An emergency data aggregation method, system, device and storage medium

Abstract

The application belongs to the field of data transmission, and particularly relates to an emergency data aggregation method, system, device and storage medium. The method comprises the following steps: dividing emergency aggregation data into multiple parts, respectively storing the multiple parts in multiple mobile terminals, using distributed decision to obtain a plurality of transmission decisions of each terminal at time t through the multiple mobile terminals, pruning the plurality of transmission decisions to obtain screened transmission decisions, calculating transmission energy consumption and transmission utility of each screened transmission decision, combining constraint conditions to obtain Lyapunov drift reduction penalty, finding a transmission decision satisfying the constraint conditions of the Lyapunov drift reduction penalty as a final transmission decision, and transmitting the emergency aggregation data according to the final transmission decision. When data transmission is performed in a harsh environment, the transmission utility of the system is improved under the condition of limited energy.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of data transmission, and particularly relates to an emergency data aggregation method, system, device and storage medium. BACKGROUND

[0002] With the continuous development of mobile computing related technologies, the functions and performance of mobile intelligent devices are continuously improved, and are widely applied to emergency management in harsh environments. However, due to the suddenness and uncertainty of emergency events, and often accompanied by harsh environments such as resource constraints, network dynamics and hostile environments, the traditional single data terminal often cannot meet the demand of quickly and comprehensively obtaining information on site. Therefore, the concept of opportunistic edge computing is proposed, which builds adjacent peer nodes into a cooperative group to cope with the influence of harsh environments in the way of sharing computing resources, storage resources and communication resources.

[0003] In the related art, when the cooperative group sends data, the data is sent in order according to the received data, and different terminals transmit part of the data, and all the received data is transmitted.

[0004] In view of the above related technologies, when transmitting data in a harsh environment, due to the limitation of terminals and the instability of the network, and the energy consumption required by different terminals when transmitting different data is different, the sequential transmission cannot maximize the energy of each terminal to transmit as much data as possible, and cannot prioritize the transmission of important data. SUMMARY

[0005] The technical problem to be solved by the present application is to provide an emergency data aggregation method, system, device and storage medium, which introduces user data preference weight under the condition of limited energy and network, so as to prioritize important user demand while improving overall data transmission efficiency.

[0006] An emergency data aggregation method, comprising:

[0007] Obtaining a single aggregation emergency data quantity of single aggregation, dividing each emergency aggregation data into a plurality of data segments of the same size, redundantly copying the data segments into multiple copies, and storing them in multiple terminals to obtain data segments stored in each terminal;

[0008] According to the channel state of each terminal at time t and the data demand preference of each data segment, a joint decision factor is established, and a decision function is obtained according to the joint decision factor;

[0009] Obtaining a monotonic threshold set;

[0010] According to the decision function and the monotonic threshold set, a plurality of transmission decisions are obtained, the transmission decision being whether each terminal transmits a data segment at time t;

[0011] setting constraints for all terminals in the aggregation process, the constraints including maximizing transmission utility and minimizing transmission energy consumption;

[0012] based on the transmission decision, obtaining transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, and transmission utility and transmission energy consumption of other terminals before time t-D;

[0013] According to the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, and the transmission utility and transmission energy consumption of other terminals before time t-D, and the constraints, obtaining Lyapunov drift minus penalty of all terminals;

[0014] traversing the monotone threshold set, selecting a transmission decision that satisfies the constraints of the Lyapunov drift minus penalty as the final transmission decision;

[0015] According to the final transmission decision, the emergency aggregation data is aggregated.

[0016] The emergency data is personnel position data and available resource data in the organization of rescue in the earthquake debris flow in the deep mountains.

[0017] Optionally, the emergency aggregation data includes personnel position data and available resource data.

[0018] Optionally, calculating the transmission utility includes:

[0019] obtaining the preference coefficient of each data segment transmitted at time t and the amount of effective data segments;

[0020] According to the preference coefficient and the amount of effective data segments, the transmission utility is calculated.

