CN110381470A - The access of service quality guarantee oriented controls combined optimization method in a kind of railway Internet of Things - Google Patents
The access of service quality guarantee oriented controls combined optimization method in a kind of railway Internet of Things Download PDFInfo
- Publication number
- CN110381470A CN110381470A CN201910669225.9A CN201910669225A CN110381470A CN 110381470 A CN110381470 A CN 110381470A CN 201910669225 A CN201910669225 A CN 201910669225A CN 110381470 A CN110381470 A CN 110381470A
- Authority
- CN
- China
- Prior art keywords
- frequency spectrum
- access
- combined optimization
- things
- internet
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/0231—Traffic management, e.g. flow control or congestion control based on communication conditions
- H04W28/0236—Traffic management, e.g. flow control or congestion control based on communication conditions radio quality, e.g. interference, losses or delay
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/0268—Traffic management, e.g. flow control or congestion control using specific QoS parameters for wireless networks, e.g. QoS class identifier [QCI] or guaranteed bit rate [GBR]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
- H04W28/18—Negotiating wireless communication parameters
- H04W28/22—Negotiating communication rate
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/42—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft
-
- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- 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
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Aviation & Aerospace Engineering (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses the accesses of service quality guarantee oriented in a kind of railway Internet of Things of internet of things field to control combined optimization method, comprising: introduces blank frequency spectrum to promote network throughput；The fairness and stability for introducing utility function guarantee access control program user improve the QoS (service quality) in access control；It is proposed a kind of Internet of Things access control combined optimization model for taking into account rate control and frequency spectrum distribution；The access control process provided, which specifically includes that, first carries out the frequency spectrum original allocation based on greediness coloring；Meet the stable constraint of combined optimization model according to distributed rate control algolithm again；New distribution is finally carried out to frequency spectrum using dynamic frequency spectrum deployment algorithm.After implementing combined optimization, the access of railway Internet of Things can be made to control and ensured with more QoS.
Description
Technical field
The present invention relates to a kind of technical methods of internet of things field, and in particular to a kind of to ensure railway Internet of Things
After service quality introduces blank frequency spectrum and utility function, initial spectrum distributes the access control combined with dynamic frequency spectrum deployment technology
Combined optimization method processed.
Background technique
Internet of Things is the internet between article, is the extension of internet and communication network and application of extending, it makes full use of
Existing network technology, in conjunction with sensing and Radio Frequency Identification Technology so that realizing information exchange and seamless chain between object and people, object and object
It connects.Technology mixing together, which is carried out, using technology of Internet of things and other field is inevitable development trend.Introduce Internet of Things skill
Postoperative, great change has occurred in railway systems.Firstly, the deployment of internet of things equipment can make railway transportation have more protection.Than
Such as, upper sufficient amount of sensor is disposed around railroad track, can collect track status information, train axle temperature letter well
The data such as breath, while the important persons such as driver carry wireless wearable device with collection of bodily health data, so as to burst
Situation makes counter-measure.Furthermore train operation quotient can carry out real-time geographic positioning to train by internet of things equipment and divide
Its driving status is analysed, passengers quantity in compartment and station Waiting Passengers number are captured and analyzed, so as to guarantee driving safety
More effectively run train.Finally, internet of things equipment can provide ticket information, position, consumption of passenger etc., so as to
Train operation quotient can provide more personalized, quality services for passenger.But as the huge more internet of things equipment of quantity is disposed
In the railway system, the railway system becomes more dependent on wireless connection, it means that it is easier by external disturbance, invasion and net
Network attack.For intensive railway network, with the increase of passengers quantity, the quickening of travel speed, even slight
Interruption can all cause serious consequence.So the solution of safety problem becomes more and more important.Network connection in Internet of Things is by access layer
It controls, sensor and the connection of internet between the two may be implemented in it.This connection needs the auxiliary of basic network equipment, than
Such as current base station, WiFi, satellite network.So railway Internet of Things to be made to possess enough safety guarantee, it must just ensure and connect
The safety entered.In the network access technique of railway Internet of Things, " last is public for smart machine in major concern Internet of Things or Sensor Network
In " local access the problem of.Wherein, relevant wireless access technology have Zigbee, bluetooth, LoRa, SigFox, NB-IoT and
LTE-eMTC etc..In information exchange and communication in access, time delay and handling capacity this to index in occupation of important position.But
Both contradict to a certain extent, it will usually for handling capacity raising and ignore transmission quality, be transmission quality
It improves and time delay is caused to increase.
It finds by prior art documents, a kind of patent " function in narrowband Internet of things system of Founder jump et al.
Consumption optimization method and terminal " in propose according to different system modes and take different low power configurations, it is excellent to reach efficiency
Change purpose.The patent " a kind of Internet of things node access CHANNEL OPTIMIZATION selection method " of Ma Li et al., what business was classified
On the basis of, network insertion is carried out using Markov model, not only meets each terminal traffic demand, also improves Internet resources benefit
With rate.Article " the White Space Networking with Wi-Fi like of Paramvir Bahl et al.
