A Dynamic Priority Emergency Communication Resource Allocation Method

Abstract

The present invention discloses a method for dynamically prioritized emergency communication resource allocation, which includes constructing an emergency communication index based on the priority of emergency communication services and the service queuing delay, calculating the service effective resource allocation weight coefficient, and allocating the network effective resources based on this allocation weight coefficient. This allocation method includes the following steps: S1. At the emergency communication network access point, based on the constructed emergency communication index function, calculate the service emergency index value according to the priority of emergency communication services and the service queuing delay parameters, and further calculate the value of the dynamic service-related effective resource allocation weight coefficient. The method of the present invention utilizes the computing power of the network access point, and provides fair communication opportunities for different types of services in large-scale disaster scenarios by dynamically adjusting the effective resource threshold values of different priority services, so as to improve the emergency rescue efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of emergency communication, and particularly to a method for dynamically prioritized emergency communication resource allocation. Background Art

[0002] An emergency communication network is a communication network that is temporarily formed by quickly deploying infrastructure, providing information transmission for communication terminals in disaster scenarios, and establishing a temporary information exchange bridge between rescuers and the rescued. Through the emergency communication network, the rescued can send information about themselves and the environmental status of the trapped location, providing a decision-making reference for rescuers to implement the rescue. The large-scale popularization of mobile communication has facilitated the use of mobile terminals to request rescue in disaster scenarios.

[0003] In the emergency communication network, there are communication resource allocation methods with different optimization objectives, such as communication resource allocation methods based on multi-parameter joint optimization, absolute priority communication resource allocation methods, and communication resource allocation methods based on prediction models, etc., to improve the fairness of resource allocation, or improve system throughput, or improve resource efficiency. The method based on multi-parameter joint optimization mainly considers beam interference and channel delay characteristics to improve bandwidth utilization and access fairness, but does not consider the difference in the urgency of service communication. The absolute priority method can ensure the communication performance of services with high urgency, but it is easy to cause non-emergency rescue services to be unable to communicate normally in dense communication scenarios. The method based on the prediction model realizes the optimal from multiple aspects of communication interference, power allocation, and system throughput by establishing a service prediction function model through intelligent learning of service characteristics and channel state data, but it requires the network to provide more additional resources for transmitting channel state information, which is not suitable for dense emergency communication scenarios with scarce resources. With the development of the performance of information processing chips, the computing power of communication network nodes has been rapidly improved. Therefore, utilize the computing power of emergency communication network access points to coordinate the transmission performance and fairness of emergency communication services, implement a refined emergency communication plan, and improve the emergency rescue efficiency in major disaster scenarios.

[0004] Currently, in the mobile cellular communication network, mobile terminal communication services mainly include three types: voice services, video streams, and data services. Voice services belong to delay-sensitive services, requiring communication within a limited end-to-end delay. When multiple services request communication simultaneously, delay-sensitive services should be transmitted first, and they have the highest priority. Video streams belong to real-time reliable services, which have requirements for communication delay but allow a certain amount of delay. Therefore, their priority is second only to delay-sensitive services. Data services are elastic service flows that can tolerate a large range of delays but have high requirements for the reliability of service packet transmission, and their communication urgency can be set to the lowest level. The priority classification of multi-services in mobile terminal emergency communication is as Figure 3 shown, which describes the basic characteristics, performance parameters, and priorities of different types of services.

[0005] Deficiencies of the prior art:

[0006] In large-scale disaster scenarios, the rescue request services of mobile terminals form intensive communications within a limited area, making it difficult for the resource-constrained temporary emergency communication network to meet all sudden service demands. It is necessary to achieve differentiated communication transmissions according to the urgency of rescue services to improve rescue efficiency and the utilization rate of emergency communication resources. Summary of the Invention

[0007] The purpose of the present invention is to provide a method for dynamically prioritized emergency communication resource allocation to solve the problems raised in the above background technology.

[0008] A method for dynamically prioritized emergency communication resource allocation includes constructing an emergency communication index based on the priority of emergency communication services and the service queuing delay to calculate the effective resource allocation weight coefficient for services. Subsequently, the network effective resources are allocated based on this allocation weight coefficient. This allocation method includes the following steps:

[0009] S1. At the emergency communication network access point, based on the constructed emergency communication index function, calculate the service emergency index value according to the priority of emergency communication services and the service queuing delay parameters, and further calculate the dynamic effective resource allocation weight coefficient value associated with the service.

[0010] S2. The emergency communication network access point sets an effective resource threshold for different types of services according to the effective resource allocation weight coefficient. Subsequently, the available resources for the service take the minimum value between the effective resource threshold for this type of service and the requested resources.

[0011] As a further improvement of the present invention, in step S1 of this method, the emergency communication index function is constructed by selecting the priority parameter of emergency communication services and the urgency parameter of service transmission. The calculation formula for the emergency communication index function is:

[0012] where q represents the service priority and T represents the urgency of service transmission.