[0021] Optionally, it is characterized in that,

[0022] The decision function is:

[0023]

[0024] where Y is the channel state-data preference balance parameter of the cooperative group, β r (t) is the preference coefficient of data r at time t, s rij (t) indicates that the jth data segment of the rth data at time t is stored on terminal i, R is the number of data to be transmitted in a aggregation process, c i (t) is the channel state of mobile terminal i at time t, s(t) is the storage of R data in the cooperative group at time t, and β(t) is the data preference coefficient.

[0025] The decision function is:

[0026]

[0027] wherein, is a decision value, is a monotonic threshold.

[0028] Optionally, obtaining a plurality of transmission decisions according to the decision function and the set of monotonic thresholds comprises:

[0029] obtaining a to-be-determined threshold according to the set of monotonic thresholds;

[0030] obtaining a decision value according to a channel state of the current terminal at time t, a data requirement preference of the data segment, and the decision function;

[0031] judging whether the decision value is greater than the to-be-determined threshold;

[0032] if the decision value is greater than or equal to the to-be-determined threshold, then transmitting data by the current terminal at time t as the transmission decision;

[0033] if the decision value is less than the to-be-determined threshold, then not transmitting data by the current terminal at time t as the transmission decision;

[0034] iterating the set of monotonic thresholds to obtain a plurality of transmission decisions of the current terminal under different monotonic thresholds.

[0035] Optionally, obtaining a Lyapunov drift minus penalty of all terminals according to a transmission utility, a transmission energy consumption of the current terminal when transmitting the data segment at time t, a transmission utility, a transmission energy consumption of other terminals before time t-D, and a constraint condition comprises:

[0036] obtaining a device channel state and a decision feedback of the other terminals at time t-D;

[0037] obtaining an energy consumption before time t-D according to the device channel state and the decision feedback at time t-D;

[0038] establishing a virtual queue according to the transmission energy consumption, the energy consumption before time t-D, and an initial queue value, and obtaining a Lyapunov function according to the virtual queue;

[0039] obtaining the Lyapunov drift minus penalty according to the virtual queue, the Lyapunov function, and the constraint condition.

[0040] Optionally, iterating the set of monotonic thresholds to select a transmission decision satisfying the constraint condition as a final transmission decision according to the Lyapunov drift minus penalty comprises:

[0041] traversing the monotone threshold set to obtain the Lyapunov drift minus penalty of different transmission decisions, and calculating an upper bound of the Lyapunov drift minus penalty as an optimization objective function;

[0042] obtaining a transmission decision corresponding to the minimum optimization objective function as a final transmission decision.

[0043] An emergency data aggregation system comprises:

[0044] An obtaining module is configured to obtain a single-aggregation emergency data quantity of single aggregation, divide each piece of emergency aggregation data into a plurality of data segments of the same size, redundantly copy the data segments into multiple copies, and store the data segments in a plurality of mobile terminals to obtain data segments stored in each terminal;

[0045] A decision module is configured to establish a joint decision factor according to a channel state of each terminal at time t and a data demand preference of each data segment, and obtain a decision function according to the joint decision factor;

[0046] An obtaining module is configured to obtain a monotone threshold set;

[0047] A setting module is configured to set a constraint condition of all terminals in an aggregation process, and the constraint condition comprises maximizing transmission utility and minimizing transmission energy consumption;

[0048] A calculation module is configured to obtain transmission utility and transmission energy consumption of a current terminal when transmitting a data segment at time t, and transmission utility and transmission energy consumption of other terminals before time t-D, based on the transmission decision;

[0049] A constraint module is configured to obtain a Lyapunov drift minus penalty of all terminals according to the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, the transmission utility and transmission energy consumption of the other terminals before time t-D, and the constraint condition;

[0050] A traversal module is configured to traverse the monotone threshold set, and select a transmission decision satisfying the constraint condition of the Lyapunov drift minus penalty as a final transmission decision;

[0051] An aggregation module is configured to aggregate emergency aggregation data according to the final transmission decision.

[0052] A terminal device comprises a memory and a processor, the memory stores a computer program capable of running on the processor, and the processor loads and executes the computer program to adopt an emergency data aggregation method.

