460000121
when it is satisfied with
Figure BDA0002711321460000122
And when the satellite energy consumption is high, the flow needs to be dispersed to the satellite with light energy consumption and sufficient residual energy, and the path weights of all the inlet and outlet links connected with the satellite are added with alpha, so that the energy exhaustion caused by the concentration of excessive data packets on the satellite is prevented. The weight α is related to the energy consumption of the satellite nodes at both ends of the link ij and the time in the earth shadow, and the calculation formula is as follows:
Figure BDA0002711321460000123
where e denotes whether the satellite is in the shadow of the earth,
Figure BDA0002711321460000124
Ei(T) energy lost by satellite i at snapshot T, Ti(t) is the time that the satellite i is in the shadow, when the satellite consumes more energy and lasts longer in the shadow, the residual energy of the satellite is not enough to guarantee long-time data transmission, and the data packet is sent to the satellite in the next routing update process.
When it is satisfied
Figure BDA0002711321460000125
And when the energy of the satellite is about to be exhausted, informing the neighbor satellite to reduce the sending data packet according to the corresponding proportion, and forwarding the data packet to the neighbor satellite with relatively sufficient energy.
Parameter E of energy rating1And E2Depending on the probability of packet dropping due to energy depletion, let I and O be the on-satellite input and output data rates respectively,tfor the time that the satellite is energy depleted, the following is calculated:
Figure BDA0002711321460000131
the satellite broadcasts packets to update the satellite energy information at intervals, and the interval of the energy updating is deltatIf, ift≤+ΔtIt means that the energy of the satellite is exhausted before the satellite in the network receives the information update route of the broadcast packet, which will result in the packet being discarded, and the probability of discarding the packet is 1. If it ist>+ΔtThe probability of packet dropping is
Figure BDA0002711321460000132
The probability of packet dropping can therefore be expressed as:
Figure BDA0002711321460000133
so parameter E of energy rating1And E2Is set as1＝p，
Figure BDA0002711321460000134
When the remaining energy level of the satellite is low,tsmaller, then p takes a larger value, E1And correspondingly, the satellite with higher energy consumption takes measures as soon as possible, disperses the data packet to the satellite with sufficient energy and informs the neighbor satellite to reduce the data transmission.
Aiming at the QoS-free service, the most basic data forwarding needs to be ensured, while basic data transmission is ensured, in order to avoid resource occupation with the service with high priority, the path delay only considers the propagation delay of the inter-satellite link, and N link disjoint candidate multi-path sets are calculated; selecting the optimal path in the candidate multi-path set according to the energy consumption and the link utilization condition of the satellite nodes on the candidate multi-path for forwarding, wherein the routing weight is calculated as follows:
Figure BDA0002711321460000135
Figure BDA0002711321460000136
Figure BDA0002711321460000141
where mu still represents the energy situation of the entire satellite network, Ep(t) energy consumption of the satellite nodes on the shortest path concentration path p in the snapshot t, EaveIs the average energy loss of all satellite nodes on the path p. L isp(t) is the number of times one of the intersatellite links on path p is utilized, LaveThe average utilization number of all the interstellar links on the path.
When the network energy condition is good, a path with less link utilization times is selected to prevent partial satellites and links from being congested, and when the network energy is insufficient, a satellite with less energy loss, namely a satellite which is idle and cannot exhaust energy in transmission, is selected for transmission.
In order to avoid a routing loop caused by the update of the candidate path set, the satellite nodes which the data packet passes through are recorded in the packet head of the data packet, and when the selected optimal next hop is already stored in the packet head, the data packet is switched to the next-best next hop until no next hop can be selected, and the data packet is discarded.
On the satellite, data packets of different services enter different buffer queues, in the route forwarding stage, a priority sending queue mechanism is used for sending the data packets, and each satellite output link is composed of three mutually independent buffer queues. When the flow occurs, according to the service label in the data packet header and the route forwarding table on the satellite, the data packets of different services are sent into different buffer queues on the corresponding satellite sending link and sent according to the priority. Each buffer queue divides the queue length according to the priority of the service, and the low-delay service is transmitted preferentially, so that the congestion probability is low, and the buffer space is smaller compared with other services. And entering a corresponding buffer queue according to the mark of the service classification in the data packet, wherein the real-time service is sent in preference to other services so as to ensure the requirement of low delay, and the reliable service is in preference to the QoS-free service.
