Low-cost multi-hop link transmission method and system for signal-free pan-tilt

Abstract

The application provides a low-cost multi-hop link transmission method and system for a signal-free holder, relates to the technical field of multi-hop transmission of a holder, and comprises the following steps: abstracting the holder in a monitoring area as a node set, and determining a wireless directional link set according to the distance between nodes and the wireless coverage radius; taking the sum of the wireless transmission and the node storage hardware cost of the whole network as the target for minimization, and constructing a weighted sum target function; establishing the uniqueness of the next hop, the consistency of the link flow selection, the upper bound, the flow conservation and aggregation, the 4G node wireless external transmission restriction, the node storage capacity and the acyclic constraint, and constructing a mixed integer linear programming model; combining the calibration parameters, using a mixed integer programming solver to obtain the optimal solution of the model, that is, the next hop of the non-4G node, the link code rate and the node storage capacity, and generating a multi-hop link transmission strategy, so as to accurately determine the unique next hop of the non-4G holder and form an acyclic convergence topology, ensure that the image flow reaches the 4G node, and reduce the transmission cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of multi-hop transmission of a pan-tilt head, and particularly relates to a low-cost multi-hop link transmission method and system for a signal-free pan-tilt head. BACKGROUND

[0002] In a power transmission network safety monitoring system, a monitoring area is usually composed of a plurality of series towers, and each tower is installed with a pan-tilt head for collecting real-time monitoring images under the previous tower to form a continuous monitoring coverage to ensure the safe operation of the power transmission network. In an area with good signal coverage, the pan-tilt head can directly upload image data to the master station through the 4G network, but in remote areas with weak signals, only a few pan-tilt heads have 4G signals, and most pan-tilt heads without 4G signals need to rely on wireless transmission devices for multi-hop forwarding, and finally converge to any pan-tilt head with 4G signals for unified uploading.

[0003] However, the existing multi-hop forwarding scheme has significant defects: the transmission distance of the wireless transmission device is limited, which easily leads to link interruption; the local available storage space of each pan-tilt head is limited, which is difficult to cope with the code rate accumulation caused by multi-hop convergence; and due to the lack of a global optimization next-hop selection strategy, the upstream node continuously superimposes the code rate, which easily causes problems such as link unreachable, loop forwarding, and node buffer overflow, not only damaging the real-time and reliability of image transmission, but also leading to high overall transmission cost, which is difficult to balance the deployment cost and operation efficiency while ensuring the quality of monitoring services.

[0004] Therefore, it is necessary to provide a low-cost multi-hop link transmission method and system for a signal-free pan-tilt head to solve the above technical problems. SUMMARY

[0005] To solve the above technical problems, the present application provides a low-cost multi-hop link transmission method and system for a signal-free pan-tilt head, which is used to solve the problem that in remote areas, the prior art cannot determine the only next hop of the 4G-free pan-tilt head and form a loop-free convergence topology, and cannot ensure that the image flow reaches the 4G node and reduce the transmission cost.

[0006] The low-cost multi-hop link transmission method for a signal-free pan-tilt head provided by the present application comprises:

[0007] All pan-tilt heads in a target monitoring area are abstracted as a node set, and a set of reachable wireless directed links is determined according to the distance between nodes and the wireless coverage radius;

[0008] A weighted sum objective function is constructed to minimize the sum of the wireless transmission cost and the node storage hardware cost corresponding to the set of wireless directed links;

[0009] Based on the weighted sum objective function, next-hop uniqueness constraints, link traffic selection consistency and upper bound constraints, flow conservation and aggregation constraints, 4G node wireless outgoing constraint, node storage capacity constraint, and acyclic constraint based on potential energy variables are established for the wireless directed link set, and a mixed integer linear programming model is constructed.

[0010] By combining the field data calibration parameters of the target monitoring area, the optimal solution of the mixed integer linear programming model is obtained using a mixed integer programming solver, namely the next hop of the non-4G node, the link code rate and the node storage capacity corresponding to the wireless directed link set, and a low-cost multi-hop link transmission strategy is generated.

[0011] Preferably, the step of abstracting all PTZ units within the target monitoring area into a set of nodes, and determining the set of reachable directed wireless links based on the distance between nodes and the wireless coverage radius, specifically includes:

[0012] All PTZ cameras within the target monitoring area are abstracted as the node set N, and the node set N is divided into a node set G with 4G signal and a node set U=NG without 4G signal;

[0013] For any node any node ,and If and only if the distance between node i and node j The wireless coverage radius of node i When the directed link (i,j) from node i to node j is determined to belong to the set E of reachable wireless directed links.

[0014] Preferably, the expression for the weighted sum objective function is as follows:

[0015] In the formula, This represents the weighted sum objective function; This indicates the cost of wireless transmission across the entire network. This indicates the hardware cost of node storage; These represent the relative importance of the overall network wireless transmission cost and the node storage hardware cost in the weighted sum objective function, respectively, and are used to uniformly balance the overall network wireless transmission cost and the node storage hardware cost. The unit data transmission cost of the directed link (i,j) from node i to node j is determined by the path loss model corresponding to the set of wireless directed links, and , ,in, This represents the cost scaling factor related to the transmit power of the wireless transmission device at node i. This represents the loss distance between node i and node j. denotes the propagation path loss exponent, which is used to reflect the distance gain attenuation strength of the set of wireless directed links, and ; denotes the aggregated traffic transmitted along the directed link (i,j) from node i to node j, and ; denotes the unit storage capacity cost of node ; denotes the actual configured storage capacity of node , and .

[0016] Preferably, the next-hop uniqueness constraint is as follows:

[0017] For any node , it satisfies , where denotes a binary variable, denotes that node i chooses node j as the unique next hop, denotes that node i does not choose node j as the unique next hop;

[0018] The link traffic selection consistency and upper bound constraint is as follows:

[0019] For the directed link from node i to node j, it satisfies , where denotes the outgoing upper bound of node i, i.e., the sum of the real-time image code rates of all nodes in the node set N, and , denotes the real-time image code rate of node .