Connectivity " realizes the raising of throughput of system in WLAN using blank frequency spectrum.M.J.Neely's et al.
Network utility Optimized model is proposed in " Delay-Based Network Utility Maximization " text to come with this
Optimize time delay.But these work are all only to consider a kind of index, such as energy consumption, time delay and handling capacity, are carried out to it single excellent
Change.
Summary of the invention
The present invention provides a kind of access control combined optimization method of service quality guarantee oriented in railway Internet of Things, application
In the railway Internet of Things access net with dynamic spectrum access ability, it can guarantee network by introducing utility function and choosing
Stable network capacity region, on the basis of rationally making full use of blank frequency spectrum, so that each access device in railway Internet of Things
Rate control and frequency spectrum distribute two factors reach optimization.
To reach above-mentioned combined optimization method, technical solution of the present invention includes:
Access control system on railway Internet of Things of the present invention is mainly made of three parts: controller, several
User, several wireless access points, wherein controller is monitored and controls to all wireless access points, and can regularly count
Calculate the interference between all wireless access points and user；The access point can have multiple wireless interfaces, but user only has one
A interface and only it is connected with an access point；Abstractively, indicate that the wireless interface collection of all access points, C indicate user with I
Collection, R indicate that effective transmission link collection between user and access point, N indicate the interference figure between the wireless interface of all access points, N
(i) other wireless interface set for indicating interference wireless interface i, remember i ∈ N (i).
The present invention uses the discrete time slots system that the time is divided into tiny time slot, while using first in, first out FIFO's
Message buffering way to manage；A ∈ I ∪ C, i.e. wireless access point and user all can serve as source node；B ∈ C, i.e. user are ok
As node；In network layer, a rate controller is placed, the rate for the message that network layer is entered from transport layer is carried out effective
Control；From source node a, the message transmitting spped rate that message is sent to destination node b is denoted asThe meeting at source node a
Maintenance flows to the message buffering queue of destination node bThe message access rate of the buffering queue isMoreover, it is assumed that
Transmission between all nodes is all independent identically distributed；There are following related constraint relationships between each rate:
Wherein, ωa,max(t) the maximum polymerization access rate that network can achieve at node a, μ are indicateda,max(t) section is indicated
The maximum polymerization transmission rate that network can achieve at point a.
In addition, providing as followsWithLong term time average value expression:
The queue dynamic of source node a to destination node b is updated, is indicated are as follows:
Wherein, []+It indicates when for positive number, directly uses, when for negative, use numerical value 0；Cl (i) is indicated
The user's collection being connected with wireless interface i；Second formula indicates to be cable network for purpose or be connected with other access points
User message, access point does not need to be cached；Third formula indicates not need at the destination nodes of all transmission pair
Association message is cached.
Present invention introduces virtual subnet queues, assess whereby the wireless interface load of access point；The virtual subnet
Nets's column are the variables that can reflect out sub-network load situation, and value is bigger, then illustrates that sub-network load is heavier, to need
More frequency spectrum resources increase channel capacity, the final buffering queue length for reducing network, the congestion for alleviating subnet；
The dynamic of virtual subnet queue is updated, is indicated are as follows:
Vi(t+1)=[Vi(t)-μi(t)+ωi(t)]+
μi(t)≤Capai(t)
Wherein, Capai(t) channel capacity of wireless interface i, μ are indicatedi(t) use for indicating wireless interface i and being attached thereto
The aggregation transfer rate of Radio Link between family, ωi(t) the polymerization access rate of all nodes in corresponding subnet is indicated, finally
One formula means that the maximum aggregation transfer rate of all transmission in corresponding subnet is equal with the channel capacity of wireless interface i.
The utility function that the present invention uses logarithm to synthesize, general type areWherein ωiIt is elasticity
Coefficient, logarithmic form can reduce xiSize, to avoid the abnormal of great fluctuation process to occur to a certain extent, specifically, this hair
Utility function form used in bright are as follows:
Wherein,It is coefficient of elasticity,Indicate time averaging virtual subnet queue,It indicates based on son
The time average polymerization transmission rate of net, τ are balanceWithThe impact factor that the two distributes frequency spectrum.
The present invention selects network capacity region Π, by what can all be supported by network with ratio sharing modeSet
Composition, can make throughput of system optimize on the basis of guaranteeing network stabilization；It avoids using traditional network capacity area
Domain is because the final result solved in this capacity region will lead to network stabilization and be destroyed, thus in actual use
Success rate it is extremely low.
Step 1: system access control combined optimization model is established；
There is the network utility function that setting uses convex, non-subtract can be described as with serial correlation characteristic, combined optimization model:
Wherein, first constraint condition may insure proportional fairness, and can make the average standard of the long term time of all nodes
Enter rate to be in the Π of network capacity region, second constraint condition show long term time be averaged access rate cannot be greater than it is long-term
Time is averaged transmission rate；Also need simultaneously it is clear, the frequency spectrum assignment constraints of access point wireless interface the size of Π；If used
Traditional network capacity region, final result will lead to network stabilization and be destroyed；So can be using network capacity region Π
Guarantee on the basis of network stabilization throughput of system to be optimized.