In order to avoid discarding the packet when the satellite buffer queue of a certain service reaches the upper limit of the capacity, a common queue is arranged on the satellite, the space of the common queue is obtained by subtracting the total buffer queue capacity of the satellite exit link from the total capacity of the satellite buffer space, when the flow of the certain service or the certain exit link is overlarge, the data packet can be buffered by using the residual space of other buffer queues, and when different service data packets enter the common queue, different TTLs (time to live) are allocated, the TTL (time to live) of the low-delay service is relatively small, and the TTLs of other services are relatively large. And when the exit buffer queue to be forwarded is vacant, the data packet enters the buffer queue to wait for forwarding, otherwise, the TTL value of the data packet is subtracted by 1, and the data packet is discarded when the TTL value is 0.
Since the class a service has a high requirement on real-time performance, the class a service updates the routing table at regular intervals with smaller traffic update intervals, while the routing tables of other classes of services are updated at intervals of topology update.
Due to the fact that the real-time service congestion probability is small, distributed TTL (time to live) is relatively small, and TTL (time to live) of reliable services and QoS-free services is relatively large.
Satellite energy model: microsatellites have a relatively limited battery capacity and are battery powered when in the shadow of the earth. Even if the satellite has sufficient energy to pass through the earth shadow, the battery discharge depth has a great influence on the service life of the battery when solar eclipses occur, and the service life of the battery is directly shortened. And the satellite cost is relatively high, the satellite battery charge and discharge times are limited, the unreasonable routing algorithm can unbalance the energy of the satellite network, and the service life of the network is shortened. For this reason, the energy level of the satellite should be considered in the routing, and the energy consumed by the satellite mainly includes static energy loss for maintaining the operation of the satellite and dynamic energy loss for transmitting and receiving data.
The total energy consumption calculation formula of the satellite i at the time of the snapshot t is as follows:
Figure BDA0002711321460000151
wherein, Cij(t) is the capacity of link ij, Ps、Pr、PoRespectively satellite transmission power, received power and operating power, ΔtIs the snapshot interval.
Due to the periodic motion of the satellite, the satellite periodically crosses the shadow and the sun irradiation area, the energy obtained by the satellite i at the snapshot t is related to the time of receiving the sun irradiation under the snapshot, and the calculation formula is as follows:
Gi(t)＝Pc×(Δt-Ti(t)) (2)
wherein, Ti(t) time of the snapshot immediately before time t, satellite i in shadow, PcCharging power for the battery.
The remaining energy of the satellite i at the time of the snapshot t can be obtained from equations (1) and (2):
Ri(t)＝min{B,Ri(t-1)-Ei(t)+Gi(t)} (3)
wherein B is the maximum battery capacity of the satellite, RiAnd (t-1) is the residual energy of the satellite before the t snapshot.
In order to illustrate the effect of the present invention, the routing scheme proposed herein is modeled and simulated by way of STK and Matlab interconnection. And (3) a polar orbit constellation is established by using STK software, and a communication simulation process of the route is realized in Matlab by adopting a virtual topology strategy with equal time intervals. Simulation related parameters are shown in table 1:
TABLE 1 simulation parameters
Number of tracks 6 Topological interval 150s
Number of satellites per orbit 11 Satellite battery capacity 2600joule
Inclination angle of track 86.4 Transmission power 7watt
Period of track 110.4min Received power 3watt
Height 780km Operating power 4watt
Packet length 200bytes Charging power 5watt
(1) Routing (EA) performance analysis based on energy awareness
Firstly, the performance analysis is carried out on the routing based on energy perception in the invention, only aiming at a single service, and most of the simulation parameters are shown in the table 1. During simulation, the length of an on-satellite buffer queue is set to be 30, the data sending rate range is 8-12 Mbps, the inter-satellite link capacity is 4Mbps, and the initial energy is far lower than the battery capacity under the condition that a plurality of satellites are influenced by solar eclipse. And comparing and analyzing the routing (EA) based on satellite energy perception and the routing (LASER) based on position and load perception according to performance indexes such as average remaining power ratio, packet loss rate, throughput and end-to-end time delay.
Fig. 3 shows that when the average remaining capacity ratio of the network is higher when the satellite is affected by solar eclipses and shadows compared to the average remaining capacity ratio of the network for LASER, EA routing can extend the lifetime of the network and make the network have more uniform energy.