[0020] Preferably, the flow conservation and aggregation constraint is as follows:

[0021] For any node , it satisfies , where denotes the real-time image code rate of node i; denotes the aggregated traffic transmitted along the directed link (k,i) from node k to node i;

[0022] The 4G node wireless outgoing restriction constraint is as follows:

[0023] When the set of wireless directed links E is constructed, only is defined, and E does not contain .

[0024] Preferably, the node storage capacity constraint includes a minimum storage capacity constraint and a maximum storage capacity constraint;

[0025] For any node The minimum storage capacity constraint is as follows:

[0026] where H denotes the real-time service buffer duration, and where, denotes the minimum resident cache capacity, denotes the link code rate; denotes the aggregated traffic transmitted along the directed link from node k to node ; denotes the aggregated traffic transmitted along the directed link from node k to node ;

[0027] The maximum storage capacity constraint is as follows:

[0028] where, denotes the maximum installable storage capacity of node .

[0029] Preferably, the potential energy variable-based acyclic constraint is as follows:

[0030] For the directed link from node i to node j, satisfies where, denote the potential energy variables of nodes i and j, respectively; M denotes a constant, , denotes the total number of nodes in the set of nodes without 4G signals;

[0031] Meanwhile, for any node , it is fixed that ; for any node , the constraint is satisfied.

[0032] Preferably, for any node , the uplink traffic upper limit of node g is set as , and the uplink traffic constraint of node g is set as: where, denotes the uplink traffic converged to node g through multi-hop links; denotes the aggregated traffic transmitted along the directed link (k, g) from node k to node g;

[0033] For any node , if where, denotes the uplink traffic converged to node through multi-hop links, denotes the aggregated traffic transmitted along the directed link from node k to node ;​ aggregate traffic of the transmission; representing a node uplink traffic cap; representing that the uplink traffic is close to the threshold, automatically switching part of the original next hop of the node k pointing to the node to other nodes with sufficient uplink traffic , i.e. adjusting the binary variable and .

[0034] A low-cost multi-hop link transmission system for signal-free transmission of a pan-tilt camera, comprising:

[0035] a link set acquisition module, configured to abstract all pan-tilt cameras in a target monitoring area as a node set, and determine a set of reachable wireless directed links according to distances between nodes and a wireless coverage radius;

[0036] a target function construction module, configured to construct a weighted sum target function with a target of minimizing a sum of a whole-network wireless transmission cost and a node storage hardware cost corresponding to the set of wireless directed links;

[0037] a constraint condition establishment module, configured to establish, based on the weighted sum target function, a next-hop uniqueness constraint, a link traffic selection consistency and upper bound constraint, a flow conservation and aggregation constraint, a 4G node wireless outgoing limit constraint, a node storage capacity constraint, and a loop-free constraint based on a potential energy variable, to construct a mixed integer linear programming model;

[0038] a transmission strategy generation module, configured to combine on-site data calibration parameters of the target monitoring area, use a mixed integer programming solver to obtain an optimal solution of the mixed integer linear programming model, i.e. a non-4G node next hop, a link code rate, and a node storage capacity corresponding to the set of wireless directed links, and generate a low-cost multi-hop link transmission strategy.

[0039] Compared with the related art, the low-cost multi-hop link transmission method and system for signal-free transmission of a pan-tilt camera provided by the present application have the following beneficial effects:

[0040] The application abstracts all pan-tilt machines in the target monitoring area as a node set, determines a set of reachable wireless directed links according to the distance between nodes and the wireless coverage radius, constructs a weighted sum objective function with the goal of minimizing the sum of the whole network wireless transmission cost and node storage hardware cost corresponding to the set of wireless directed links, establishes the next hop uniqueness constraint, link flow selection consistency and upper bound constraint, flow conservation and aggregation constraint, 4G node wireless outgoing restriction constraint, node storage capacity constraint corresponding to the set of wireless directed links, and the acyclic constraint based on potential energy variable based on the weighted sum objective function, and constructs a mixed integer linear programming model. The optimal solution of the mixed integer linear programming model, i.e. the next hop of non-4G nodes, link code rate and node storage capacity corresponding to the set of wireless directed links, is obtained by using a mixed integer programming solver combined with the on-site data calibration parameters of the target monitoring area, and a low-cost multi-hop link transmission strategy is generated, so that the only next hop of the non-4G pan-tilt machine can be accurately determined and an acyclic convergence topology is formed, ensuring that the image flow reaches the 4G node and reducing the transmission cost.

[0041] The application can accurately determine the only next hop for each non-4G pan-tilt machine, form an acyclic convergence topology combined with the acyclic constraint based on potential energy variable, completely eliminate the risk of loop forwarding, and strictly follow the constraints of wireless transmission distance and node storage upper limit, ensuring that the image flow of all non-4G pan-tilt machines can be stably transmitted to the 4G node, solving the problems of link unreachable and node buffer overflow. The application incorporates wireless transmission cost and storage hardware cost into unified optimization based on the weighted sum objective function, which can be flexibly adapted to operational requirements by adjusting the weight, i.e. in power supply shortage scenarios, transmission energy consumption can be reduced, and in budget sensitive scenarios, storage cost can be controlled first, thereby realizing the joint minimization of the two types of costs in the whole network, significantly reducing the deployment and operation cost. The application supports parameter calibration based on on-site data and mixed integer programming solution, and can dynamically update parameters and quickly re-optimize in the operation and maintenance stage according to link quality, node failure, etc. The system robustness and fault tolerance can be improved through extension strategies such as load balancing, 4G node uplink flow limiting, standby next hop switching, etc., ensuring the long-term stable and efficient operation of the monitoring business of the power transmission network in remote areas. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The flowchart of the low-cost multi-hop link transmission method for signal-free pan-tilt machines provided by the embodiments of the application is shown in the figure;