[0053] A computer readable storage medium stores a computer program, and the computer program is loaded and executed by a processor to adopt an emergency data aggregation method.

[0054] The beneficial effects of the present invention are:

[0055] 1. By dividing the emergency aggregate data into multiple parts and storing them on multiple mobile terminals, the data transmission is distributed through the multiple mobile terminals to obtain several transmission decisions for each terminal at time t. These transmission decisions are then pruned to obtain a filtered transmission decision. The transmission energy consumption and transmission utility of each filtered transmission decision are calculated. Combined with the constraints, the Lyapunov drift minus penalty is obtained. The final transmission decision whose Lyapunov drift minus penalty satisfies the constraints is found and used to transmit the emergency aggregate data. This improves the transmission utility of the system when transmitting data in harsh environments with limited energy.

[0056] 2. In order to prevent the terminal from consuming too much energy to transmit all the data, a preference coefficient for the data segment is set. The transmission decision is made based on the preference coefficient and the channel status, so that more important data can be transmitted first during transmission to avoid the situation where important data cannot be transmitted due to insufficient energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 The figure is a flow chart of an emergency data aggregation method of the present invention. DETAILED DESCRIPTION

[0058] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0059] An emergency data aggregation method, such as Figure 1 As shown, including:

[0060] S100. Obtain the number of emergency data aggregated in a single time, divide each emergency aggregated data into several data segments of the same size, redundantly copy the data segment into multiple copies, and store them in multiple terminals to obtain the data segment stored in each terminal.

[0061] Specifically, the collaborative group consists of N The terminal consists of T terminals, and a total of T data aggregation processes are performed. Each aggregation process requires R data to be transmitted. Use the vector β(t) = (β1(t),...,β r (t).,..,β R (t)) represents the data preference coefficient of data transmission at time t. To enhance data storage capacity and improve its reliability, each data is divided into P data segments of the same size and redundantly replicated into multiple copies for distributed storage among multiple mobile terminals. ri (t)=(s ri1 (t),...,s riP (t)) represents the data segment storage status of the rth data on terminal i at time t, srip (t) = 1 means that the copy of the pth data segment of data r at time t is stored in mobile terminal i, otherwise s rip (t) = 0. The vector s r (t) = (s r1 (t),...,s rN (t)) represents the terminal storage status of data r at time t, and s(t) = (s1(t),...,s R (t)) represents the total storage status of all data at time t.

[0062] The emergency aggregation data includes personnel location data and available resource data. For example, when rescuing in a mountain earthquake mudslide, the information of trapped personnel obtained by a UAV terminal mobile group is acquired by shooting. Due to poor signal in the mountain, the network environment is particularly complex and dynamic, and is also affected by the power of the UAV, so it is not possible to immediately upload all data to the edge server in real time. The emergency aggregation data is the location data of trapped personnel and some property data of the personnel obtained by the UAV.

[0063] Since the energy of each terminal is limited in the mountain, and the network is limited, only under limited resources, more important data can be transmitted as much as possible and preferentially.

[0064] S110, according to the channel state of each terminal at time t and the data demand preference of each data segment, a joint decision factor is established, and a decision function is obtained according to the joint decision factor.

[0065] Specifically, the distributed decision is that each terminal decides at time t whether to transmit the data segment.

[0066] Specifically, since the channel state and data demand preference need to be considered simultaneously in the data aggregation process, a joint decision factor g(t) = (g1(t),...,g N (t)) is defined, where g i (t) is:

[0067]

[0068] Where Y is the channel state-data preference balance parameter of the cooperative group, β r (t) is the preference coefficient of data r at time t, s rij (t) represents the storage of the jth data segment of the rth data on terminal i at time t, R is the number of data to be transmitted in one aggregation process, c i (t) is t the channel state of the mobile terminal ichannel state, s(t) is t moment R the storage condition of the data in the coordination group, β(t) is the data preference coefficient.