Step 2: the distribution of system initial spectrum is carried out；
The present invention uses the frequency spectrum allocation algorithm based on greediness coloring to acquire the initial solution that frequency spectrum distributes；First processing input
Data, data are constituted into non-directed graph, ascending order arrangement and number using the degree of each node；Simultaneously by color to be employed
It is numbered, arranges from small to large by number；It then, is each node-coloring according to dependency rule；According to node each after coloring
The difference of color, classifies to channel；Finally using consumed number of color is coloured, blank frequency spectrum is allocated, is obtained
Frequency spectrum distribution solution；Wherein dependency rule are as follows: node and color are used from small to large according to number, and adjacent node face
Color must be different.
Step 3: access control combined optimization is carried out；
Using the distributed rate control algolithm optimized based on Lyapunov, so that the stable constraint of combined optimization model
Met；Specific implementation is made of both the rate controller of meshed network layer and link scheduler of access point；The former can
To control the rate of the message flow in network layer by upper-layer protocol injection, and the buffering queue length of each transport stream determines in node
The rate；The latter is to carry out Radio Link scheduled transmission according to the buffering team leader difference between access point and coupled user,
So that the buffering queue entire length in subnet reaches minimum.
(1), rate controller: in each time slot, the access rate of all messages for being transmitted to b is controlled at node a
System, optimization problem are described as follows:
Wherein, it is balanced for the optimization that stresses to handling capacity and time delay, introduces γ balance parameters；Set utility function tool
Have it is convex, non-subtract and the characteristics such as continuous, so the optimal solution of this optimization problem can be obtained by directly carrying out first derivation；
(2), link scheduler: in each time slot, access point can observe the buffering queue length of all transmission in subnet, by
It is found that buffering team leader's difference between access point and coupled user can be directly with the buffering queue length table of transmission
Show；So the buffering maximum transmission link of team leader transmits in access point meeting priority scheduling subnet, team leader is
Step 4: the distribution of dynamic access frequency spectrum is carried out to user；
Using the dynamic frequency spectrum deployment algorithm based on Frank-Wolfe, the distribution of the initial spectrum according to obtained in step 1
Solve Si, obtained in distributed rate control algolithm in step 3WithNew distribution is carried out to frequency spectrum, finally
So that the network utility optimization in combined optimization model is achieved；Utility function is substituted into combined optimization model, is obtained
Because the formula has proved to be NP-hardness problem, therefore to calculate the problem, approximate solution need to be carried out；This hair
It is bright first to complete channel distribution with the algorithm in step 2, then solved with the thought of Frank-Wolfe；It can be described as: choosing
Feasible initial point, i.e. initial channel allocation result p specify permissible error range ε, enable m=0；1. carrying out linear programming, i.e.,
Processing problem:Remember that the optimal solution being calculated is q(m), and remember d(m)=q(m)-p(m)；2. judgingDoes is it true? if true, output p(m), circulation terminates；Otherwise, by d(m)As feasible descent direction,
Effective linear search is carried out, linear search step-length is determined with this；Simultaneously for guarantee result in feasible zone, it is specified that step-length α ∈ [0,
1]；3. then handling problem:Optimal solution is obtained by calculation, is denoted as αm, enable p(m+1)=p(m)+αm*d(m), and make m=m+1, it repeats the above process.
The beneficial effects of the present invention are: both time delay and handling capacity have innovatively been carried out combined optimization by the present invention；Right
Both handling capacity and time delay carry out on the basis of rationally accepting or rejecting, and introduce effectiveness in the radio resource allocation of railway Internet of Things herein
Theory reduces system complexity, realizes the part optimization to the access control of railway Internet of Things；Specific utility function can be with
So that Resource Allocation Formula is guaranteed the fairness and stability of user, the service quality (QoS) of business can be improved.
Detailed description of the invention
Fig. 1 is railway Internet of Things access control system composition schematic diagram of the invention；
Fig. 2 is the utility function image being related to of the invention；
Fig. 3 is combined optimization connection control method flow chart of the invention；
Fig. 4 is the inter-user interference figure in the present embodiment.
Specific embodiment
It elaborates below to the embodiment of the present invention, the present embodiment carries out under the premise of the technical scheme of the present invention
Implement, the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to following implementation
Example.
Technical solution of the present invention includes:
Access control system on railway Internet of Things of the present invention is mainly made of three parts: controller, several
User, several wireless access points, wherein controller is monitored and controls to all wireless access points, and can regularly count
Calculate the interference between all wireless access points and user；The access point can have multiple wireless interfaces, but user only has one
A interface and only it is connected with an access point；Abstractively, indicate that the wireless interface collection of all access points, C indicate user with I
Collection, R indicate that effective transmission link collection between user and access point, N indicate the interference figure between the wireless interface of all access points, N
(i) other wireless interface set for indicating interference wireless interface i, remember i ∈ N (i).