Fig. 4, fig. 5, and fig. 6 respectively compare packet loss rates, throughputs, and end-to-end delays of EA and LASER at different data transmission rates, and it can be seen from the graphs that EA routes have lower packet loss rates and higher throughputs. The performance of the proposed scheme is superior to LASER in terms of packet loss rate and throughput. But the difference between EA and LASER is not obvious in terms of end-to-end delay, because the proposed scheme optimizes data transmission on the premise of improving reliability.
Traffic classification routing (EA-TCR) performance analysis based on energy perception
On the basis of the EA route, the EA-TCR route integrates the requirements of various services, adopts different routing schemes aiming at different service flows, introduces a priority forwarding queue and a public queue mechanism, and simulation parameters are shown in a table 1. The simulation analysis shows that when the network energy is insufficient and the network is congested, the EA-TCR and DSP performances are achieved, the inter-satellite link capacity C is set to be 2.4Mbps, and the flow data rate range is 10.4-14.4 Mbps. Also assuming that several satellites are affected by solar eclipse, the initial energy is much lower than the battery capacity. The total buffer queue capacity of each satellite is set to be 120, in order to keep the total buffer queue capacity of the satellite consistent in the two routing schemes, the total buffer queue length of each exit link in the EA-TCR routing is 24, the buffer queue length of A, B, C type traffic is 4, 10 and 10 respectively, and the common queue length is 24. The buffer queue length for the comparative routing scheme is 30. A. B, C class packets are assigned time-to-live TTLs of 10, 45, and 45, respectively, in the common queue.
Fig. 7, 8, and 9 respectively compare the packet loss rate, throughput, and end-to-end delay performance of EA-TCR and DSP at different data transmission rates. As can be seen from fig. 7 and 8, the EA-TCR has better performance in terms of packet loss rate and throughput performance than the DSP in terms of overall performance of the network. In the aspect of end-to-end delay, as shown in fig. 9, the end-to-end delay of each type of service in the DSP route increases with the increase of the data rate, and the delay increases more significantly when the network is congested. EA-TCR routing can ensure that the A-type service is transmitted in real time with lower time delay when congestion occurs, and the end-to-end time delay of the service is increased without time delay. In fig. 10, the packet loss rate of the class B service is analyzed separately, and it can be seen that when the network energy is insufficient and is congested, the packet loss rate of the class B service is lower than that of the DSP, and the proposed scheme ensures reliable transmission of the class B service.

Claims (10)

1. A satellite traffic routing method based on energy perception and load balancing is characterized by comprising the following steps:
step 1), calculating and storing the topological information of each satellite on each satellite in the form of an adjacent matrix;
step 2), utilizing a link broadcast packet to regularly broadcast queuing delay, link and satellite energy information on each satellite to the whole network through a link information exchange mechanism, and updating information parameters for route calculation on each satellite;
step 3), updating the routing table on each satellite according to the routing schemes of different service types according to the adjacent matrix and the updated information parameters on each satellite;
in the process of route transmission, when flow occurs, according to the service type label in the data packet header and the on-satellite routing table, sending data packets of different services into different buffer queues on a satellite transmission link corresponding to the data packets, and waiting for sending;
when the capacity of the buffer queue of each service reaches the upper limit, temporarily storing the data packet into a public waiting queue, and distributing different survival times according to different service types; when the data packet in the public waiting queue is empty corresponding to the exit buffer queue of the next hop, the data packet enters the buffer queue to wait for forwarding, otherwise, the value of the self survival time is reduced by 1, and the data packet is discarded when the survival time is 0;
for the satellite with the energy to be exhausted, informing a neighbor satellite to reduce sending data packets to the satellite, forwarding the data packets to the neighbor satellite with relatively sufficient energy, and updating the topology information of the network; if the number of the links which are not failed is reduced to 1, the satellite connected with the satellite only transmits the data packet of the last hop to the satellite, if the links are not recovered in a long time or the satellite links are all failed, the whole network topology information and the on-satellite information are updated, the global routing recalculation is triggered, and the step 1) is returned, so that the satellite traffic classification routing is completed.
2. The satellite traffic routing method based on energy awareness and load balancing according to claim 1, wherein each satellite recovers the static topology data corresponding to each satellite during snapshot switching.
3. The satellite stream based on energy awareness and load balancing according to claim 1Method for volume routing, characterized in that a continuously changing topology of satellites is discretized into a number of time periods t0,t1]，[t1,t2]，…，[tn-1,tn]The topology of each time segment is treated as invariant and abstracted as an undirected graph Gi＝(Vi,Ei) In which V isiRepresenting a set of satellite nodes, EiAn adjacency matrix X [ k ] representing the set of all inter-satellite links on which topology information is pre-stored][i][j]It represents the inter-satellite link transmission delay from satellite s (i) to satellite s (j) at the time of the kth snapshot.