[0069] where Y≥0, represents the trade-off parameter between the channel state and the maximum preference coefficient. Define as the decision function of mobile terminal i, whether terminal i transmits will be determined by the joint decision factor. The decision of N terminals is represented by vector . In order to maximize the effective data transmission of the most urgent data, the maximum preference data decision term stored by the terminal is introduced into the joint decision factor , so that the mobile terminal can make decision and judgment according to the channel state (c i (t)) and data preference at the same time. When Y=0, the mobile terminal completely relies on the channel state decision. With the increase of Y value, the terminal will make more transmission decisions according to the maximum preference of the stored data.

[0070] Specifically, since each mobile terminal has d i (t)∈{0,1} two decision choices. And each decision factor g i will be affected by γ kinds of channel states and R kinds of different preference data, and the possible value of the decision factor is |g i | = Rγ. Therefore, the total number of possible decisions is . For m∈{1,...,M} represents the specified distributed strategy in M possible strategies.

[0071] S120, obtain a set of monotonic thresholds.

[0072] Specifically, since the data amount and the number of channel states are discrete, the number of monotonic thresholds is also limited, and all the monotonic thresholds form a set of monotonic thresholds.

[0073] S130, according to the decision function and the set of monotonic thresholds, obtain a plurality of transmission decisions, the transmission decision is whether each terminal transmits a data segment at t moment.

[0074] According to the decision function and the set of monotonic thresholds, a plurality of transmission decisions are obtained, including:

[0075] S1300, according to the set of monotonic thresholds, obtain a to-be-determined threshold.

[0076] S1310, according to the channel state of the current terminal at t moment, the data demand preference of the data segment and the decision function, obtain a decision value.

[0077] S1320, judge whether the decision value is greater than the to-be-determined threshold.

[0078] S1330: If the decision value is greater than or equal to the threshold to be determined, the current terminal transmits data at time t as the transmission decision.

[0079] S1340: If the decision value is less than the threshold to be determined, the current terminal does not transmit data at time t as the transmission decision.

[0080] S1350 , traverse the monotonic threshold set to obtain several transmission decisions of the current terminal under different monotonic thresholds.

[0081] Specifically, for a terminal, if the monotonic threshold is determined, then the transmission decision is determined for the terminal. If the value is greater than the monotonic threshold, data is transmitted; otherwise, data is not transmitted.

[0082] The threshold to be determined is one of the monotonic thresholds in the monotonic threshold set. When traversing, the monotonic thresholds in the monotonic threshold set can be sorted from small to large, and then traversed one by one to obtain several transmission decisions of the current terminal under different monotonic thresholds.

[0083] The current terminal is any terminal among all terminals.

[0084] For the optimization problem of maximizing system utility under given energy consumption constraints, for all i∈{1,...,N}, the optimal strategy is Does not change with variable g i (t) decreases and decreases, so the following formula is obtained:

[0085]

[0086] in, is the decision value, is the monotonic threshold.

[0087] When the function g i (t) higher than When the threshold is reached, the transmission is selected, otherwise it will not participate in the transmission. At this time, the decision pruning is a polynomial complexity. The computational complexity is reduced, all transmission decisions with decision values ​​less than the monotonic threshold are excluded, and transmission decisions with decision values ​​greater than the monotonic threshold are retained as screening transmission decisions.

[0088] Since the amount of data and the number of channel states are discrete, the value of the joint decision factor for the pruned strategy is discrete and finite. The problem shifts from selecting the optimal decision strategy to selecting a monotonic threshold, that is, finding the optimal monotonic threshold to maximize the utility while satisfying the energy consumption constraint.

[0089] S140: Setting constraints for all terminals in the aggregation process, where the constraints include maximizing transmission utility and minimizing transmission energy consumption.

[0090] Specifically, calculating the transmission utility includes:

[0091] S1400. Obtain the preference coefficient and the number of valid data segments of each data segment transmitted at time t according to the screening transmission decision.

[0092] S1411. Calculate the transmission utility based on the preference coefficient and the amount of valid data segments.