The present invention uses the discrete time slots system that the time is divided into tiny time slot, while using first in, first out FIFO's
Message buffering way to manage；A ∈ I ∪ C, i.e. wireless access point and user all can serve as source node；B ∈ C, i.e. user are ok
As node；In network layer, a rate controller is placed, the rate for the message that network layer is entered from transport layer is carried out effective
Control；From source node a, the message transmitting spped rate that message is sent to destination node b is denoted asThe meeting at source node a
Maintenance flows to the message buffering queue of destination node bThe message access rate of the buffering queue isMoreover, it is assumed that
Transmission between all nodes is all independent identically distributed；There are following related constraint relationships between each rate:
Wherein, ωa,max(t) the maximum polymerization access rate that network can achieve at node a, μ are indicateda,max(t) section is indicated
The maximum polymerization transmission rate that network can achieve at point a.
In addition, providing as followsWithLong term time average value expression:
The queue dynamic of source node a to destination node b is updated, is indicated are as follows:
Wherein, []+It indicates when for positive number, directly uses, when for negative, use numerical value 0；Cl (i) is indicated
The user's collection being connected with wireless interface i；Second formula indicates to be cable network for purpose or be connected with other access points
User message, access point does not need to be cached；Third formula indicates not need at the destination nodes of all transmission pair
Association message is cached.
Present invention introduces virtual subnet queues, assess whereby the wireless interface load of access point；Virtual subnet Nets
Column are the variables that can reflect out sub-network load situation, and value is bigger, then illustrate that sub-network load is heavier, to need more
Frequency spectrum resource increase channel capacity, the final buffering queue length for reducing network, the congestion for alleviating subnet；
The dynamic of virtual subnet queue is updated, is indicated are as follows:
Vi(t+1)=[Vi(t)-μi(t)+ωi(t)]+
μi(t)≤Capai(t)
Wherein, Capai(t) channel capacity of wireless interface i, μ are indicatedi(t) use for indicating wireless interface i and being attached thereto
The aggregation transfer rate of Radio Link between family, ωi(t) the polymerization access rate of all nodes in corresponding subnet is indicated, finally
One formula means that the maximum aggregation transfer rate of all transmission in corresponding subnet is equal with the channel capacity of wireless interface i.
The utility function that the present invention uses logarithm to synthesize, general type areWherein ωiIt is elasticity
Coefficient, logarithmic form can reduce xiSize, to avoid the abnormal of great fluctuation process to occur to a certain extent, specifically, this hair
Utility function form used in bright are as follows:
Wherein,It is coefficient of elasticity,Indicate time averaging virtual subnet queue,It indicates based on son
The time average polymerization transmission rate of net, τ are balanceWithThe impact factor that the two distributes frequency spectrum.
The present invention selects network capacity region Π, by what can all be supported by network with ratio sharing modeSet
Composition, it can make throughput of system optimize on the basis of guaranteeing network stabilization；It avoids using traditional network capacity area
Domain is because the final result solved in this capacity region will lead to network stabilization and be destroyed, thus in actual use
Success rate it is extremely low.
Step 1: system access control combined optimization model is established；
The network utility function that setting uses has convex, non-subtract and characteristics, the combined optimization model such as continuous can be described as:
Wherein, first constraint condition may insure proportional fairness, and can make the average standard of the long term time of all nodes
Enter rate to be in the Π of network capacity region, second constraint condition show long term time be averaged access rate cannot be greater than it is long-term
Time is averaged transmission rate；Also need simultaneously it is clear, the frequency spectrum assignment constraints of access point wireless interface the size of Π；If used
Traditional network capacity region, final result will lead to network stabilization and be destroyed；So can be using network capacity region Π
Guarantee on the basis of network stabilization throughput of system to be optimized.
Step 2: the distribution of system initial spectrum is carried out；
The present invention uses the frequency spectrum allocation algorithm based on greediness coloring to acquire the initial solution that frequency spectrum distributes；First processing input
Data, data are constituted into non-directed graph, ascending order arrangement and number using the degree of each node；Simultaneously by color to be employed
It is numbered, arranges from small to large by number；It then, is each node-coloring according to rule；According to Node color each after coloring
Difference, classify to channel；Finally using consumed number of color is coloured, blank frequency spectrum is allocated, frequency spectrum is obtained
Distribution solution；It is wherein regular are as follows: node and color are all to be used from small to large according to number, and adjacent node color must not
Together.