4. The satellite traffic routing method based on energy awareness and load balancing according to claim 1, wherein the traffic types include real-time traffic, reliability traffic, and QoS-less traffic.
5. The satellite traffic routing method based on energy awareness and load balancing according to claim 4, wherein the real-time traffic routing updates the on-satellite queuing delay and the link propagation delay through a link information exchange mechanism, calculates a link path loss function, and finally calculates the real-time traffic propagation routing by using a Dijkstra shortest path algorithm.
6. The satellite traffic routing method based on energy perception and load balancing according to claim 5, wherein the queuing delay is calculated by an exponential smoothing function, and the link path loss function is:
costA(t)＝Td(t)+Tq(t) (4)
wherein, Td(T) and Tq(t) respectively representing the propagation delay and the average queuing delay of the link at the time t, and respectively updating at the interval of topology updating and flow updating; wherein the average queuing delay TqThe calculation formula of (t) is as follows:
Tq(t)＝(1-α)×ToldQ+α×TnewQ (5)
wherein the weight factor alpha representsAverage queuing delay T of last snapshot and current snapshotQInfluence of specific gravity, TQThe calculation formula of (a) is as follows:
Figure FDA0002711321450000021
qi(t) is the number of packets in the buffer queue at time t, PavgIs the length of the data packet, C is the inter-satellite link capacity; t is tnIs the start time of a time interval.
7. The satellite traffic routing method based on energy perception and load balancing according to claim 4, wherein the reliability service adopts a routing method based on satellite energy perception, after satellite energy at time t is obtained through calculation of a satellite energy model, satellite energy information is broadcasted to the whole network by using a link broadcast packet, relevant information on the satellite is updated, and a route is calculated;
when the ratio of the satellite residual energy R (t) to the satellite battery capacity B at the moment t satisfies
Figure FDA0002711321450000031
And then, calculating a route by using a weighted path loss function of the link propagation delay and the residual energy, wherein the weighted function is as follows:
Figure FDA0002711321450000032
Figure FDA0002711321450000033
wherein Dl(i, j) is the link propagation delay between satellite i and satellite j at snapshot t, DmaxAnd DminRespectively the maximum propagation delay and the minimum propagation delay between any two satellite nodes; el(i, j) represents the energy state of link ij;
the weighting factor mu needs to be updated every snapshot interval, using RiRepresenting the residual energy of the satellite, μ is calculated and updated as follows:
Figure FDA0002711321450000034
when it is satisfied with
Figure FDA0002711321450000035
And then adding alpha to the path weight of all the import and export links connected with the satellite, wherein the weight alpha is related to the energy consumption condition of the satellite nodes at two ends of the link ij and the time in the earth shadow, and the calculation formula is as follows:
Figure FDA0002711321450000036
where e denotes whether the satellite is in the shadow of the earth,
Figure FDA0002711321450000041
Ei(T) energy lost by satellite i at snapshot T, Ti(t) the time of the satellite i in the shadow, when the energy consumption of the satellite is larger and the duration time in the shadow is longer, the residual energy of the satellite is not enough to guarantee long-time data transmission, and the data packet is reduced to be sent to the satellite in the next route updating process;
when it is satisfied with
Figure FDA0002711321450000042
And informing the neighbor satellites to reduce the sending data packets according to the corresponding proportion, and forwarding the data packets to the neighbor satellites with relatively sufficient energy.
8. The satellite traffic routing based on energy awareness and load balancing of claim 7Method, characterized by a parameter E of energy rating1And E2Depending on the probability of packet dropping due to energy depletion, let I and O be the on-satellite input and output data rates respectively,tfor the time that the satellite is energy depleted, the following is calculated:
Figure FDA0002711321450000043
the satellite broadcasts packets to update the satellite energy information at intervals, and the interval of the energy updating is deltatIf, ift≤+ΔtAt this time, the probability of discarding the data packet is 1; if it ist>+ΔtThe probability of packet dropping is
Figure FDA0002711321450000044
The probability of packet dropping can therefore be expressed as:
Figure FDA0002711321450000045
so parameter E of energy rating1And E2Is set as1＝p，
Figure FDA0002711321450000046
When the remaining energy level of the satellite is low,tsmaller, then p takes a larger value, E1And correspondingly, the satellite with higher energy consumption takes measures as soon as possible, disperses the data packet to the satellite with sufficient energy and informs the neighbor satellite to reduce the data transmission.