[0093] Specifically, the data segment preference coefficient is [the value of the value of the data segment in the original text]: During data transmission, due to harsh environments and terminal energy constraints, not all data may be transmitted. Therefore, important data is prioritized for transmission. The size of the data segment preference coefficient represents the importance of the data segment. The limited number of data segments is due to the use of redundant data storage. When multiple terminals transmit the same copy, only one data segment is effectively transmitted. Therefore, the number of valid data segments of data r collected during data aggregation process t is calculated as follows:

[0094]

[0095] Among them, u r (t) is the effective data segment of the rth data transmitted at time t, d(t) is the transmission decision, s r (t) is the storage status of the rth data in the collaborative group at time t, and P is the maximum number of data segments that each data can be divided into.

[0096] Taking into account the different preferences of each data, the total joint utility of the system is modeled as the weighted sum of the effective data segment utilities of each data according to its preference coefficient, which is defined as follows:

[0097]

[0098] βr(t) for t Preference coefficient of moment data r, β max is the largest preference coefficient among all the data.

[0099] During the aggregation process, the mobile terminal transmits all the data segments of the required data it has stored, so the energy consumption penalty can be determined by the channel state. i (t) is the energy consumption penalty of terminal i in the aggregation process t. The transmission energy consumption is calculated as follows:

[0100]

[0101] Among them, d i (t) is the transmission decision of terminal i at time t, ci (t) is the channel state of terminal i.

[0102] S150, based on the transmission decision, obtaining the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, and the transmission utility and transmission energy consumption of other terminals before time t-D.

[0103] Specifically, since the distributed decision is adopted, i.e., each terminal decides whether to transmit data by itself, the terminal cannot obtain the data information to be transmitted at time t, therefore, the delay time D is set, and the energy consumption and utility of the data transmitted by other terminals before time t-D are taken as the energy consumption and transmission utility at the current time, so as to estimate the energy consumption and transmission utility of all terminals.

[0104] S160, obtaining the Lyapunov drift minus penalty of all terminals according to the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, the transmission utility and transmission energy consumption of other terminals before time t-D, and the constraint condition.

[0105] S1600, obtaining the device channel state and decision feedback of other terminals at time t-D.

[0106] S1610, obtaining the energy consumption before time t-D according to the device channel state and decision feedback at time t-D.

[0107] S1620, establishing a virtual queue according to the transmission energy consumption, the energy consumption before time t-D, and the initial queue value, and obtaining a Lyapunov function according to the virtual queue.

[0108] S1630, obtaining the Lyapunov drift minus penalty according to the virtual queue, the Lyapunov function, and the constraint condition.

[0109] Specifically, in each aggregation process, a mobile terminal selects a strategy in m∈{1,...,M}, and D≥0 represents the feedback delay of the system, and all mobile devices will receive the device channel state c(t) and decision feedback d(t) before time D at the end of the uploading process.

[0110] The energy consumption constraint is converted into a stability problem of a virtual queue. For each mobile terminal, a virtual queue Q(t)=(Q1(t),...,Q N (t)) is defined, where Q(0)=0, and e i (-1)=...=e i (-D)=0. Each mobile terminal will update Q(t) at the end of the tth uploading process, and the update formula is:

[0111] Q i(t+1) = max{Q i (t) + e i (t-D) - C,0}

[0112] where Q i (t+1) is the queue value of the next time, Q i (t) is the virtual queue value of the current time, e i (t-D) is the transmission energy consumption at time D ago, and C is the average energy consumption of the terminal.

[0113] In a data aggregation process, the mobile terminal cannot obtain the channel state and decision of other terminals. Therefore, an approximate method is used, each terminal will know the channel state c(t-D) and decision d(t-D) at time D ago, and the energy consumption and utility in the previous process are sampled and approximated using a window of positive integer W to estimate the current energy consumption and utility:

[0114]

[0115] If the virtual queue is stable (i.e. ), the energy cost constraint is satisfied. The Lyapunov function is defined as follows:

[0116]

[0117] Specifically, the constraint condition is to minimize the transmission energy consumption and maximize the transmission utility, which can be expressed by the following formula:

[0118]

[0119] C is the average energy consumption constraint of the mobile terminal.