Step 3: access control combined optimization is carried out；
Using the distributed rate control algolithm optimized based on Lyapunov, so that the stable constraint of combined optimization model
Met；Specific implementation is made of both the rate controller of meshed network layer and link scheduler of access point；The former can
To control the rate of the message flow in network layer by upper-layer protocol injection, and the buffering queue length of each transport stream determines in node
The rate；The latter is to carry out Radio Link scheduled transmission according to the buffering team leader difference between access point and coupled user,
So that the buffering queue entire length in subnet reaches minimum.
(1), rate controller: in each time slot, the access rate of all messages for being transmitted to b is controlled at node a
System, optimization problem are described as follows:
Wherein, it is balanced for the optimization that stresses to handling capacity and time delay, introduces γ balance parameters；Set utility function tool
Have it is convex, non-subtract and the characteristics such as continuous, so the optimal solution of this optimization problem can be obtained by directly carrying out first derivation；
(2), link scheduler: in each time slot, access point can observe the buffering queue length of all transmission in subnet, by
It is found that buffering team leader's difference between access point and coupled user can be directly with the buffering queue length table of transmission
Show；So the buffering maximum transmission link of team leader transmits in access point meeting priority scheduling subnet, team leader is
Step 4: the distribution of dynamic access frequency spectrum is carried out to user；
Using the dynamic frequency spectrum deployment algorithm based on Frank-Wolfe, the distribution of the initial spectrum according to obtained in step 1
Solve Si, obtained in distributed rate control algolithm in step 3WithNew distribution is carried out to frequency spectrum, is finally made
The network utility optimization obtained in combined optimization model is achieved.Utility function is substituted into combined optimization model, is obtained
Because the formula has proved to be NP-hardness problem, therefore to calculate the problem, approximate solution need to be carried out；This hair
It is bright first to complete channel distribution with the algorithm in step 2, then solved with the thought of Frank-Wolfe；It can be briefly described are as follows:
Feasible initial point is chosen, i.e. initial channel allocation result p specifies permissible error range ε, enables m=0；1., carry out linear gauge
It draws, i.e. processing problem:Remember that the optimal solution being calculated is q(m), and remember d(m)=q(m)-p(m)；2., judgementIt whether is true；If true, output p(m), circulation terminates；Otherwise, by d(m)As feasible descent direction,
Effective linear search is carried out, linear search step-length is determined with this；Simultaneously for guarantee result in feasible zone, it is specified that step-length α ∈ [0,
1]；3., then handle problem:Optimal solution is obtained by calculation, is denoted as αm, enable p(m+1)=p(m)+αm*
d(m), and make m=m+1, it repeats the above process.
The railway Internet of Things access control system composition provided in the present embodiment is assumed are as follows: controller 1, wireless access point
Totally 3,16 users；Interference relationships between 16 users, as shown in Figure 4；Remember that a frequency spectrum distribution solution is s={ < loweri
(t),upperi(t) > }i∈I, the channel bound that wherein wireless interface i is used at time t is upperi(t) and loweri
(t)；After introducing blank frequency spectrum, WH (f is rememberedlower,fupper, WS) and it is entire blank frequency spectrum, WS is frequency spectrum overall width, blank frequency
The bound of spectrum is fupperAnd flower；In emulation, the vector for taking 1 × n to tie up is plus white Gaussian noise, as blank frequency spectrum WH.
The present embodiment is realized by following steps:
Step 1: initial spectrum distribution is carried out:
The present embodiment uses the frequency spectrum allocation algorithm based on greediness coloring to acquire the initial solution that frequency spectrum distributes；First processing is defeated
Data are constituted non-directed graph by the data entered, and note number of nodes is n；The null matrix for taking 1 × n to tie up rises as color used in each node
Initial value CM；Color sum used is CON, and initial value is taken as 0；Then, ascending order arrangement is carried out based on degree, is as a result denoted as D；Traversal institute
There are node, i, j=1,2 ..., n；The color value for finding the adjoint point that is connected in data adjacency matrix W (i, j), selects minimum and not
Same color value, is assigned to CM (j)；If color is inadequate, CON=CON+1；All nodes are accordingly coloured according to CM.Most
Afterwards, blank frequency spectrum WH is fifty-fifty put into CON channel: pi=WS/CON, i=1,2 ..., CON obtains the channel in WH
Frequency spectrum distribution solution is at i
After carrying out network simulation, originally 1 to 16 user's rearrangement are as follows: D=
[41213141351116267891510]；Four user's classification can be then obtained, blue, green, yellow and black four kinds of color marks are successively used
Note；Node (user) 1,3,4,6,12,13,14,16 is blue；Node (user) 2,5,7,11 is green；Node (user) 8,
9,15 be yellow；Node (user) 10 is black；I.e. channel can original allocation be 4 parts；Accordingly, blank frequency spectrum original allocation solution
Are as follows: S=[4444]；Wherein, SiFor frequency spectrum distribution solution at channel i, i indicates the i-th column of above-mentioned S.