9. The satellite traffic routing method based on energy awareness and load balancing according to claim 4, wherein the specific routing method for QoS-less traffic comprises: calculating N link disjoint candidate multi-path sets; selecting the optimal path in the candidate multi-path set according to the energy consumption and the link utilization condition of the satellite nodes on the candidate multi-path for forwarding, wherein the routing weight is calculated as follows:
Figure FDA0002711321450000051
Figure FDA0002711321450000052
Figure FDA0002711321450000053
where mu still represents the energy situation of the entire satellite network, Ep(t) energy consumption of the satellite nodes on the shortest path concentration path p in the snapshot t, EaveFor the average energy loss, L, of all satellite nodes on the path pp(t) is the number of times one of the intersatellite links on path p is utilized, LaveThe average utilization number of all the interstellar links on the path.
10. A satellite traffic routing system based on energy perception and load balancing is characterized by comprising a satellite network topology matrix module, a satellite network parameter updating module and a routing module;
the satellite network topology matrix module is used for calculating, transmitting and storing the topology information of each satellite on each satellite in the form of an adjacent matrix; the satellite network parameter updating module broadcasts queuing delay, link and satellite energy information on each satellite to the whole network at regular time through a link information exchange mechanism by using a link broadcast packet, and updates information parameters used for route calculation on each satellite;
the routing module updates the routing table on each satellite according to the adjacent matrix and the updated information parameters on each satellite and the routing schemes of different service types; when the flow occurs, sending data packets of different services into different buffer queues on a satellite transmission link corresponding to the data packets according to the service type labels in the data packet headers and the on-satellite routing table, and waiting for transmission;
when the capacity of the buffer queue of each service reaches the upper limit, temporarily storing the data packet into a public waiting queue, and distributing different survival times according to different service types; when the data packet in the public waiting queue is empty corresponding to the exit buffer queue of the next hop, the data packet enters the buffer queue to wait for forwarding, otherwise, the value of the self survival time is reduced by 1, and the data packet is discarded when the survival time is 0;
for the satellite with the energy to be exhausted, informing a neighbor satellite to reduce sending data packets to the satellite, forwarding the data packets to the neighbor satellite with relatively sufficient energy, and updating the topology information of the network; if the number of the links which are not failed by the satellite is reduced to 1, the satellite connected with the satellite only transmits a data packet of the last hop to the satellite, and if the links are not recovered or the satellite links are all failed within a long time, the whole network topology information and the on-satellite information are updated, and the global routing recalculation is triggered.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113709876A (en) * 2021-07-08 2021-11-26 北京邮电大学 Satellite service resource allocation method and electronic equipment
CN113938176A (en) * 2021-08-26 2022-01-14 西安空间无线电技术研究所 Low-delay service space-based computing method
CN114629543A (en) * 2022-01-28 2022-06-14 航天东方红卫星有限公司 Satellite network adaptive traffic scheduling method based on deep supervised learning
CN114828144A (en) * 2022-03-27 2022-07-29 西安电子科技大学 Low-earth-orbit satellite constellation-oriented service quality guarantee routing method
CN116633426A (en) * 2023-07-25 2023-08-22 鹏城实验室 Satellite routing method, device and storage medium
CN117674961A (en) * 2023-11-20 2024-03-08 航天恒星科技有限公司 Low orbit satellite network time delay prediction method based on space-time feature learning

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7164661B2 (en) * 2000-04-14 2007-01-16 Hughes Networks Systems, Llc System and method for providing a two-way satellite system
CN102118312A (en) * 2011-01-27 2011-07-06 南京邮电大学 Hierarchical Ad hoc on-demand distance vector (AODV) routing method
CN104902515A (en) * 2015-06-08 2015-09-09 西安电子科技大学 Load aware-based multi-layer satellite network routing method
CN105897329A (en) * 2016-06-08 2016-08-24 大连大学 Multi-service routing optimization method of LEO satellite network based on multi-objective decisions
CN105916183A (en) * 2016-06-15 2016-08-31 上海物联网有限公司 Wireless sensor network routing method based on link quality and residual energy
CN106162752A (en) * 2016-07-17 2016-11-23 西安电子科技大学 It is applicable to the load balancing method for routing of air-ground integrated network
CA2981855A1 (en) * 2015-04-10 2016-12-08 Viasat, Inc. Ground based antenna beamforming for communications between access nodes and users terminals linked by a satelliten and satellite therefore
CN106686659A (en) * 2017-02-14 2017-05-17 重庆邮电大学 AOMDV-based energy aware node-disjoint multipath routing algorithm
CN107634915A (en) * 2017-08-25 2018-01-26 中国科学院计算机网络信息中心 Data transmission method, device and storage medium
CN108366409A (en) * 2018-03-13 2018-08-03 重庆邮电大学 A kind of reliable multipath polyaluminium chloride PAC algorithm based on balancing energy
CN110650511A (en) * 2018-06-26 2020-01-03 云南电网有限责任公司 Improved AODV routing protocol based on energy consumption and load

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7164661B2 (en) * 2000-04-14 2007-01-16 Hughes Networks Systems, Llc System and method for providing a two-way satellite system
CN102118312A (en) * 2011-01-27 2011-07-06 南京邮电大学 Hierarchical Ad hoc on-demand distance vector (AODV) routing method
CA2981855A1 (en) * 2015-04-10 2016-12-08 Viasat, Inc. Ground based antenna beamforming for communications between access nodes and users terminals linked by a satelliten and satellite therefore
CN104902515A (en) * 2015-06-08 2015-09-09 西安电子科技大学 Load aware-based multi-layer satellite network routing method
CN105897329A (en) * 2016-06-08 2016-08-24 大连大学 Multi-service routing optimization method of LEO satellite network based on multi-objective decisions
CN105916183A (en) * 2016-06-15 2016-08-31 上海物联网有限公司 Wireless sensor network routing method based on link quality and residual energy
CN106162752A (en) * 2016-07-17 2016-11-23 西安电子科技大学 It is applicable to the load balancing method for routing of air-ground integrated network
CN106686659A (en) * 2017-02-14 2017-05-17 重庆邮电大学 AOMDV-based energy aware node-disjoint multipath routing algorithm
CN107634915A (en) * 2017-08-25 2018-01-26 中国科学院计算机网络信息中心 Data transmission method, device and storage medium
CN108366409A (en) * 2018-03-13 2018-08-03 重庆邮电大学 A kind of reliable multipath polyaluminium chloride PAC algorithm based on balancing energy
CN110650511A (en) * 2018-06-26 2020-01-03 云南电网有限责任公司 Improved AODV routing protocol based on energy consumption and load

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
MINGLONG CHEN 等: "Joint Route Selection and Resource Allocation Algorithm for Data Relay Satellite Systems Based on Energy Efficiency Optimization", 《2019 11TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP)》 *
冯玺宝: "多层卫星网络QoS路由协议研究", 《中国优秀硕士学位论文全文数据库》 *
夏慧云: "基于拓扑和路由结合的分布式卫星组网方法研究", 《中国优秀硕士学位论文全文数据库》 *
赵洪利 等: "《空间信息传输与仿真技术》", 31 December 2011, 《中国宇航出版社》 *

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113709876A (en) * 2021-07-08 2021-11-26 北京邮电大学 Satellite service resource allocation method and electronic equipment
CN113709876B (en) * 2021-07-08 2023-06-20 北京邮电大学 Satellite service resource allocation method and electronic equipment
CN113938176A (en) * 2021-08-26 2022-01-14 西安空间无线电技术研究所 Low-delay service space-based computing method
CN114629543A (en) * 2022-01-28 2022-06-14 航天东方红卫星有限公司 Satellite network adaptive traffic scheduling method based on deep supervised learning
CN114629543B (en) * 2022-01-28 2024-03-29 航天东方红卫星有限公司 Satellite network self-adaptive flow scheduling method based on deep supervised learning
CN114828144A (en) * 2022-03-27 2022-07-29 西安电子科技大学 Low-earth-orbit satellite constellation-oriented service quality guarantee routing method
CN116633426A (en) * 2023-07-25 2023-08-22 鹏城实验室 Satellite routing method, device and storage medium
CN116633426B (en) * 2023-07-25 2023-10-27 鹏城实验室 Satellite routing method, device and storage medium
CN117674961A (en) * 2023-11-20 2024-03-08 航天恒星科技有限公司 Low orbit satellite network time delay prediction method based on space-time feature learning
CN117674961B (en) * 2023-11-20 2024-05-28 航天恒星科技有限公司 Low orbit satellite network time delay prediction method based on space-time feature learning

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