[0120] The Lyapunov function represents a scalar measure of the queue Q(t). If the value of L(t) is small, the virtual queue of the mobile device has strong stability, that is, the energy cost constraint is satisfied. In order to keep the virtual queue stable at the delay D, the Lyapunov drift is defined as:

[0121] Δ(t+D) = L(t+D+1) - L(t+D)

[0122] Where L(t+D+1) represents the Lyapunov function value at time t+D+1, L(t+D) represents the Lyapunov function value at time t+D, Δ(t+D) is the change of the system within the time period D, and the smaller the value of Δ(t+D), the more stable the system.

[0123] The purpose of the drift is to avoid the Lyapunov function being in the congestion state, and minimizing the Lyapunov drift above can keep the stability of the queue. In view of the feedback delay of the system at D time, the queue stability at the current time cannot be obtained until after D time, so the Lyapunov drift at D time is used.

[0124] In order to maximize the utility while minimizing the energy consumption, the optimization objective is converted into minimizing the upper bound of the Lyapunov drift minus penalty expression E{Δ(t+D)-Vu(t)|Q(t)}. In order to control the trade-off between queue stability (i.e. energy consumption) and utility, a parameter V is introduced. As the value of V increases, the coordination group will gradually change from being more inclined to keep low energy consumption to being more inclined to transmit greater effective system utility.

[0125] Therefore, the following formula is obtained:

[0126] For a given V>0. Each upload process has:

[0127]

[0128] The left side of the inequality represents the Lyapunov drift minus penalty, and the right side of the inequality is the upper bound of the Lyapunov drift minus penalty. All screening transmission decisions at time t are substituted into the above formula, and the smallest upper bound of the Lyapunov drift minus penalty is selected. The transmission decision corresponding to the smallest upper bound of the Lyapunov drift minus penalty is taken as the final transmission decision. At this time, the transmission energy consumption is the smallest and the transmission utility is the largest.

[0129] S170, traverse the set of monotonic thresholds, and select a transmission decision whose Lyapunov drift minus penalty satisfies the constraint condition as the final transmission decision.

[0130] S1700, traverse the set of monotonic thresholds to obtain the Lyapunov drift minus penalty of different transmission decisions, and calculate the upper bound of the Lyapunov drift minus penalty as an optimization objective function.

[0131] S1710, obtain the transmission decision corresponding to the smallest optimization objective function as the final transmission decision.

[0132] Specifically, when the upper bound of the Lyapunov drift minus penalty is the smallest, that is, when the energy consumption is the smallest and the transmission utility is the largest, the transmission decision corresponding to the smallest optimization objective function is obtained as the final transmission decision.

[0133] S180, perform data aggregation on emergency data according to the final transmission decision.

[0134] An emergency data aggregation system comprises:

[0135] An acquisition module is configured to acquire a number of single-time converging emergency data, divide each piece of the emergency converging data into a plurality of data segments of the same size, redundantly copy the data segments into multiple copies, and store the data segments in a plurality of mobile terminals to obtain data segments stored in each terminal;

[0136] A decision module is configured to establish a joint decision factor according to a channel state of each terminal at time t and a data demand preference of each data segment, and obtain a decision function according to the joint decision factor;

[0137] An acquisition module is configured to acquire a set of monotonous thresholds;

[0138] A setting module is configured to set a constraint condition of all terminals in a converging process, and the constraint condition includes maximizing transmission utility and minimizing transmission energy consumption;

[0139] A calculation module is configured to obtain transmission utility and transmission energy consumption of a current terminal when transmitting a data segment at time t, and transmission utility and transmission energy consumption of other terminals before time t-D, based on the transmission decision;

[0140] A constraint module is configured to obtain Lyapunov drift minus penalty of all terminals according to the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, the transmission utility and transmission energy consumption of the other terminals before time t-D, and the constraint condition;

[0141] A traversal module is configured to traverse the set of monotonous thresholds, and select a transmission decision satisfying the constraint condition of the Lyapunov drift minus penalty as a final transmission decision;

[0142] A converging module is configured to perform data convergence on the emergency converging data according to the final transmission decision.

[0143] Embodiments of the application further disclose a terminal device including a memory and a processor, the memory stores a computer program capable of running on the processor, and the processor loads and executes the computer program, and adopts an emergency data converging method.

[0144] The terminal device can be a computer device such as a desktop computer, a notebook computer, or a cloud server, and the terminal device includes but is not limited to a processor and a memory, for example, the terminal device can further include an input / output device, a network access device, and a bus.

[0145] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), programmable logic devices (PLD), or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, and the present application is not limited thereto.

[0146] The memory can be an internal storage unit of the terminal device, for example, a hard disk or a memory of the terminal device, or an external storage device of the terminal device, for example, a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD), or a flash memory card (FC) equipped on the terminal device, or a combination of the internal storage unit and the external storage device. The memory is used to store a computer program and other programs and data required by the terminal device, and can also be used to temporarily store data that has been output or will be output, and the present application is not limited thereto.

[0147] The terminal device stores one of the emergency data aggregation methods in the memory of the terminal device, and loads and executes the method on the processor of the terminal device, thereby facilitating use.

[0148] The computer readable storage medium stores a computer program, and the computer program is executed by the processor to use one of the emergency data aggregation methods.

[0149] The computer program can be stored in the computer readable medium, and the computer program includes computer program code in the form of source code, object code, executable files, or some intermediate code, etc. The computer readable medium includes any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the computer readable medium includes but is not limited to the above-mentioned components.

[0150] The computer readable storage medium stores one of the emergency data aggregation methods in the computer readable storage medium, and loads and executes the method on the processor, thereby facilitating storage and application of the method.

[0151] Those skilled in the art should understand that the above discussion of any embodiment is only exemplary, and is not intended to limit the scope of protection of the present application; under the idea of the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes of different aspects of one or more embodiments of the present application as described above, which are not provided in details for the sake of brevity.

[0152] Those skilled in the art should understand that the above discussion of any embodiment is only exemplary, and is not intended to limit the scope of protection of the present application; under the idea of the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes of different aspects of one or more embodiments of the present application as described above, which are not provided in details for the sake of brevity.

[0153] One or more embodiments of the present application are intended to cover all such alternatives, modifications and variations as fall within the broad scope of the present application. Therefore, any omission, modification, equivalent replacement, improvement, etc. made in the spirit and principle of one or more embodiments of the present application should be included in the scope of protection of the present application.

[0154] To sum up, the above is only a preferred embodiment of the present application, and is not intended to limit the scope of protection of the present application. Any modification, equivalent replacement, improvement, etc. made in the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A method for converging emergency data, characterized in that include: Obtaining the amount of single-aggregation emergency data aggregated in a single time, dividing each emergency aggregate data into multiple data segments of the same size, redundantly copying the data segment into multiple copies, and storing the copies in multiple terminals to obtain the data segments stored in each terminal; Establishing a joint decision factor based on the channel state of each terminal at time t and the data demand preference of each data segment, and obtaining a decision function based on the joint decision factor; Get the monotonic threshold set; Obtaining a plurality of transmission decisions based on the decision function and the monotonic threshold set, the transmission decision being whether each terminal transmits a data segment at time t; Setting constraints for all terminals in the aggregation process, wherein the constraints include maximizing transmission utility and minimizing transmission energy consumption; Based on the transmission decision, the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t and the transmission utility and transmission energy consumption of other terminals before time tD are obtained; D is the delay time; According to the transmission utility and energy consumption of the current terminal when transmitting the data segment at time t and the transmission utility and energy consumption of other terminals before time tD and the constraints, the Lyapunov drift minus penalty of all terminals is obtained; Traversing the monotonic threshold set, and selecting the transmission decision whose Lyapunov drift minus penalty satisfies the constraint condition as the final transmission decision; Aggregating the emergency aggregated data according to the final transmission decision; Calculating transfer utility includes: Obtain the preference coefficient and the number of valid data segments for each data segment transmitted at time t; The transmission utility is calculated according to the preference coefficient and the effective data segment amount.