Step 2: access control combined optimization is carried out:
Using distributed rate control algolithm, so that the stable constraint of combined optimization model is met；Use network
Following rate can be obtained after emulation:
The aggregation transfer rate of Radio Link between wireless interface i and the user being attached thereto is as shown in table 1:
The aggregation transfer rate of table 1 wireless interface i and the Radio Link between the user that is connected:
The polymerization access rate of all nodes is as shown in table 2 in subnet:
The polymerization access rate of all nodes in 2 subnet of table:
Step 3: frequency spectrum is dynamically distributed.
The allocation algorithm used is based on Frank-Wolfe thought；It is obtained according to step 2WithTo frequency spectrum
Carry out new distribution；Utility function is brought intoIn, it can obtainBecause of the formula
NP-hardness problem is had proved to be, therefore to calculate the problem, approximate solution need to be carried out；The present invention first uses in step 1
Algorithm completes channel distribution, then is solved with the thought of Frank-Wolfe；The output number of colours CON in step 1 is taken first,
M=1, fk=1 are enabled, permissible error range ε=10- is specified5；It recycles following procedure and carries out linear programming, handle problem:Remember that the optimal solution being calculated is q(m), and remember d(m)=q(m)-p(m).Then, Rule of judgmentIt whether is true；If true, output p(m), circulation terminates；Otherwise, by d(m)As feasible descent direction,
Effective linear search is carried out, linear search step-length is determined with this；To guarantee result in feasible zone, it is specified that step-length α ∈ [0,1]；
Then problem is handled:Optimal solution is obtained by calculation, is denoted as αm, enable p(m+1)=p(m)+αm*d(m), and
M=m+1 is repeated the above process；Wherein, f:Rn→R1For differentiable function, p(m)Indicate the m times iteration point on p, ε is any
It small (for theoretically), can be set according to actual conditions, αmIt is p(m)Optimal step size；Differentiable function is in the present embodimentFactor τ=1 is set, selects pi=WS/CON, i=1,2 ..., CON as initial point；
Solution: S=(10 is dynamically distributed as follows using that can obtain after network simulation-3×)[0.15450.15450.15450.1545]。
The Optimized model that the present embodiment uses comprehensively considers time delay and handling capacity both sides relation, distributes frequency according to rate dynamic
Rate realizes the combined optimization of handling capacity and time delay.
Both time delay and handling capacity have innovatively been carried out combined optimization by the present invention.It is carried out to both handling capacity and time delay
On the basis of rationally accepting or rejecting, utility theory is introduced in the radio resource allocation of railway Internet of Things herein, reduces system complex
Degree realizes the part optimization to the access control of railway Internet of Things.Specific utility function can be such that Resource Allocation Formula guarantees
The service quality (QoS) of business can be improved in the fairness and stability of user.
Claims (4)
1. the access of service quality guarantee oriented controls combined optimization method in a kind of railway Internet of Things, it is characterised in that: pass through
It introduces utility function and chooses the network capacity region for guaranteeing network stabilization, on the basis for sufficiently and reasonably utilizing blank frequency spectrum
On, united analysis is carried out to both rate control and frequency spectrum distribution, by initial spectrum distribution, virtual subnet queue and transmission speed
Rate carries out dynamic frequency spectrum deployment, provides a kind of combined optimization model, reaches time delay in the access control of railway Internet of Things with this and gulps down
The combined optimization for the amount of spitting, to meet the needs of its service quality guarantee.
2. the access of service quality guarantee oriented controls combined optimization side in a kind of railway Internet of Things according to claim 1
Method, which is characterized in that the objective function of the combined optimization model is:
Wherein, I indicates that the wireless interface collection of all access points, C indicate that user's collection, WS indicate the overall width of blank frequency spectrum, CON table
Show the number that channel is classified after original allocation,Indicate time averaging virtual subnet queue,It indicates to be based on subnet
Time average polymerization transmission rate, τ indicate balanceWithThe impact factor that the two distributes frequency spectrum, SiIt indicates at channel i
Initial spectrum distribution solution, μi(t) the aggregation transfer rate of the Radio Link between wireless interface i and the user being attached thereto is indicated.