[0013] As a further improvement of the present invention, the calculation formula for the urgency parameter T in this method is:

[0014]

[0015] where T out is the boundary of the service packet queuing delay. If it exceeds this boundary value, the service packet is discarded;

[0016] t is the queuing time for the service packet waiting to be transmitted.

[0017] As a further improvement of the present invention, in this method, the emergency communication exponential function describes the relationship between service priority and transmission urgency, and the formula for the service effective resource allocation weight coefficient is:

[0018] As a further improvement of the present invention, in step S2 of this method, when the effective resources of the emergency communication network cannot meet all service communication requests, the network sets an effective resource threshold proportional to the emergency communication index for different types of services, that is, the maximum effective resource allocated to the service is: BW max = BW·ω

[0019] where BW is the total effective resources of the network.

[0020] As a further improvement of the present invention, in this method, when an emergency communication service requests communication, the available resources obtained are the minimum of the requested resources and the maximum effective resources of the service, that is, the available resources allocated by the network to the service are: BW u = min{BW req , BW max}

[0021] where BW req is the service communication request resources with quality of service guarantee.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] The present invention comprehensively considers service priority and service queuing delay factors, calculates the effective resource thresholds obtained by different types of services, and dynamically allocates the available resources for service communication accordingly, providing fair access network opportunities for multi-service intensive communication in large-scale disaster scenarios, and ensuring that all rescued persons receive effective rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flowchart of a method for dynamically prioritized emergency communication resource allocation according to the present invention;

[0025] Figure 2 is a multi-service intensive communication scenario in emergency communication of a method for dynamically prioritized emergency communication resource allocation according to the present invention;

[0026] Figure 3 is a multi-service priority classification table for emergency communication of a method for dynamically prioritized emergency communication resource allocation according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment

[0029] Please refer to Figures 1-3 , the present invention provides the following technical solution: A method for dynamically prioritized emergency communication resource allocation. In an emergency communication network temporarily formed in a large-scale disaster scenario, the network access point calculates the emergency communication index values and effective resource allocation weight coefficients for different types of services. When the effective resources of the emergency communication network cannot meet the communication transmission of all services simultaneously, the emergency communication services need to compete for access to the network. The network access point allocates available resources to different types of services based on the resource allocation weight coefficients, specifically including a pre-calculation stage and a dynamic resource allocation stage, and the process is as follows:

[0030] In the pre-calculation stage, the emergency communication index value is calculated according to the emergency communication index function constructed based on the emergency communication service priority and the real-time queuing delay parameter, and further the dynamic service effective resource allocation weight coefficient is calculated. Specifically:

[0031] Let q i = {q1, q2, q3}, and i = 1, 2, 3 are the priority parameters of three service types: data service, video stream, and voice service respectively;

[0032] That is, the data service priority is set as q1, the video service priority is set as q2, the voice service priority is set as q3, and q3 > q2 > q1;

[0033] Let the transmission urgency parameter of the three service groups be Among them, T outi is the queuing delay boundary of the i-th type of service packet, and t i is the queuing time of the i-th type of service packet waiting for transmission in the network access point;

[0034] In summary, the emergency communication index value of the i-th type of service is

[0035] Therefore, the maximum available effective resource allocation weight coefficient of the i-th type of service is

[0036] In the dynamic resource allocation stage, an effective resource threshold is set for each type of service according to the resource allocation weight coefficients obtained by different types of services. When the service obtains the transmission opportunity, the actual available resources are allocated to this type of service. Specifically:

[0037] Based on the weight coefficient of effective resource allocation for services, the network access point calculates the effective resource threshold for the i-th type of service as

[0038] BW i max = BW·ω i (1)

[0039] where BW i max is the effective resource threshold for the i-th type of service;

[0040] When multiple types of services compete for network access, the network access point calculates the effective resource threshold for the high-priority service as BW3 according to formula (1) max , then the available resource BW3 u allocated to this type of service is

[0041] BW3 u = min(BW3 req , BW3 max ) (2)

[0042] where BW3 req is the service request resource to ensure the transmission quality of high-priority services. The network access point calculates the remaining effective resources of the network, that is, BW2 R = BW - BW3 u .

[0043] Subsequently, the network access point allocates available resources to medium-priority services. The effective resource threshold for this type of service calculated by formula (1) is BW2 max , then the available resource BW2 u allocated to this type of service is

[0044] BW2 u = min(BW2 req , BW2 max ) (3)

[0045] where BW2 req is the service request resource to ensure the transmission quality of medium-priority services. The network access point calculates the remaining effective resources of the network, that is, BW1 R = BW - BW3 u - BW2 u .

[0046] Finally, the network access point allocates available resources to low-priority services, then the available resource BW1 u allocated to this type of service is

[0047] BW1 u = min(BW3 req , BW1R ) (4)

[0048] When the remaining available resource BW1 R cannot meet the communication requirements of low-priority services, the low-priority services will not be transmitted temporarily in this cycle.

[0049] In this embodiment, according to service availability, the queuing delay boundary for data services is set to T out1 = 2000ms, the queuing delay boundary for video streams is T out2 = 450ms, and the queuing delay boundary for voice services is T out3 = 300ms. Then, the transmission urgency parameter for data service packets is The transmission urgency parameter for video stream packets is The transmission urgency parameter for voice service packets is where t1, t2, and t3 are the transmission queuing delays of the corresponding service packets respectively;

[0050] Let the priority parameters of the three service types of data services, video streams, and voice services be q = {1, 2, 3}, that is, q1 = 1, q2 = 2, and q3 = 3. If the queuing delays of the three service packets in a certain time period are set to t1 = 400ms, t2 = 50ms, and t3 = 0ms respectively, then the emergency communication index value of the data service is The emergency communication index value of the video stream is The emergency communication index value of the voice service is Therefore, the effective resource allocation weight coefficients that can be occupied by the three services are calculated to be ω1 ≈ 0.084, ω2 ≈ 0.335, and ω3 ≈ 0.581 respectively.

[0051] Suppose there are 4000 communication terminals in a certain emergency scenario, and the effective bandwidth resource of the emergency communication system is BW = 10MHz, which can simultaneously transmit three types of service applications of data, video streams, and voice. Among them, the requested bandwidth of a single data service is 10kHz, the requested bandwidth resource of the video stream service is 300kHz, and the requested bandwidth resource of the voice service is 13kHz;

[0052] In this embodiment, the effective resource threshold for the first type of data service is BW1 max = BW·ω1 = 840kHz, the effective resource threshold for the second type of video stream service is BW2 max = BW·ω2 = 3350kHz, and the effective resource threshold for the third type of voice service is BW3 max = BW·ω3 = 5810kHz;

[0053] If the number of terminals that need to conduct voice services simultaneously in the communication terminal is set to 200, the number of terminals for video services is 30, and the number of terminals for data services is 2000, then the network access point of the emergency communication system first allocates available bandwidth resources for voice services as BW3 u = min(BW3 req , BW3 max ) = min(2600, 5810) = 2600 kHz. The network can provide communication transmission for the voice services requested by all 200 terminals, and calculate the remaining effective resources of the network, that is, BW2 R = BW - BW3 u = 7400 kHz;

[0054] Subsequently, allocate available bandwidth resources BW2 for video stream services u = min(BW2 req , BW2 max ) = min(9000, 3350) = 3350 kHz. The network can provide communication transmission for the video services requested by 11 terminals, and calculate the remaining effective resources of the network, that is, BW1 R = BW - BW3 u - BW2 u = 4050 kHz. At this time, the remaining network bandwidth resources can provide communication transmission for the data applications of 405 terminals.

[0055] This implementation case only describes a process of implementing the allocation of communication resources. Due to the dynamic changes in the number of terminals requesting communication for different types of services and the queuing delay of the communication service packets, therefore, the network access point of the emergency communication system needs to calculate the allocation weight coefficient of communication resources according to the changes in the network state, and accordingly allocate available bandwidth resources for different types of services.

[0056] In summary, the method of the present invention constructs a service emergency communication index to calculate the effective resource allocation weight coefficient. The network access point allocates available resources for different types of services based on this allocation weight coefficient, providing a convenient implementation solution for the resource collaborative communication of multi-service emergency communication.

[0057] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusively, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0058] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art will appreciate that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic priority-based emergency communication resource allocation method, which includes constructing an emergency communication index according to the emergency communication service priority and service queuing delay to calculate the service effective resource allocation weight coefficient, and then allocating the network effective resources based on this allocation weight coefficient, and is characterized in that: The present allocation method includes the following steps: S1. At the emergency communication network access point, based on the constructed emergency communication exponential function, calculate the service emergency index value according to the emergency communication service priority and the service queuing delay parameter, and calculate the dynamic effective resource allocation weight coefficient value associated with the service; S2. The emergency communication network access point sets an effective resource threshold for different types of services according to the effective resource allocation weight coefficient, and then the available resource for the service takes the minimum value between the effective resource threshold of this type of service and the requested resource; In step S1 of the present method, the emergency communication exponential function is constructed by selecting the emergency communication service priority parameter and the urgency parameter of service transmission. The calculation formula of the emergency communication exponential function is as follows: where q represents the service priority and T represents the transmission urgency of the service; The calculation formula for the transmission urgency parameter T in this method is: Among them, T out is the queuing delay boundary for service grouping. If the boundary value is exceeded, the service grouping will be discarded; t is the queuing time for the service packet to wait for transmission; In this method, the emergency communication exponential function describes the relationship between service priority and transmission urgency. The formula for the service effective resource allocation weight coefficient is as follows: In step S2 of the present method, when the effective resources of the emergency communication network cannot meet all service communication requests, the network sets an effective resource threshold proportional to the emergency communication index for different types of services, that is, the maximum effective resources allocated for the service are: BW max = BW·ω where BW is the total effective resource of the network; In this method, when an emergency communication service requests communication, the available resource obtained is the minimum value between the requested resource of the service and the maximum effective resource, that is, the available resource allocated by the network to the service is: BW u = min{BW req , BW max} Among them, BW req is a service communication request resource with quality of service guarantee.

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