2. The emergency data aggregation method according to claim 1, characterized in that: The emergency aggregated data includes personnel location data and available resource data.

3. The emergency data aggregation method according to claim 1, characterized in that: The joint decision factor is expressed as: ； Where Y is the channel state-data preference balance parameter of the cooperative group, for Time data The preference coefficient of It means that the jth data segment of the rth data at time t is stored on terminal i. R is the number of data copies that need to be transmitted during one aggregation process. for Moment mobile terminal The channel status, for time The storage status of individual data in the collaborative group, is the data preference coefficient; P is the number of data segments; The decision function is: ； in, is the decision value, is the monotonic threshold.

4. The emergency data aggregation method according to claim 1, wherein: According to the decision function and the monotonic threshold set, a plurality of transmission decisions are obtained, including: Obtaining a threshold to be determined according to the monotonic threshold set; Obtain a decision value based on the current terminal's channel status at time t, the data segment's data demand preference, and the decision function; Determining whether the decision value is greater than the threshold to be determined; If the decision value is greater than or equal to the threshold to be determined, the current terminal transmits data at time t as the transmission decision; If the decision value is less than the threshold to be determined, the current terminal does not transmit data at time t as the transmission decision; Traverse the monotonic threshold set to obtain multiple transmission decisions of the current terminal under different monotonic thresholds.

5. The emergency data aggregation method according to claim 1, characterized in that: The Lyapunov drift minus penalty for all terminals is obtained based on the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t and the transmission utility and transmission energy consumption of other terminals before time tD as well as the constraints, including: Obtain the device channel status and decision feedback of other terminals at time tD; According to the device channel status and decision feedback at time tD, the energy consumption before time tD is obtained; Establishing a virtual queue according to the transmission energy consumption, the energy consumption before time tD, and the initial queue value, and obtaining a Lyapunov function according to the virtual queue; According to the virtual queue, the Lyapunov function and the constraint conditions, a Lyapunov drift minus penalty is obtained.

6. The emergency data aggregation method according to claim 1, characterized in that: The traversing the monotonic threshold set and selecting the transmission decision in which the Lyapunov drift minus penalty satisfies the constraint condition as the final transmission decision includes: Traversing the monotonic threshold set to obtain the Lyapunov drift minus penalty for different transmission decisions, and calculating the upper bound of the Lyapunov drift minus penalty as an optimization objective function; The transmission decision corresponding to the minimum optimization objective function is obtained as the final transmission decision.

7. An emergency data aggregation system for implementing the method of claim 1, characterized in that include: an acquisition module, configured to acquire the amount of single-aggregation emergency data, divide each emergency aggregate data into a plurality of data segments of the same size, redundantly copy the data segment into a plurality of copies, and store the copies in a plurality of mobile terminals to obtain a data segment stored in each terminal; A decision module, configured to establish a joint decision factor based on the channel state of each terminal at time t and the data demand preference of each data segment, and obtain a decision function based on the joint decision factor; An acquisition module, used to obtain a monotonic threshold set; A setting module, configured to set constraints for all terminals in the aggregation process, wherein the constraints include maximizing transmission utility and minimizing transmission energy consumption; A calculation module, configured to obtain, based on the transmission decision, the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t, and the transmission utility and transmission energy consumption of other terminals before time tD; The constraint module is used to obtain the Lyapunov drift minus penalty of all terminals based on the transmission utility and transmission energy consumption of the current terminal when transmitting the data segment at time t and the transmission utility and transmission energy consumption of other terminals before time tD as well as the constraint conditions; A traversal module, configured to traverse the monotonic threshold set and select a transmission decision in which the Lyapunov drift minus penalty satisfies a constraint condition as a final transmission decision; An aggregation module is configured to aggregate the emergency aggregation data according to the final transmission decision.

8. A terminal device comprising a memory and a processor, characterized in that: The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, the aggregation method according to any one of claims 1 to 6 is adopted.

9. A computer-readable storage medium storing a computer program, wherein: When the computer program is loaded and executed by a processor, the aggregation method according to any one of claims 1 to 6 is adopted.

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