3. the access of service quality guarantee oriented controls combined optimization side in a kind of railway Internet of Things according to claim 1
Method, which is characterized in that its treatment process the following steps are included:
Step 1: carry out original allocation to frequency spectrum: data are constituted non-directed graph, remember node by the wherein data of first processing input
Number is n；Initial value CM of the null matrix for taking 1 × n to tie up as color used in each node；Color sum used is CON, and initial value takes
It is 0；Then, ascending order arrangement is carried out based on degree, is as a result denoted as D, traverse all nodes, i, j=1,2 ..., n finds data neighbour
The color value for connecing the adjoint point that is connected in matrix W (i, j), selects a smallest and different color value, is assigned to CM (j)；If color is not
Enough, then CON=CON+1, accordingly colours all nodes according to CM；Finally, fifty-fifty putting blank frequency spectrum WH into CON
In channel: pi=WS/CON, i=1,2 ..., CON, obtaining frequency spectrum distribution solution at the channel i in WH is
Step 2: distributed rate control algolithm is then used, so that the stable constraint of combined optimization model is met；It calculates
Method is made of both the rate controller of meshed network layer and the link scheduler of access point,
The rate controller respectively transmits in node to control the rate of the message flow in network layer by upper-layer protocol injection
The buffering queue length of stream determines the rate；The link scheduler is according to the buffering team between access point and coupled user
Long difference carries out Radio Link scheduled transmission, so that the buffering queue entire length in subnet reaches minimum；Then, according to
It is obtained aboveWithNew distribution is carried out to frequency spectrum；This is specific to substitute into
Optimized model after utility function need to carry out close because the formula has proved to be NP-hardness problem, therefore to calculate the problem
Like solution；The output number of colours CON for taking front first, enables m=1, fk=1, specifies permissible error range ε=10-5；Work as fk
When=1, carry out linear programming is recycled, i.e. processing problem:Remember that the optimal solution being calculated is q(m), and
Remember d(m)=q(m)-p(m)；Then, Rule of judgmentIt whether is true；If true, fk=0 is enabled, exports p(m),
Circulation terminates；Otherwise, by d(m)As feasible descent direction, effective linear search is carried out, linear search step-length is determined with this；For
Guarantee result in feasible zone, it is specified that step-length α ∈ [0,1]；Then it handles:Optimal solution is obtained, is denoted as
αm, enable p(m+1)=p(m)+αm*d(m), and m=m+1, it repeats the above process, wherein f:Rn→R1For differentiable function, p(m)It indicates in p
On the m times iteration point, ε be it is arbitrarily small, can be set according to actual conditions, αmIt is p(m)Optimal step size, if differentiable function isFactor τ=1 is set, p is selectedi=WS/CON, i=1,2 ..., CON is as initial point.
4. the access of service quality guarantee oriented controls combined optimization side in a kind of railway Internet of Things according to claim 1
Method, which is characterized in that in the railway Internet of Things described in the access control combined optimization method of service quality guarantee oriented
Utility function concrete form are as follows:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910669225.9A CN110381470B (en) | 2019-07-24 | 2019-07-24 | Access control joint optimization method facing service quality guarantee in railway Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910669225.9A CN110381470B (en) | 2019-07-24 | 2019-07-24 | Access control joint optimization method facing service quality guarantee in railway Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110381470A true CN110381470A (en) | 2019-10-25 |
| CN110381470B CN110381470B (en) | 2023-06-20 |
Family
ID=68255263
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910669225.9A Active CN110381470B (en) | 2019-07-24 | 2019-07-24 | Access control joint optimization method facing service quality guarantee in railway Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110381470B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111278033A (en) * | 2020-01-21 | 2020-06-12 | 北京工业大学 | Method for intelligent scanning and dynamic optimal configuration of transmission rate of LoRa communication network |
| CN112468449A (en) * | 2020-11-06 | 2021-03-09 | 中国电子科技集团公司电子科学研究院 | Resource optimization configuration algorithm for backtracking security controlled network access channel |
| CN114741191A (en) * | 2022-03-30 | 2022-07-12 | 西安电子科技大学 | Multi-resource allocation method for compute-intensive task relevance |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103621160A (en) * | 2011-04-08 | 2014-03-05 | 阿尔卡特朗讯公司 | QoS aware multi radio access point for operation in TV whitespaces |
| CN104581965A (en) * | 2015-01-08 | 2015-04-29 | 中国人民解放军理工大学 | Spectrum allocation method based on user allocation and time delay |
| CN108540246A (en) * | 2018-01-09 | 2018-09-14 | 重庆邮电大学 | A kind of resource allocation methods of the secondary IoT equipment of IoT sensor networks based on cognitive radio under imperfect channel |
| CN109005593A (en) * | 2018-08-03 | 2018-12-14 | 上海理工大学 | A kind of method and apparatus of the optimization for frequency spectrum distribution |
| CN109462426A (en) * | 2018-11-20 | 2019-03-12 | 南京邮电大学 | Beam forming and power distribution method towards high-iron carriage service quality guarantee |
| CN109640330A (en) * | 2019-01-29 | 2019-04-16 | 电子科技大学 | Spectrum management system, blank frequency spectrum cognitive method and blank frequency spectrum distribution method |