[0043] Figure 2 The system block diagram of the low-cost multi-hop link transmission system for signal-free pan-tilt machines provided by the embodiments of the application is shown in the figure;

[0044] Figure 3 The hardware structure schematic diagram of an electronic device provided by the embodiments of the application is shown in the figure. DETAILED DESCRIPTION

[0045] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0046] As Figure 1 shown in FIG. 1, which is a flowchart of a low-cost multi-hop link transmission method for a signal-free pan-tilt head provided by an embodiment of the present application, Figure 1 The execution subject of the method shown in FIG. 1 can be a software and / or a hardware device. The execution subject of the present application can include but is not limited to at least one of the following: a user equipment, a network equipment, etc. The user equipment can include but is not limited to a computer, a smart phone, a personal digital assistant (PDA) and the above-mentioned electronic devices, etc. The network equipment can include but is not limited to a single network server, a server group composed of multiple network servers or a cloud composed of a large number of computers or network servers based on cloud computing, wherein the cloud computing is a kind of distributed computing, which is a super virtual computer composed of a loose-coupled computer group. The present embodiment does not make any limitation in this regard. The steps S1 to S4 are included, and the details are as follows:

[0047] S1, abstracting all pan-tilt heads in a target monitoring area as a node set, and determining a set of reachable wireless directed links according to the distance between nodes and the wireless coverage radius;

[0048] The target monitoring area refers to an area where the pan-tilt head needs to be deployed to carry out image acquisition and data transmission, which can be a power transmission network monitoring area composed of a plurality of series towers. The pan-tilt head refers to a monitoring device with real-time image acquisition function, which is installed on a tower carrier and used to acquire monitoring images under the previous tower to ensure the safety of the power transmission network. The node set refers to a set formed after all pan-tilt heads in the target monitoring area are abstracted as nodes in graph theory. The wireless coverage radius refers to the maximum effective coverage distance of the wireless transmission device carried by the pan-tilt head without 4G signal. The set of reachable wireless directed links is a set of all one-way links, which only allows a 4G node to be the starting point of the link, and the 4G node cannot be the starting point of the link, to ensure that the link establishment conforms to the hardware transmission capability.

[0049] Firstly, all pan-tilt heads used for power transmission network monitoring in the target monitoring area can be abstracted as a set of nodes in graph theory, which will be divided into two categories according to whether they have 4G signals to distinguish data forwarding nodes and data uploading nodes. Then, the physical distance between any two pan-tilt heads is obtained through field mapping, and combined with the wireless coverage radius of the wireless transmission device carried by the pan-tilt head without 4G signal, the one-way link that meets the condition that the distance between nodes does not exceed the wireless coverage radius is selected to form a set of reachable wireless directed links. This set strictly limits the starting point of the link to be a node without 4G signal, and the 4G signal node cannot be the starting point of the link, which lays the topological foundation for subsequent multi-hop transmission path design.

[0050] S2, a weighted sum objective function is constructed to minimize the sum of the whole network wireless transmission cost and the node storage hardware cost corresponding to the set of wireless directed links;

[0051] It can be understood that the whole network wireless transmission cost refers to the total transmission cost generated by all selected wireless directed links. The node storage hardware cost refers to the total cost generated by configuring storage hardware to meet the real-time data buffering demand of all pan-tilt head nodes. The weighted sum objective function is a mathematical model constructed with the core target of minimizing the sum of the whole network wireless transmission cost and the node storage hardware cost.

[0052] Among them, the calculation logic of the whole network wireless transmission cost is the product sum of the unit data transmission cost of all selected wireless directed links and the aggregated traffic. The unit transmission cost is determined by the path loss model, and the aggregated traffic includes the real-time image bitrate generated by the node and the traffic imported by the downstream node. The node storage hardware cost is the product sum of the unit storage capacity cost of all pan-tilt head nodes and the actual configured storage capacity.

[0053] By setting non-negative weights to represent the importance proportion of the whole network wireless transmission cost and the node storage hardware cost respectively, and the weight value can be flexibly adjusted according to the engineering scene, such as focusing on reducing the transmission cost in remote areas with tight power supply, and focusing on controlling the storage cost in large-scale deployment with budget sensitivity, to realize the adaptation of engineering requirements and mathematical optimization.

[0054] S3, based on the weighted sum objective function, the next hop uniqueness constraint, the link traffic selection consistency and upper bound constraint, the flow conservation and aggregation constraint, the 4G node wireless external transmission restriction constraint, the node storage capacity constraint, and the acyclic constraint based on potential energy variable corresponding to the set of wireless directed links are established, and a mixed integer linear programming model is constructed;

[0055] It should be noted that the next hop uniqueness constraint is a constraint condition set for all nodes without 4G signal, requiring each 4G-free node to select only one other node as the next hop for data forwarding, avoiding bandwidth waste due to multiple next hops or data island due to no next hop, and ensuring that all 4G-free nodes have a unique transmission path.

[0056] The link flow selection consistency and upper bound constraint is a constraint condition set for all wireless directed links, which is used to realize strict binding of next hop selection and link flow allocation, that is, the link not selected as the next hop has no flow transmission, and the selected link transmits flow not exceeding the total sum of all node real-time image code rates in the network, avoiding invalid links occupying wireless resources or flow exceeding node processing capacity.

[0057] The flow conservation and aggregation constraint is a constraint condition set for all nodes without 4G signal, requiring the total outgoing flow of the node to be equal to the sum of the real-time image code rate generated by the node and all flows converging to the node, ensuring that the node will not have redundant flow to cause downstream link congestion, or flow loss to cause incomplete reception of data by the main station, thereby ensuring data transmission integrity.

[0058] The 4G node wireless outgoing limit constraint, that is, the wireless directed link only allows nodes without 4G signal as the starting point, prohibits nodes with 4G signal as the starting point of the link, and forces 4G nodes not to participate in wireless multi-hop forwarding, only as a flow sink, and the aggregated flow is uploaded to the main station through the 4G network, avoiding 4G node 4G uplink bandwidth overload due to forwarding flow.

[0059] The node storage capacity constraint is a constraint condition set for all gimbal nodes, including minimum storage capacity constraint and maximum storage capacity constraint. The former requires the node storage capacity to be not less than the product of the real-time service buffer time length and the total real-time code rate to be processed by the node, to meet the data temporary storage requirement, and the latter requires the node storage capacity to be not more than the maximum storage limit allowed by the hardware installation space and power supply capacity, to avoid hardware configuration exceeding physical bearing.

[0060] By introducing potential variables, a potential variable-based loop-free constraint is set, and each node is assigned a level value, wherein the potential of the 4G node is fixed as the lowest value, the potential of the 4G-free node is increased according to the level, and the selected link is required to satisfy that the potential of the starting node is higher than that of the terminal node, forcing the data transmission path to monotonically converge to the 4G node, fundamentally avoiding loop forwarding problem, without additional deployment of loop detection algorithm.

[0061] In practical applications, the next hop uniqueness constraint forces each 4G-free node to select only one next hop, avoiding path redundancy or data islands; the link traffic selection consistency and upper bound constraint achieve the binding of next hop selection and traffic allocation, with no traffic on unselected links and no traffic exceeding the total network code rate on selected links; the flow conservation and aggregation constraint ensures that the 4G-free node's outgoing traffic is equal to the sum of the local code rate and the incoming flow, avoiding traffic redundancy or loss; the 4G node wireless outgoing restriction constraint defines the forbidden 4G node as the starting point of the link through the link set, allowing it to only serve as a traffic sink; the node storage capacity constraint contains two types of minimum and maximum constraints; and the acyclic constraint based on potential variables uses hierarchical potential distribution to force the potential of the link starting point to be higher than that of the end point, fundamentally eliminating loops. After integrating the above constraints and objective functions, a mixed integer linear programming model is constructed.

[0062] S4, in combination with the field data calibration parameters of the target monitoring area, uses a mixed integer programming solver to obtain the optimal solution of the mixed integer linear programming model, i.e., the non-4G node next hop corresponding to the wireless directed link set, the link code rate, and the node storage capacity, to generate a low-cost multi-hop link transmission strategy.

[0063] Among them, the field data calibration parameters refer to the model input parameters collected or calibrated on site in the target monitoring area, including the distance between nodes, the wireless coverage radius of the 4G-free node, the real-time image code rate of each node, the real-time service buffer duration, the maximum installable storage capacity of the node, the unit storage capacity cost, the link unit data transmission cost, etc., which are the basic inputs to ensure that the solution of the mixed integer linear programming model fits the engineering practice. The optimal solution is the decision variable result output by the mixed integer linear programming solver, which satisfies all the constraint conditions and makes the weighted sum objective function take the minimum value, containing the next hop selection of the 4G-free node, the transmission code rate of each link, and the storage capacity configuration of each node, etc.

[0064] The non-4G node next hop is determined by the optimal solution and is the unique data forwarding target node of each node without 4G signal, which is the core basis for building an acyclic multi-hop transmission topology and directly determines the direction of data transmission path. The link code rate is determined by the optimal solution and is the real-time data rate actually transmitted by each wireless directed link, which reflects the bandwidth demand of the link and is used to calculate the power, bandwidth configuration, and modulation and coding parameters of the link wireless transmission device to ensure that the link transmission quality meets the real-time monitoring requirements. The node storage capacity is determined by the optimal solution and is the actual storage hardware capacity that each pan-tilt node needs to be configured, which needs to meet both the minimum storage capacity constraint and the maximum storage capacity constraint, and is a direct basis for node storage hardware procurement and deployment. The low-cost multi-hop link transmission strategy is an engineering implementation plan generated based on the optimal solution, covering non-4G node next hop configuration, link code rate adaptation, and node storage hardware deployment, etc., and can achieve the goal of acyclic transmission, minimum cost, and reliable data reaching the 4G node.

[0065] Firstly, the input parameters of the mixed integer linear programming model are obtained by field collection and calibration, including the distance between nodes, the wireless coverage radius of the non-4G node, the real-time image code rate of each node, the buffer time length, the maximum installable storage capacity of the node, the unit storage cost, the unit transmission cost of the link, etc., to ensure that the solving result fits the actual field. Then, the mixed integer linear programming solver is used to solve, to obtain the solution that satisfies all constraints and makes the objective function optimal, and the core results include the unique determination of the next hop of the non-4G node, the transmission code rate of each wireless directed link, i.e., the link code rate, and the storage capacity configuration of each node. Finally, based on these optimal results, a low-cost multi-hop link transmission strategy is generated to directly guide the field deployment, such as configuring the next hop forwarding relationship of the non-4G node, adapting the wireless device parameters of the link code rate, and configuring the hardware according to the storage capacity, while supporting dynamic updating and rapid re-optimization of parameters in the operation and maintenance stage, to ensure that the low-cost multi-hop link transmission strategy fits the field changes for a long time.

[0066] In the specific implementation process, all the pan-tilt heads in the target monitoring area are abstracted as a node set, and the reachable wireless directed link set is determined according to the distance between nodes and the wireless coverage radius, which specifically includes:

[0067] All the pan-tilt heads in the target monitoring area are abstracted as the node set N, and the node set N is divided into a node set G with 4G signal and a node set U=N-G without 4G signal.

[0068] For any node , any node , and , the directed link (i,j) from node i to node j belongs to the reachable wireless directed link set E only when the distance between node i and node j does not exceed the wireless coverage radius of node i.

[0069] It can be understood that all the pan-tilt heads for power transmission network monitoring in the target monitoring area are uniformly abstracted as a node set in graph theory, as the basic unit of the multi-hop transmission topology. According to whether the pan-tilt head has 4G signal, the node set is divided into two subsets, i.e., the node subset with 4G signal, which serves as the data uplink hub and only transmits data to the master station through the 4G network without participating in wireless multi-hop forwarding, and the node subset without 4G signal, which serves as the data forwarding node and needs to transmit data to the 4G node through wireless link multi-hop.

[0070] For the node without 4G signal, the hardware performance of its wireless transmission device and the field geographic condition are taken as the basis to determine the reachable directed link. Specifically, for any one node without 4G signal and any other node, and the two nodes are not the same node, the physical distance between the two nodes is obtained through field mapping, if the distance does not exceed the wireless coverage radius of the node without 4G signal, it is determined that a one-way link from the node without 4G signal to the other node can be established between the two nodes, and all one-way links satisfying the condition constitute a set of reachable wireless directed links, ensuring that the link establishment meets the hardware transmission capability, and providing a legal link range for subsequent multi-hop path optimization.

[0071] The expression of the weighted sum objective function is as follows:

[0072] In the formula, denotes the weighted sum objective function; denotes the total network wireless transmission cost; denotes the node storage hardware cost; denote the importance proportion of the total network wireless transmission cost and the node storage hardware cost in the weighted sum objective function, respectively, for balancing the total network wireless transmission cost and the node storage hardware cost; denotes the unit data transmission cost of the directed link (i,j) from node i to node j, which is determined by the path loss model corresponding to the set of wireless directed links, and , wherein, denotes the cost scaling coefficient related to the transmission power of the wireless transmission device of node i, denotes the loss distance between node i and node j, denotes the propagation path loss exponent, which is used to reflect the distance gain attenuation strength of the set of wireless directed links, and ; denotes the aggregated traffic transmitted along the directed link (i,j) from node i to node j, and ; denotes the unit storage capacity cost of node ; denotes the actual configured storage capacity of node , and .

[0073] The weighted sum objective function quantifies two types of core costs and associates them through weights: one type is the whole network wireless transmission cost, and the other type is the node storage hardware cost, and the two are superimposed through corresponding weights to form the total optimization objective. Among them, the two types of weights respectively represent the importance proportion of the whole network wireless transmission cost and the node storage hardware cost in the total objective, which can be flexibly adjusted according to the engineering scene, such as increasing the transmission cost weight to preferentially reduce energy consumption when power supply is tight in remote areas, increasing the storage cost weight to control the procurement cost when the hardware budget is sensitive, and then realizing the unified trade-off of the two types of costs.

[0074] The calculation of the whole network wireless transmission cost depends on the unit data transmission cost of each directed link and the aggregated traffic. The unit data transmission cost is determined by the path loss model corresponding to the set of wireless directed links, and the value is non-negative. When calculating, the transmission power of the wireless transmission device of the source node, the loss distance between the two nodes and the propagation path loss exponent need to be associated. The aggregated traffic refers to the total data amount transmitted along the directed link, and the value is also non-negative, including the local data of the source node and the imported data of the downstream node. The product of the two is added, and then multiplied by the transmission cost weight, which constitutes the whole network wireless transmission cost item.

[0075] The calculation of the node storage hardware cost is associated with the unit storage capacity cost and the actual configured storage capacity of each node. The unit storage capacity cost reflects the procurement unit price of the node storage hardware. The actual configured storage capacity needs to meet the non-negative constraint and at the same time meet the node hardware bearing limit. The product of the two is added, and then multiplied by the storage cost weight, forming the node storage hardware cost item. The superposition of the two types of cost items constitutes the complete weighted sum objective function, and the optimal configuration scheme after balancing the two types of costs can be obtained by solving the function.

[0076] The next hop uniqueness constraint is as follows:

[0077] For any node , it satisfies , wherein is a binary variable, represents that node i selects node j as the unique next hop, represents that node i does not select node j as the unique next hop;

[0078] The link traffic selection consistency and upper bound constraint is as follows:

[0079] For the directed link from node i to node j , it satisfies , wherein represents the outgoing upper bound of node i, that is, the sum of the real-time image code rate of all nodes in the node set N, and , represents the real-time image code rate of node .

[0080] The next hop uniqueness constraint forces each node without 4G signal to select and only select one other node as the next hop for data forwarding. This constraint marks the selection state by a binary variable, which takes the value of 1 when the node determines to select the unique next hop node, and takes the value of 0 when the node does not select. This completely avoids the waste of wireless bandwidth caused by multiple next hops or the data island caused by no next hop, and ensures that all data streams of nodes without 4G have a unique transmission path.

[0081] The link flow selection consistency and upper bound constraint strictly binds the selection of the next hop and the link flow. For any directed link, if it is not selected as the next hop, the link flow is forced to be 0 to avoid invalid links occupying wireless resources; if it is selected as the next hop, the link flow does not exceed the upper bound of the node's outgoing, and the upper bound of the outgoing is the sum of the real-time image code rates of all PTZ nodes, thereby preventing the flow from exceeding the data processing capacity of the node, ensuring that the link flow and the selection of the next hop are completely matched, and guaranteeing the stability of data transmission.

[0082] The flow conservation and aggregation constraint is as follows:

[0083] For any node , it satisfies , where represents the real-time image code rate of the node i; represents the aggregated flow transmitted along the directed link (k, i) from node k to node i;

[0084] The 4G node wireless outgoing limit constraint is as follows:

[0085] When constructing the set of wireless directed links E, only is defined, and E does not contain .

[0086] In actual application, the flow conservation and aggregation constraint forces the total outgoing flow of a node without 4G signal to be equal to the sum of the real-time image code rate generated by the node itself and the aggregated flow imported into the node. The imported aggregated flow refers to the data amount transmitted along the directed link from other nodes without 4G signal to the node, and through this constraint, it can be ensured that the node will neither cause congestion of downstream links due to the outgoing flow being greater than the total incoming flow, nor cause data loss due to the outgoing flow being less than the total incoming flow, thereby completely guaranteeing the data integrity in the multi-hop transmission process.

[0087] The 4G node wireless sending restriction constraint is realized by a construction rule of a wireless directed link set, and the rule is that the set only contains links with a 4G node as a starting point and all nodes as ending points, and does not contain a link with a 4G node as a starting point, so that the 4G node is forced to only receive multi-hop forwarded data as a traffic sink point and does not participate in wireless multi-hop forwarding, thereby avoiding 4G network uplink bandwidth overload caused by forwarding data of other nodes by the 4G node.

[0088] The node storage capacity constraint includes a minimum storage capacity constraint and a maximum storage capacity constraint;

[0089] For any node , the minimum storage capacity constraint is as follows:

[0090] wherein H represents a real-time service buffer duration, and wherein, represents a minimum resident cache capacity, represents a link code rate; represents a directed link from node k to node ; represents aggregated traffic transmitted along the directed link from node k to node ;

[0091] The maximum storage capacity constraint is as follows:

[0092] wherein, represents a maximum storage capacity that can be installed in node .

[0093] It should be noted that the minimum storage capacity constraint is for all gimbal nodes, and requires that the actual storage capacity of the node is not less than the minimum resident cache capacity required by the real-time service. The minimum resident cache capacity is determined by the product of the real-time service buffer duration and the link code rate, which can avoid loss of real-time image data due to insufficient cache during transmission fluctuations, and ensure data transmission continuity.

[0094] The maximum storage capacity constraint also covers all nodes, and forces the actual storage capacity of the node to be not more than the maximum storage capacity that can be installed in the node. The maximum storage capacity is determined by the hardware installation space, power supply capacity and other physical conditions of the gimbal, such as the difference in maximum storage capacity between small gimbal and large relay gimbal, which can prevent hardware installation failure or power overload caused by excessive storage module configuration, and ensure that the storage configuration conforms to the engineering practice.

[0095] The potential variable-based acyclic constraint is as follows:

[0096] For a directed link from node i to node j​ , satisfy wherein, respectively represent the potential energy variables of nodes i, j; M represents a constant, , represents the total number of nodes in the set of nodes without 4G signals;

[0097] At the same time, for any node , fix ; for any node , constrain .

[0098] In practical applications, the acyclic constraint based on the potential energy variable requires that, for all directed links, the link must satisfy the potential energy variable relationship between the start node and the end node, so that the potential energy of the start node of the selected link is necessarily higher than that of the end node, and the potential energy of the 4G node is the lowest. The potential energy of the data transmission path monotonically decreases from the node without 4G to the node with 4G, which fundamentally avoids loops, such as bidirectional forwarding between nodes, without the need for additional deployment of loop detection algorithms, thereby ensuring the directionality and reliability of the multi-hop topology.

[0099] For any node , set the upper limit of the uplink traffic of node g as set the uplink traffic constraint for node g: wherein, represents the uplink traffic converged to node g through multi-hop links; represents the aggregated traffic transmitted along the directed link (k, g) from node k to node g;

[0100] For any node , if wherein, represents the uplink traffic converged to node through multi-hop links, represents the aggregated traffic transmitted along the directed link from node k to node ; represents the upper limit of the uplink traffic of node ; represents the uplink traffic close to the threshold value, then automatically switch part of the next hop of node k originally pointing to node to other nodes with sufficient uplink traffic, that is, adjust the binary variable and .

[0101] It needs to be explained that for each node with 4G signal, the uplink traffic upper limit of the node is set according to the uplink bandwidth capability of the node accessing the 4G base station, and then the uplink traffic constraint is configured for the node, so as to prevent the 4G network delay or data loss caused by uplink overload of the single 4G node.

[0102] If the aggregated uplink traffic of a node with 4G signal is close to the set uplink traffic upper limit, part of the nodes without 4G signal originally directed to the 4G node are automatically redistributed to other 4G nodes with sufficient uplink traffic, so as to realize uplink traffic balance among 4G nodes and guarantee the overall data transmission stability.

[0103] As shown in Figure 2 Fig. 1 is a system block diagram of a low-cost multi-hop link transmission system for a signal-free transmission pan-tilt head provided by an embodiment of the present application, and the system comprises:

[0104] A link set acquisition module is configured to abstract all pan-tilt heads in a target monitoring area as a node set, and determine a set of reachable wireless directed links according to the distance between nodes and the wireless coverage radius.

[0105] A target function construction module is configured to construct a weighted sum target function with the goal of minimizing the sum of the network-wide wireless transmission cost and node storage hardware cost corresponding to the set of wireless directed links.

[0106] A constraint condition establishment module is configured to establish the next-hop uniqueness constraint, the link traffic selection consistency and upper bound constraint, the flow conservation and aggregation constraint, the 4G node wireless outgoing restriction constraint, the node storage capacity constraint, and the acyclic constraint based on potential energy variables corresponding to the set of wireless directed links based on the weighted sum target function, and construct a mixed integer linear programming model.

[0107] A transmission strategy generation module is configured to combine the field data calibration parameters of the target monitoring area, use a mixed integer programming solver to obtain the optimal solution of the mixed integer linear programming model, that is, the non-4G node next hop, link code rate and node storage capacity corresponding to the set of wireless directed links, and generate a low-cost multi-hop link transmission strategy.

[0108] Figure 2 The device of the embodiment shown can be used to perform the steps in the method embodiment shown in Figure 1 The implementation principle and technical effects are similar, and will not be repeated here.

[0109] An electronic device includes a memory and a processor, the memory storing a computer program, and when the processor runs the computer program stored in the memory, the processor performs the steps of the low-cost multi-hop link transmission method for a signal-free transmission pan-tilt head as described in any one of the above.

[0110] As Figure 3 shown in FIG. 1, which is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application. The electronic device 30 comprises a processor 31, a memory 32 and a computer program; wherein

[0111] The memory 32 is configured to store the computer program. The memory can also be a flash memory. The computer program can be an application program, a functional module or the like for implementing the above method.

[0112] The processor 31 is configured to execute the computer program stored in the memory to implement each step of the above method performed by the device. For details, please refer to the related description in the above method embodiment.

[0113] Optionally, the memory 32 can be independent or integrated with the processor 31.

[0114] When the memory 32 is independent of the processor 31, the device can further comprise:

[0115] A bus 33 is configured to connect the memory 32 and the processor 31.

[0116] A readable storage medium, wherein the readable storage medium stores a computer program, and the computer program is configured to be executed by a processor to implement the steps of the low-cost multi-hop link transmission method for a no-signal transmission gimbal according to any one of the above embodiments.

[0117] The readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transfer of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general or special purpose computer. For example, the readable storage medium can be coupled to the processor, so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). In addition, the ASIC can be located in a user equipment. Of course, the processor and the readable storage medium can also exist as discrete components in a communication device. The readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk and an optical data storage device, etc.

[0118] The present application also provides a program product including execution instructions stored in a readable storage medium. At least one processor of the device can read the execution instructions from the readable storage medium, and the at least one processor executes the execution instructions to enable the device to implement the method provided by the various embodiments described above.

[0119] In the embodiments of the above device, it should be understood that the processor can be a central processing unit (CPU for short), and can also be other general-purpose processors, digital signal processors (DSP for short), application specific integrated circuits (ASIC for short), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the present application can be directly embodied as hardware processor execution, or executed by a combination of hardware and software modules in the processor.

[0120] Through the introduction of the above embodiments, the present application provides a low-cost multi-hop link transmission method and system for a signal transmission-free pan-tilt head. All pan-tilt heads in a target monitoring area are abstracted as a node set, and a set of reachable wireless directed links is determined according to the distance between nodes and the wireless coverage radius. A weighted sum objective function is constructed to minimize the sum of the total network wireless transmission cost and node storage hardware cost corresponding to the set of wireless directed links. Based on the weighted sum objective function, a next-hop uniqueness constraint corresponding to the set of wireless directed links, a link flow selection consistency and upper bound constraint, a flow conservation and aggregation constraint, a 4G node wireless outgoing restriction constraint, a node storage capacity constraint, and a non-cyclic constraint based on potential energy variables are established. A mixed integer linear programming solver is constructed. The parameters are calibrated using the field data of the target monitoring area, and the mixed integer programming solver is used to obtain the optimal solution, i.e., the next hop of non-4G nodes corresponding to the set of wireless directed links, the link code rate, and the node storage capacity, to generate a low-cost multi-hop link transmission strategy. Thus, the only next hop of the 4G pan-tilt head can be accurately determined, and a non-cyclic convergence topology is formed to ensure that the image flow reaches the 4G node and reduces the transmission cost.

[0121] The application can accurately determine the only next hop for each 4G headless machine, combine the non-cyclic constraint based on potential energy variable, form a non-cyclic convergence topology, completely eliminate the loop forwarding risk, and strictly follow the wireless transmission distance and node storage upper limit constraint to ensure that the image flow of all 4G headless machines can be stably transmitted to the 4G node, solve the problems of link unreachable and node buffer overflow. The application based on the weighted and objective function integrates the wireless transmission cost and storage hardware cost into unified optimization, which can be flexibly adapted to operation demand by adjusting the weight, that is, the power supply is focused on reducing transmission energy consumption in a tight power supply scenario, and the budget is sensitive to the scene, which can preferentially control the storage cost, thereby realizing the joint minimization of the two types of costs in the whole network, and significantly reducing the deployment and operation cost. The application supports parameter calibration and mixed integer programming solution based on field data, and can dynamically update parameters and quickly re-optimize in the operation and maintenance stage according to link quality, node failure and the like, and can also improve the system robustness and fault resistance through expansion strategies such as load balancing, 4G node uplink flow limiting, standby next hop switching, and the like, to ensure the long-term stable and efficient operation of the monitoring business of the power transmission network in remote areas.

[0122] Finally, it should be pointed out that: the above embodiments are only used to illustrate the technical solutions of the application, and not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the application.

Claims

1. A low-cost multi-hop link transmission method for a signal-free pan-tilt-zoom (PTZ) camera, characterized in that, The method comprises: all pan-tilt cameras in a target monitoring area are abstracted as a node set, and a set of reachable wireless directed links is determined according to the distance between nodes and the wireless coverage radius; a weighted sum objective function is constructed by taking the sum of the whole network wireless transmission cost and the node storage hardware cost corresponding to the set of wireless directed links as the target for minimization; based on the weighted sum objective function, a next hop uniqueness constraint, a link flow selection consistency and upper bound constraint, a flow conservation and aggregation constraint, a 4G node wireless outgoing limit constraint, a node storage capacity constraint and a loop-free constraint based on a potential energy variable corresponding to the set of wireless directed links are established, and a mixed integer linear programming model is constructed; the optimal solution of the mixed integer linear programming model, that is, the next hop of the non-4G node, the link code rate and the node storage capacity corresponding to the set of wireless directed links, is obtained by using a mixed integer programming solver in combination with the field data calibration parameters of the target monitoring area, and a low-cost multi-hop link transmission strategy is generated.

2. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 1, wherein, The all pan-tilt cameras in the target monitoring area are abstracted as the node set, and the set of reachable wireless directed links is determined according to the distance between nodes and the wireless coverage radius, specifically comprising: all pan-tilt cameras in the target monitoring area are abstracted as a node set N, and the node set N is divided into a node set G with 4G signals and a node set U=N-G without 4G signals; For any node i∈U, any node j∈N, and i≠j, a directed link (i,j) from node i to node j is determined to belong to a set of reachable wireless directed links E if and only if the distance d ij between node i and node j is not more than the wireless coverage radius R of node i i ​ 3. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 1, wherein, The expression of the weighted sum objective function is as follows: minimize J = w Y *∑ (i,j)∈E c i,j *f i,j +w S *∑ i'∈N κ i' *B i' wherein minimize J represents a weighted sum objective function;∑ (i,j)∈E c i,j *f i,j represents a total network wireless transmission cost;∑ i∈N κ i *B i represents a node storage hardware cost;w Y , w S respectively represent the importance proportion of the total network wireless transmission cost and the node storage hardware cost in the weighted sum objective function, for uniformly weighing the total network wireless transmission cost and the node storage hardware cost;c i,j represents a unit data transmission cost of a directed link (i, j) from node i to node j, determined by a path loss model corresponding to a set of wireless directed links, and c i,j ≥ 0, wherein α i represents a cost scaling coefficient related to the transmission power of the wireless transmission device of node i, represents a loss distance between node i and node j, and γ represents a propagation path loss exponent, for reflecting the distance gain attenuation strength of the set of wireless directed links, and 2 ≤ γ ≤ 4;f i,j represents the aggregated traffic transmitted along the directed link (i, j) from node i to node j, and f i,j ≥ 0;κ i' represents a unit storage capacity cost of node i';B i' represents the actual configured storage capacity of node i', and B i' ≥ 0.

4. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 1, wherein, The next hop uniqueness constraint is as follows: For any node i∈U, satisfies ∑ j:(i,j)∈E x i,j =1, where x i,j represents a binary variable, x i,j =1 represents that the node i selects the node j as the only next hop, and x i,j =0 represents that the node i does not select the node j as the only next hop. The link flow selection consistency and upper bound constraint is as follows: For a directed link from node i to node j (i,j) E, satisfies 0 < f i,j ≤ T i * x i,j , where T i denotes the outgoing upper bound of node i, i.e., the sum of real-time image code rates of all nodes in the node set N, and T i = ∑ i'∈N s i' , s i' denotes the real-time image code rate of node i'.

5. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 1, wherein, The flow conservation and aggregation constraint is as follows: For any node i∈U, satisfies ∑ j:(i,j)∈E f i,j = s i +∑ k∈U:(k,i)∈E f k,i , where s i denotes the real-time image rate of node i; f k,i denotes the aggregated traffic transmitted along the directed link (k,i) from node k to node i. The 4G node wireless outgoing limit constraint is as follows: When constructing the set of wireless directed links E, only the following are defined and E does not contain G x N.

6. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 1, wherein, The node storage capacity constraint includes a minimum storage capacity constraint and a maximum storage capacity constraint; For any node i'∈N, the minimum storage capacity constraint is as follows: B i' ≥H*(s i' +∑ k∈U:(k,i')∈E f k,i' ) where H denotes the real-time service buffer duration, and V min = H * ξ, where V min denotes the minimum resident cache capacity, ξ denotes the link code rate; (k, i') denotes a directed link from node k to node i'; f k,i' denotes the aggregated traffic transmitted along the directed link (k, i') from node k to node i'. The maximum storage capacity constraint is as follows: wherein, represents the maximum installable storage capacity of node i'.

7. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 1, wherein, The loop-free constraint based on the potential energy variable is as follows: For a directed link from node i to node j (i, j) E, satisfies p i ≤ p j - 1 + M * (1 - x i,j ), where p i , p j respectively represent the potential energy variables of nodes i, j; M represents a constant, M = |U| + 1, |U| represents the total number of nodes in the set of nodes without 4G signals. At the same time, for any node g G, fix p g = 0; for any node i U, constraint 1 ≤ p i ≤ |U|.

8. The low-cost multi-hop link transmission method for a signal-free pan-tilt according to claim 7, wherein, For any node g ∈ G, set the uplink flow upper bound of node g as Set the uplink flow constraint for node g as: Where, ∑ k∈U f k,g represents the uplink flow converged to node g through multi-hop links; f k,g represents the aggregated flow transmitted along the directed link (k, g) from node k to node g. For any node g1∈G, if where, denotes the uplink traffic aggregated to node g1 through multi-hop links, denotes the aggregated traffic transmitted along the directed link (k, g1) from node k to node g1; denotes the uplink traffic upper bound of node g1; denotes the uplink traffic is close to the threshold, then automatically switch part of the original next hop of node k pointing to node g1 to other node g2 with sufficient uplink traffic, that is, adjust the binary variable and 9. A low-cost multi-hop link transmission system for a signal-free pan-tilt, applied to the low-cost multi-hop link transmission method for a signal-free pan-tilt according to any one of claims 1 to 8, characterized in that, The system comprises: a link set acquisition module configured to abstract all pan-tilt cameras in a target monitoring area as a node set, and determine a set of reachable wireless directed links according to the distance between nodes and the wireless coverage radius; an objective function construction module configured to construct a weighted sum objective function by taking the sum of the whole network wireless transmission cost and the node storage hardware cost corresponding to the set of wireless directed links as the target for minimization; a constraint condition establishment module configured to establish a next hop uniqueness constraint, a link flow selection consistency and upper bound constraint, a flow conservation and aggregation constraint, a 4G node wireless outgoing limit constraint, a node storage capacity constraint and a loop-free constraint based on a potential energy variable corresponding to the set of wireless directed links based on the weighted sum objective function, and construct a mixed integer linear programming model; a transmission strategy generation module configured to obtain the optimal solution of the mixed integer linear programming model, that is, the next hop of the non-4G node, the link code rate and the node storage capacity corresponding to the set of wireless directed links, by using a mixed integer programming solver in combination with the field data calibration parameters of the target monitoring area, and generate a low-cost multi-hop link transmission strategy.

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