-
2019
- 2019-07-24 CN CN201910669225.9A patent/CN110381470B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103621160A (en) * | 2011-04-08 | 2014-03-05 | 阿尔卡特朗讯公司 | QoS aware multi radio access point for operation in TV whitespaces |
| CN104581965A (en) * | 2015-01-08 | 2015-04-29 | 中国人民解放军理工大学 | Spectrum allocation method based on user allocation and time delay |
| CN108540246A (en) * | 2018-01-09 | 2018-09-14 | 重庆邮电大学 | A kind of resource allocation methods of the secondary IoT equipment of IoT sensor networks based on cognitive radio under imperfect channel |
| CN109005593A (en) * | 2018-08-03 | 2018-12-14 | 上海理工大学 | A kind of method and apparatus of the optimization for frequency spectrum distribution |
| CN109462426A (en) * | 2018-11-20 | 2019-03-12 | 南京邮电大学 | Beam forming and power distribution method towards high-iron carriage service quality guarantee |
| CN109640330A (en) * | 2019-01-29 | 2019-04-16 | 电子科技大学 | Spectrum management system, blank frequency spectrum cognitive method and blank frequency spectrum distribution method |
Non-Patent Citations (4)
| Title |
|---|
| HUAWEI TONG等: "An Enhanced Volleyball Premier League Algorithm with Chaotic Maps", 《2020 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI)》 * |
| HUI TIAN等: "Energy-efficient user association in heterogeneous networks with M2M/H2H coexistence under QoS guarantees", 《CHINA COMMUNICATIONS》 * |
| 童华炜: "基于群体智能的物联网任务调度方法研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 黎宝华: "物联网环境下基于演化博弈的动态频谱分配算法", 《物联网技术》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111278033A (en) * | 2020-01-21 | 2020-06-12 | 北京工业大学 | Method for intelligent scanning and dynamic optimal configuration of transmission rate of LoRa communication network |
| CN111278033B (en) * | 2020-01-21 | 2022-10-18 | 北京工业大学 | Method for intelligent scanning and dynamic optimal configuration of transmission rate of LoRa communication network |
| CN112468449A (en) * | 2020-11-06 | 2021-03-09 | 中国电子科技集团公司电子科学研究院 | Resource optimization configuration algorithm for backtracking security controlled network access channel |
| CN112468449B (en) * | 2020-11-06 | 2022-11-01 | 中国电子科技集团公司电子科学研究院 | Method for optimizing and configuring backtracking security controlled network access channel resources |
| CN114741191A (en) * | 2022-03-30 | 2022-07-12 | 西安电子科技大学 | Multi-resource allocation method for compute-intensive task relevance |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110381470B (en) | 2023-06-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110381470A (en) | The access of service quality guarantee oriented controls combined optimization method in a kind of railway Internet of Things | |
| Sun et al. | Autonomous resource slicing for virtualized vehicular networks with D2D communications based on deep reinforcement learning | |
| Qian et al. | Leveraging dynamic stackelberg pricing game for multi-mode spectrum sharing in 5G-VANET | |
| CN107682135A (en) | A kind of network slice adaptive virtual resource allocation method based on NOMA | |
| CN106105117A (en) | Traffic engineering controller in delamination software definition network | |
| CN102098684B (en) | System and method for allocating cross-layer resources in cognitive radio network | |
| CN106454920B (en) | Resource allocation optimization algorithm based on Delay Guarantee in a kind of LTE and D2D hybrid network | |
| Zhang et al. | Federated deep reinforcement learning for resource allocation in O-RAN slicing | |
| CN103067985B (en) | The binding of ultrahigh speed wireless lan channel and distribution method based on channel quality | |
| CN103179633B (en) | The cognitive radio network routing method that a kind of combined channel distributes | |
| CN107846714A (en) | The switching method and equipment of a kind of visible light communication and WiFi heterogeneous systems | |
| CN106954232A (en) | A kind of resource allocation methods of time delay optimization | |
| CN103596224B (en) | Resource regulating method based on multistage-mapping under a kind of high-speed mobile environment | |
| Wang et al. | Energy-delay minimization of task migration based on game theory in MEC-assisted vehicular networks | |
| CN106793133A (en) | The dispatching method of multi-service QoS is ensured in a kind of electric power wireless communication system | |
| CN103841044A (en) | Bandwidth control method based on software-defined networking and oriented to different types of flow | |
| CN103607737B (en) | A kind of heterogeneous-network service shunt method and system | |
| CN107248896B (en) | A kind of D2D communication united mode selection and Proportional Fair optimization method | |
| CN106993298A (en) | A kind of intelligent electric power communication service difference dispatching method based on QoS | |
| CN106171025A (en) | A kind of car networking transport resource regulating method and device | |
| CN109451462A (en) | A kind of In-vehicle networking frequency spectrum resource allocation method based on semi-Markov chain | |
| CN105992252A (en) | Processing method and apparatus for context of UE | |
| CN103327542B (en) | A kind of QoS support method and device that is applied to MANET network | |
| CN108093485A (en) | A kind of resource allocation methods and device | |
| CN102665219B (en) | Dynamic frequency spectrum allocation method of home base station system based on OFDMA |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: Room 201, building 2, phase II, No.1 Kechuang Road, Yaohua street, Qixia District, Nanjing City, Jiangsu Province Applicant after: NANJING University OF POSTS AND TELECOMMUNICATIONS Address before: 210012 No. 19 Ningshuang Road, Yuhuatai District, Nanjing City, Jiangsu Province Applicant before: NANJING University OF POSTS AND TELECOMMUNICATIONS |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |