CN114585043A - Routing method, device, computer equipment and storage medium - Google Patents

Routing method, device, computer equipment and storage medium Download PDF

Info

Publication number
CN114585043A
CN114585043A CN202210301085.1A CN202210301085A CN114585043A CN 114585043 A CN114585043 A CN 114585043A CN 202210301085 A CN202210301085 A CN 202210301085A CN 114585043 A CN114585043 A CN 114585043A
Authority
CN
China
Prior art keywords
time slot
routing
target
transmission
energy
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202210301085.1A
Other languages
Chinese (zh)
Other versions
CN114585043B (en
Inventor
于秦
周鸿臻
胡杰
杨鲲
刘双美
麻泽龙
卢鑫
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
HYDRAULIC SCIENCE RESEARCH INSTITUTE OF SICHUAN PROVINCE
University of Electronic Science and Technology of China
Yangtze River Delta Research Institute of UESTC Huzhou
Original Assignee
HYDRAULIC SCIENCE RESEARCH INSTITUTE OF SICHUAN PROVINCE
University of Electronic Science and Technology of China
Yangtze River Delta Research Institute of UESTC Huzhou
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by HYDRAULIC SCIENCE RESEARCH INSTITUTE OF SICHUAN PROVINCE, University of Electronic Science and Technology of China, Yangtze River Delta Research Institute of UESTC Huzhou filed Critical HYDRAULIC SCIENCE RESEARCH INSTITUTE OF SICHUAN PROVINCE
Priority to CN202210301085.1A priority Critical patent/CN114585043B/en
Publication of CN114585043A publication Critical patent/CN114585043A/en
Application granted granted Critical
Publication of CN114585043B publication Critical patent/CN114585043B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention provides a routing method, a routing device, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring transmission requirements of all wireless sensor nodes in a target network model; generating a first routing link set and a second routing link set according to the transmission requirements of all wireless sensor nodes; generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set; and resolving a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint. The invention solves the problem of the energy efficiency of the sensor in the energy-counting integrated network in the prior art, and improves the survival time of the sensor while ensuring the quality of network communication service, thereby improving the data energy transmission performance of the network.

Description

Routing method, device, computer equipment and storage medium
Technical Field
The present invention relates to the field of routing technologies, and in particular, to a routing method and apparatus, a computer device, and a storage medium.
Background
The Energy Harvesting (EH) technology has a great development prospect because it can provide stable Energy for Energy-limited networks such as wireless sensor networks and the like and prolong the life cycle of the networks. The energy sources of the energy collection technology include not only most natural energy sources of the surrounding environment, such as solar energy, light energy, wind energy, heat energy, chemical energy, etc., but also received surrounding wireless signals can be converted into electric energy, such as artificially acquired Radio Frequency (RF) signals. And energy collection based on RF signals is a research hotspot because it can be protected from the weather environment and provide stable energy.
With the rapid development of wireless network technologies and the dramatic increase in the number of mobile devices, User Equipment (UEs) such as cell phones and wearable devices generate a huge amount of data. How to wirelessly power these devices becomes a challenging problem. The Wireless Energy Transfer (WET) technology can collect external RF signals and convert the external RF signals into Direct Current (DC) circuits through circuit design for Wireless Information Transfer (WIT), thereby dealing with the Energy bottleneck problem of some Energy-limited and unstable networks. Data and energy integrated communication networks (networks) are a new type of network that can realize cooperative transmission of Data and energy. In the digital integrated network, energy and data can be transmitted simultaneously, and energy signals can be transmitted to energy-limited equipment to provide energy for information transmission, so that the service life of the network is prolonged. In a typical multi-user integrated network, a base station provides energy to users through a downlink WET, and the users perform uplink WET through the energy.
The fact that energy transmission is added to the digital energy integrated network on the basis of information transmission means that under the condition that original resources are fixed and unchanged, the information transmission needs to give way to partial resources for energy transmission, a wireless sensor network is a typical energy-limited network, energy is provided by a battery for a sensor, and energy efficiency needs to be considered in a routing algorithm. However, the traditional routing method of the wireless communication network does not consider the energy efficiency of the sensor, and cannot be applied to a digital energy integrated network; therefore, it is necessary to develop a routing method that can be applied to a digital-to-energy integrated network.
Disclosure of Invention
Aiming at the defects in the prior art, the routing method, the routing device, the computer equipment and the storage medium solve the problem that the energy efficiency of the sensor in the energy-counting integrated network is not considered in the prior art, ensure the quality of network communication service, and improve the survival time of the sensor, thereby improving the data energy transmission performance of the network.
In a first aspect, the present invention provides a routing method, where the method includes: acquiring transmission requirements of all wireless sensor nodes in a target network model, wherein the target network model comprises a wireless mesh network, a wireless sensor network and sink nodes; generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all wireless sensor nodes; generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set; and resolving a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target allocation time slot and the second target allocation time slot to obtain a current optimal routing scheme.
Optionally, before acquiring transmission requirements of all wireless sensor nodes in the target network model, the method further includes: constructing an initial network model integrating data and energy; and determining a transmission rule of the initial network model to obtain a target network model.
Optionally, the first routing link set is represented by a matrix: a ═ L | × MSThe second set of routing links is configured to,
expressed in a matrix as: b ═ L | × MR(ii) a Where | L | represents the number of all feasible links, MSRepresenting the number of sets of feasible routing links, MRRepresenting the number of sets of feasible routing links.
Optionally, the formula of the first slot constraint is as follows:
Figure BDA0003565664330000021
Figure BDA0003565664330000022
wherein A iskThe k-th link is represented by,
Figure BDA0003565664330000023
the time slot of the kth link is represented, Ds represents the transmission duration of the kth link, and Ts represents the total duration of all the time slots;
the formula expression of the second time slot constraint is as follows:
Figure BDA0003565664330000024
Figure BDA0003565664330000025
wherein the content of the first and second substances,
Figure BDA0003565664330000026
representing a data stream flThe length of the transmission time of (c),
Figure BDA0003565664330000027
time slot, T, representing the k linkRIndicating the total duration of all time slots in the transmission phase of the routing network.
Optionally, resolving a first target allocation timeslot and a second target allocation timeslot according to the first timeslot constraint and the second timeslot constraint includes: acquiring a target sensor node with the least current energy in a target network model; generating an objective optimization function according to the current energy of the target sensor node, the first time slot constraint and the second time slot constraint; and resolving the target optimization function to obtain the first target allocation time slot and the second target allocation time slot.
Optionally, the formula expression of the objective optimization function is:
Figure BDA0003565664330000031
Figure BDA0003565664330000032
Figure BDA0003565664330000033
Figure BDA0003565664330000034
wherein the content of the first and second substances,
Figure BDA0003565664330000035
and
Figure BDA0003565664330000036
are combined into
Figure BDA0003565664330000037
Optionally, the formula for calculating the current energy of the wireless sensor node is as follows:
Figure BDA0003565664330000038
wherein the content of the first and second substances,
Figure BDA0003565664330000039
representative node siThe current energy of the energy source is,
Figure BDA00035656643300000310
representing the remaining energy of the node after the last round of superframe transmission,
Figure BDA00035656643300000311
representing the energy harvested by the node in the superframe of the current round,
Figure BDA00035656643300000312
represents the energy consumed by the node in the superframe of the current round, wherein the energy harvested by the node
Figure BDA00035656643300000313
Can be expressed as:
Figure BDA00035656643300000314
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA00035656643300000315
representing a sensor node sjThe energy can be obtained by an energy harvesting radio frequency signal, beta represents the conversion efficiency of energy harvesting, hijRepresenting the parameters of the channel between the nodes,
Figure BDA00035656643300000316
representative routing node riThe transmit power of (a);
the energy consumption of the sensor nodes is:
Figure BDA00035656643300000317
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA00035656643300000318
representing the energy consumption of the communication,
Figure BDA00035656643300000319
the energy consumption of sensing and calculation is represented,
Figure BDA00035656643300000320
the formula expression of (1) is:
Figure BDA00035656643300000321
wherein the content of the first and second substances,
Figure BDA00035656643300000322
and
Figure BDA00035656643300000323
respectively representing the transmit power and the receive power of the sensor node.
In a second aspect, the present invention provides a routing device, comprising: the system comprises a transmission demand acquisition module, a transmission demand acquisition module and a transmission demand acquisition module, wherein the transmission demand acquisition module is used for acquiring the transmission demands of all wireless sensor nodes in a target network model, and the target network model comprises a wireless mesh network, a wireless sensor network and a sink node; the link set generation module is used for generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all the wireless sensor nodes; a time slot constraint generating module, configured to generate a first time slot constraint of each wireless sensor in a sensor network transmission phase according to the first routing link set, and generate a second time slot constraint of each data stream in a wireless mesh network transmission phase according to the second routing link set; and the target distribution time slot calculation module is used for calculating a first target distribution time slot and a second target distribution time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are combined with the first target distribution time slot and the second target distribution time slot respectively to obtain a current optimal routing scheme.
In a third aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program: acquiring transmission requirements of all wireless sensor nodes in a target network model, wherein the target network model comprises a wireless mesh network, a wireless sensor network and sink nodes; generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all wireless sensor nodes; generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set; and resolving a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target allocation time slot and the second target allocation time slot to obtain a current optimal routing scheme.
In a fourth aspect, the invention provides a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: acquiring transmission requirements of all wireless sensor nodes in a target network model, wherein the target network model comprises a wireless mesh network, a wireless sensor network and sink nodes; generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all wireless sensor nodes; generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set; and resolving a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target allocation time slot and the second target allocation time slot to obtain a current optimal routing scheme.
Compared with the prior art, the invention has the following beneficial effects:
generating routing link sets of different levels according to transmission requirements of all wireless sensor nodes in a target network model, performing optimal time slot resource allocation according to time slot constraints in the current routing link set, and combining the routing link sets with the optimal time slot resources to obtain a current optimal routing scheme; the invention uses the mode of simultaneous transmission of data and energy during routing, can controllably improve the energy performance of the sensor node, jointly optimizes the routing, transmission set generation and time slot allocation of the network by researching the combined algorithm of the data and energy routing in the two-layer data and energy integrated network combining the wireless mesh network and the wireless sensor network, ensures the quality of network communication service, and improves the survival time of the sensor, thereby improving the data energy transmission performance of the network.
Drawings
Fig. 1 is a schematic flow chart illustrating a routing method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a system model of a two-tier energy-integrated network according to an embodiment of the present invention;
fig. 3 is a schematic specific flowchart of step S104 in fig. 1 according to an embodiment of the present invention;
fig. 4 is a schematic flowchart of another routing method according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a routing device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In a first aspect, the present invention provides a routing method, which specifically includes the following embodiments:
fig. 1 is a schematic flow chart of a routing method according to an embodiment of the present invention, and as shown in fig. 1, the routing method specifically includes the following steps:
step S101, acquiring transmission requirements of all wireless sensor nodes in the target network model.
In this embodiment, before acquiring transmission requirements of all wireless sensor nodes in the target network model, the method further includes: constructing an initial network model integrating data and energy; and determining a transmission rule of the initial network model to obtain a target network model.
In this embodiment, the target network model includes a wireless mesh network, a wireless sensor network, and a sink node.
It should be noted that the initial network model of the numerical integration constructed in this embodiment is divided into two layers, as shown in fig. 2, each of which includes KRWireless Mesh Network (Wireless Mesh Network) of routing nodes and Network system comprising the sameSThe system comprises a Wireless Sensor Network (WSN) of Sensor nodes, and optionally a routing node as a sink node, wherein data of all the Sensor nodes are transmitted to the sink node through the Wireless mesh network, and the sink node also transmits a control command to the Sensor nodes through the Wireless mesh network. The entire network is represented by graph G (N, L), where N ═ NR∪NSRepresenting a set of routing and sensor nodes, L ═ LR∪LSRepresenting the set of links between routing nodes and the links between a sensor and its nearest routing node. The nodes are single-antenna devices, the routing node has stable power supply, and the sensor node has a small rechargeable battery and can acquire energy carried by radio-frequency signals sent by the nodes within a certain range through energy collection.
Further, transmission rules of the two types of nodes and data flow characteristics in the network are defined for the initial network model, and therefore the target network model is obtained. The routing nodes can communicate with the routing nodes in the communication range, the sensor nodes only communicate with the nearest routing nodes in the communication range, and then the routing network transmits the data stream to the sink nodes. The data flow in the network is not newly generated and is not dead in the transfer process, the data flow can be generated or destroyed only by a source node as a sender and a target node as a receiver in the network, and the node responsible for forwarding in each data flow does not influence the data flow.
In this embodiment, the superframe format is defined according to the system characteristics of the target network model, and the superframe is divided into three phases:
the first stage is a control command transmission stage: firstly, the routing node wakes up surrounding sensor nodes at this stage by sending beacon frames, the network gathers and acquires the transmission requirements of all the sensor nodes, and routing path selection and resource allocation in a subsequent algorithm are performed at this stage by using the collected information.
The second stage is a sensor network transmission stage: at this stage, the sensor node information with transmission requirements is transmitted to the nearest routing node, the routing node collects the sensor node information to the sink node through the wireless mesh network, and meanwhile, a corresponding control command is replied from the sink node.
The third phase is a wireless mesh network transmission phase: in the stage, transmission among routing nodes, namely original data streams in the wireless mesh network, is carried out, and the survival time of the sensor nodes in the network is prolonged through routing and time slot allocation on the basis that the service quality of the network is required to be ensured.
Step S102, according to the transmission requirements of all wireless sensor nodes, generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from each data flow from a source node to a sink node in the wireless mesh network.
In this embodiment, in the transmission stage of the sensor network, a sensor node with a transmission requirement communicates with a sink node through the wireless mesh network, and at this time, a shortest path algorithm Dijkstra is used to generate a first routing link set from each sensor to the sink node. The Dijkstra algorithm is mainly characterized in that a greedy algorithm strategy is adopted from a starting point, and adjacent nodes of vertexes which are nearest to the starting point and have not been visited are traversed each time until the nodes are expanded to an end point. The dimension of the first routing link set is | L | × MSWhere | L | represents the number of all feasible links, MSRepresenting the number of sets of feasible routing links. Each cell in the matrix A is 0 or 1, and represents the set of the routing linksAnd whether the link is active or not is converged.
During the transmission phase of the wireless mesh network, data streams in the wireless mesh network will communicate in the routing nodes, at this time, a breadth first algorithm is used to systematically expand and check all nodes in the graph, and all routing link sets with hop numbers smaller than a fixed value are searched for, so as to generate all second routing link sets which satisfy the conditions from the source node to the destination node for each data stream. The limitation on the hop count of the routing link is to reduce the end-to-end delay in the network service and improve the network service quality. The dimension of the second routing link set is L multiplied by MRMatrix B of (1) represents a similar MRRepresenting the number of sets of feasible routing links. Each cell in the matrix B is 0 or 1, respectively, to indicate whether the link is active in the routing link set. It should be noted that B in B isjIs a mapping of F ∈ F. Flow f may correspond to one or more columns of B, which are grouped together
Figure BDA0003565664330000071
And (4) showing. F (B)j) Is represented by BjWhether or not fiMapping of (2).
Step S103, generating a first time slot constraint of each wireless sensor in the transmission stage of the sensor network according to the first routing link set, and generating a second time slot constraint of each data stream in the transmission stage of the wireless mesh network according to the second routing link set.
It should be noted that, for the transmission phase of the sensor network, first the time allocated to each routing link set in the phase
Figure BDA0003565664330000072
The following first slot constraint needs to be satisfied:
Figure BDA0003565664330000073
Figure BDA0003565664330000074
wherein A iskIndicating the k-th link in the wireless sensor network,
Figure BDA0003565664330000075
the time slot of the kth link in the wireless sensor network is represented, Ds represents the transmission duration of the kth link in the wireless sensor network, and Ts represents the total duration of all time slots in the transmission stage of the sensor network; for each sensor node, only one transmission link set is generated between the sensor node and the sink node, so that only the transmission link set A is neededkTime slot of
Figure BDA0003565664330000076
Satisfying the transmission requirements D of the sensor nodesSAnd (4) finishing. Meanwhile, for the transmission stage of the sensor network, the total duration of all time slot allocations of the transmission stage cannot exceed TSThe limitation of (2).
In this embodiment, the wireless mesh network transmission phase is a phase in which the routing nodes communicate with each other according to the target network model. At this stage, since there is no information transmission between the routing node and the sensor node, the ith data flow f for this stagelThe following second slot constraint needs to be satisfied:
Figure BDA0003565664330000081
Figure BDA0003565664330000082
wherein the content of the first and second substances,
Figure BDA0003565664330000083
representing a data stream flThe length of the transmission time of (c),
Figure BDA0003565664330000084
time slot, B, representing the k link in a wireless mesh networkmMeans of noThe mth link in the wire mesh network,
Figure BDA0003565664330000085
time slot, T, indicating the mth link in a wireless mesh networkRRepresenting the total time length of all time slots in the transmission phase of the routing network;
Figure BDA0003565664330000086
for a data stream flIs required for transmission, i.e. corresponds to flTransmission set of
Figure BDA0003565664330000087
The sum of the allocated time slots needs to be greater than or equal to its transmission requirement, otherwise flow f cannot be guaranteed in that time slotlThe link channel throughput in the corresponding transmission set meets the requirements. Meanwhile, for the transmission stage of the routing network, the total duration of all time slot allocations of the routing network cannot exceed TRThe limit of (2).
And step S104, calculating a first target distribution time slot and a second target distribution time slot according to the first time slot constraint and the second time slot constraint, and combining the first routing link set and the second routing link set with the first target distribution time slot and the second target distribution time slot respectively to obtain a current optimal routing scheme.
In this embodiment, as shown in fig. 3, the calculating the first target allocation timeslot and the second target allocation timeslot according to the first timeslot constraint and the second timeslot constraint specifically includes the following steps:
step S201, acquiring a target sensor node with the least current energy in a target network model;
step S202, generating an objective optimization function according to the current energy of the target sensor node, the first time slot constraint and the second time slot constraint;
step S203, resolving the objective optimization function to obtain the first objective allocation timeslot and the second objective allocation timeslot.
It should be noted that, in order to maximize the lifetime of the sensor nodes, an optimization goal is defined to maximize the energy level of the node with the least remaining energy in the whole sensor nodes, which is expressed by the following formula:
Figure BDA0003565664330000088
wherein the variable to be optimized is the time slot allocation T for the transmission setSAnd TR. Combining the formulas of the first time slot constraint and the second time slot constraint, the generated objective optimization function can be expressed as:
Figure BDA0003565664330000091
Figure BDA0003565664330000092
Figure BDA0003565664330000093
Figure BDA0003565664330000094
wherein the limitation on the total length of the time slots is derived from the limitation on the total length of the superframe, thereby limiting the time slots
Figure BDA0003565664330000095
And
Figure BDA0003565664330000096
are combined into
Figure BDA0003565664330000097
In this embodiment, the original optimization problem is a convex problem, and the optimization objective can be regarded as taking point by point
Figure BDA0003565664330000098
So the objective optimization function can be converted to the following form:
Figure BDA0003565664330000099
Figure BDA00035656643300000910
Figure BDA00035656643300000911
Figure BDA00035656643300000912
Figure BDA00035656643300000913
wherein E represents the minimum value of the residual energy of all the sensor nodes, and is the equivalent form of the original optimization problem. Its lagrange function is:
Figure BDA00035656643300000914
wherein
Figure BDA00035656643300000915
Is a lagrange multiplier, and thus its KKT condition:
Figure BDA00035656643300000916
Figure BDA00035656643300000917
Figure BDA00035656643300000918
λ*≠0
μ*≥0
wherein, thetaS,θRIs 0 or 1, represents whether the corresponding time slot is activated or not, is based on
Figure BDA0003565664330000101
The conditions in the calculation formula are abstracted. By the above formula, λ at the time of optimal slot allocation can be obtained*,μ*. At this time, into*,μ*To the following conditions:
Figure BDA0003565664330000102
Figure BDA0003565664330000103
Figure BDA0003565664330000104
the optimal time slot allocation T can be foundS*,TR*Wherein the optimal slot allocation TS*,TR*And respectively allocating time slots to the first target and the second target.
It is further noted that the optimal time slot allocation T is obtained according to the aboveS*,TR*The first routing link set and the second routing link set may be respectively combined with the first target allocation timeslot and the second target allocation timeslot to obtain a current optimal routing scheme.
In the transmission stage of the wireless sensor network, the network only generates a routing link set to the sink node for each transmitter node, and the route set is generated according to the timeSlot allocation TS*And corresponding time slot resources are sequentially allocated to the routing paths corresponding to each routing link set, so that the energy performance of the network can be improved on the basis of ensuring the transmission requirements of all the sensors at this stage.
During the transmission phase of the wireless mesh network, the network generates a plurality of routing link sets for transmission demands among each routing node, and each routing link set corresponds to one routing path. At this time, the original data stream is divided into several sub-data streams, and the sub-data stream size and the optimal time slot allocation TR*Is in direct proportion. And transmitting the sub-data flow from the routing source node to the routing destination node in the allocated time slot through the corresponding routing path. The transmission requirement of the routing network is guaranteed at this stage, and under the condition that the influence on the service quality of the network is relatively small, the energy performance of the network is greatly improved, so that the survival time of all sensors is prolonged.
Compared with the prior art, the invention has the following beneficial effects:
generating routing link sets of different levels according to transmission requirements of all wireless sensor nodes in a target network model, performing optimal time slot resource allocation according to time slot constraints in the current routing link set, and combining the routing link sets with the optimal time slot resources to obtain a current optimal routing scheme; the invention uses the mode of simultaneous transmission of data and energy during routing, can controllably improve the energy performance of the sensor node, jointly optimizes the routing, transmission set generation and time slot allocation of the network by researching the combined algorithm of the data and energy routing in the two-layer data and energy integrated network combining the wireless mesh network and the wireless sensor network, ensures the quality of network communication service, and improves the survival time of the sensor, thereby improving the data energy transmission performance of the network.
In this embodiment, the method further includes: and calculating the energy consumption of the sensor nodes and the energy obtained by energy collection. For a sensor node in a network, defining its energy level may be represented by the following formula:
Figure BDA0003565664330000111
wherein
Figure BDA0003565664330000112
Representative node siThe current energy of the electric motor (c),
Figure BDA0003565664330000113
representing the remaining energy of the node after the last round of superframe transmission,
Figure BDA0003565664330000114
representing the energy harvested by the node in the superframe of the current round,
Figure BDA0003565664330000115
representing the energy consumed by the node in the superframe of the current round. Wherein the energy harvested at the nodes
Figure BDA0003565664330000116
Can be expressed as:
Figure BDA0003565664330000117
wherein the content of the first and second substances,
Figure BDA0003565664330000118
representing a sensor node sjThe energy can be obtained by an energy harvesting radio frequency signal, beta represents the conversion efficiency of energy harvesting, hijRepresenting the parameters of the channel between the nodes,
Figure BDA0003565664330000119
representative routing node riA transmission power ofkl1 represents the unit in the k-th row and column of matrix A is active, lkRepresenting the network link corresponding to the k-th row of matrix A, bkm1 represents the active state of the cells in the k-th row and m-th column of matrix B, lkRepresenting the network link corresponding to the k-th row corresponding to matrix B,
Figure BDA00035656643300001110
and
Figure BDA00035656643300001111
representing the slot assignments for matrix a and matrix B, respectively.
Energy consumption of sensor nodes
Figure BDA00035656643300001112
It is mainly composed of communication, sensing, and computation. Among the three, the energy consumed by communication is much greater than sensing and computation. Thus, the energy consumption is defined as:
Figure BDA00035656643300001113
wherein the content of the first and second substances,
Figure BDA00035656643300001114
representing the energy consumption of the communication,
Figure BDA00035656643300001115
indicating the energy consumption of sensing and calculation. Further, due to
Figure BDA00035656643300001116
Smaller, it is reduced to a constant value. While
Figure BDA00035656643300001117
Can be expressed as:
Figure BDA0003565664330000121
wherein the content of the first and second substances,
Figure BDA0003565664330000122
and
Figure BDA0003565664330000123
respectively representing the transmit power and the receive power of the sensor node.
Fig. 4 is a schematic flow chart of another routing method according to an embodiment of the present invention, and as shown in fig. 4, the routing method specifically includes the following steps:
s1, determining a network model of the system and distributing a transmission protocol for the network model;
s2, defining a superframe format according to system characteristics, and dividing the superframe into three stages;
s3, generating a route link set according to the transmission requirement, and distributing into a corresponding superframe stage;
s4, solving the energy consumption of the sensor node and the energy obtained by energy collection;
s5, defining an optimization target as the maximum survival time of the sensor node, and obtaining an optimization target expression and the constraint thereof;
s6, solving the optimal transmission set time slot allocation according to the optimization target expression and the constraint thereof;
and S7, generating a routing scheme according to the optimal transmission set time slot allocation.
Further, step S1 specifically includes the following sub-steps:
s11, the Wireless digital energy and transmission Network model is assumed to be divided into two layers, namely a Wireless Mesh Network (Wireless Mesh Network) containing routing nodes and a Wireless Sensor Network (WSN) containing Sensor nodes. Determining the number of two types of nodes and the number of sink nodes and node antennas;
and S12, defining the transmission rules of the two types of nodes and the data flow characteristics in the network.
Further, step S2 specifically includes the following sub-steps:
s21, dividing the superframe into three stages, wherein the first stage is a control command transmission stage, and acquiring the transmission requirements of the whole number of the integrated networks in the period and generating routing path selection and resource allocation through a routing algorithm;
s22, the second stage is a sensor network transmission stage, and sensor node information with transmission requirements is transmitted to the sink node at the stage;
s23, the third phase is a wireless mesh network transmission phase, in which transmission between routing nodes is performed.
Further, step S3 specifically includes the following sub-steps:
s31, generating a sensor network routing link set by using a shortest path algorithm;
and S32, generating a wireless mesh network transmission phase routing link set by using a breadth first algorithm.
Further, step S5 specifically includes the following sub-steps:
s51, generating time slot distribution constraint of the sensor network transmission stage;
s52, generating time slot constraint of wireless mesh network transmission phase;
and S53, defining an optimization target to maximize the survival time of the sensor node to obtain an optimization problem.
The beneficial effects of the invention are: the method comprises three parts of network routing link combination generation, time slot resource allocation and routing scheme generation, adopts a breadth-first algorithm and a shortest path algorithm in a graph theory to jointly generate a network routing link set, and jointly optimizes the time slot resource allocation of different stages of a network superframe through a convex optimization algorithm, thereby ensuring the network communication service quality and improving the survival time of a sensor.
In a second aspect, the present invention provides a routing device, as shown in fig. 5, the device includes:
a transmission requirement obtaining module 110, configured to obtain transmission requirements of all wireless sensor nodes in a target network model, where the target network model includes a wireless mesh network, a wireless sensor network, and a sink node;
a link set generating module 120, configured to generate, according to transmission requirements of all wireless sensor nodes, a first routing link set from each wireless sensor to the wireless mesh network, and a second routing link set from a source node to a sink node for each data flow in the wireless mesh network;
a time slot constraint generating module 130, configured to generate a first time slot constraint of each wireless sensor in a sensor network transmission phase according to the first routing link set, and generate a second time slot constraint of each data stream in a wireless mesh network transmission phase according to the second routing link set;
and the target allocation time slot calculation module 140 is configured to calculate a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target allocation time slot and the second target allocation time slot, and a current optimal routing scheme is obtained.
In a third aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program: acquiring transmission requirements of all wireless sensor nodes in a target network model, wherein the target network model comprises a wireless mesh network, a wireless sensor network and sink nodes; generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all wireless sensor nodes; generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set; and resolving a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target allocation time slot and the second target allocation time slot to obtain a current optimal routing scheme.
In a fourth aspect, the present invention provides a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of: acquiring transmission requirements of all wireless sensor nodes in a target network model, wherein the target network model comprises a wireless mesh network, a wireless sensor network and sink nodes; generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all wireless sensor nodes; generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set; and resolving a first target allocation time slot and a second target allocation time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target allocation time slot and the second target allocation time slot to obtain a current optimal routing scheme.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

Claims (10)

1. A routing method, the method comprising:
acquiring transmission requirements of all wireless sensor nodes in a target network model, wherein the target network model comprises a wireless mesh network, a wireless sensor network and sink nodes;
generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all wireless sensor nodes;
generating a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generating a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set;
and resolving a first target distribution time slot and a second target distribution time slot according to the first time slot constraint and the second time slot constraint, and combining the first routing link set and the second routing link set with the first target distribution time slot and the second target distribution time slot respectively to obtain a current optimal routing scheme.
2. The routing method of claim 1, wherein prior to obtaining transmission requirements of all wireless sensor nodes in a target network model, the method further comprises:
constructing an initial network model integrating data and energy;
and determining a transmission rule of the initial network model to obtain a target network model.
3. The routing method of claim 1, wherein the first set of routing links is represented by a matrix of: a ═ L | × MSAnd the second route link set matrix is expressed as: b ═ L | × MR；
Where | L | represents the number of all feasible links, MSRepresenting the number of sets of feasible routing links, MRRepresenting the number of sets of feasible routing links.
4. The routing method of claim 1, wherein the first slot constraint is formulated as:
Figure FDA0003565664320000011
Figure FDA0003565664320000012
wherein, AkThe k-th link is represented by,
Figure FDA0003565664320000013
the time slot of the kth link is represented, Ds represents the transmission duration of the kth link, and Ts represents the total duration of all the time slots;
the formula expression of the second time slot constraint is as follows:
Figure FDA0003565664320000014
Figure FDA0003565664320000021
wherein the content of the first and second substances,
Figure FDA0003565664320000022
representing a data stream flThe length of the transmission time of (c),
Figure FDA0003565664320000023
time slot, T, representing the k linkRIndicating the total duration of all time slots in the transmission phase of the routing network.
5. The routing method of claim 1, wherein resolving a first target assigned time slot and a second target assigned time slot based on the first time slot constraint and the second time slot constraint comprises:
acquiring a target sensor node with the least current energy in a target network model;
generating an objective optimization function according to the current energy of the target sensor node, the first time slot constraint and the second time slot constraint;
and resolving the target optimization function to obtain the first target allocation time slot and the second target allocation time slot.
6. The routing method of claim 5, wherein the objective optimization function has a formula expression of:
Figure FDA0003565664320000024
Figure FDA0003565664320000025
Figure FDA0003565664320000026
Figure FDA0003565664320000027
wherein the content of the first and second substances,
Figure FDA0003565664320000028
and
Figure FDA0003565664320000029
are combined into
Figure FDA00035656643200000210
7. The routing method of claim 5, wherein the formula for calculating the current energy of the wireless sensor node is:
Figure FDA00035656643200000211
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA00035656643200000212
representative node siThe current energy of the energy source is,
Figure FDA00035656643200000213
representing the remaining energy of the node after the last round of superframe transmission,
Figure FDA00035656643200000214
representing the energy harvested by the node in the superframe of the current round,
Figure FDA00035656643200000215
represents the energy consumed by the node in the superframe of the current round, wherein the energy harvested by the node
Figure FDA00035656643200000216
Can be expressed as:
Figure FDA00035656643200000217
wherein the content of the first and second substances,
Figure FDA00035656643200000218
representing a sensor node sjA set of routing nodes that can obtain energy from an energy harvesting radio frequency signal, beta representing the conversion efficiency of energy harvesting, hijRepresenting the parameters of the channel between the nodes,
Figure FDA00035656643200000219
representative routing node riThe transmit power of (a);
the energy consumption of the sensor nodes is:
Figure FDA0003565664320000031
wherein the content of the first and second substances,
Figure FDA0003565664320000032
representing the energy consumption of the communication,
Figure FDA0003565664320000033
the energy consumption of sensing and calculation is represented,
Figure FDA0003565664320000034
the formula expression of (1) is:
Figure FDA0003565664320000035
wherein the content of the first and second substances,
Figure FDA0003565664320000036
and
Figure FDA0003565664320000037
respectively representing the transmit power and the receive power of the sensor node.
8. A routing apparatus, the apparatus comprising:
the system comprises a transmission demand acquisition module, a transmission demand acquisition module and a transmission demand acquisition module, wherein the transmission demand acquisition module is used for acquiring the transmission demands of all wireless sensor nodes in a target network model, and the target network model comprises a wireless mesh network, a wireless sensor network and a sink node;
the link set generation module is used for generating a first routing link set from each wireless sensor to the wireless mesh network and a second routing link set from a source node to a sink node of each data stream in the wireless mesh network according to the transmission requirements of all the wireless sensor nodes;
a time slot constraint generating module, configured to generate a first time slot constraint of each wireless sensor in a sensor network transmission stage according to the first routing link set, and generate a second time slot constraint of each data stream in a wireless mesh network transmission stage according to the second routing link set;
and the target distribution time slot resolving module is used for resolving a first target distribution time slot and a second target distribution time slot according to the first time slot constraint and the second time slot constraint, so that the first routing link set and the second routing link set are respectively combined with the first target distribution time slot and the second target distribution time slot to obtain a current optimal routing scheme.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented by the processor when executing the computer program.
10. A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
CN202210301085.1A 2022-03-25 2022-03-25 Routing method, device, computer equipment and storage medium Active CN114585043B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210301085.1A CN114585043B (en) 2022-03-25 2022-03-25 Routing method, device, computer equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210301085.1A CN114585043B (en) 2022-03-25 2022-03-25 Routing method, device, computer equipment and storage medium

Publications (2)

Publication Number Publication Date
CN114585043A true CN114585043A (en) 2022-06-03
CN114585043B CN114585043B (en) 2023-07-21

Family

ID=81777025

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210301085.1A Active CN114585043B (en) 2022-03-25 2022-03-25 Routing method, device, computer equipment and storage medium

Country Status (1)

Country Link
CN (1) CN114585043B (en)

Citations (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388793A (en) * 2007-08-31 2009-03-18 费舍-柔斯芒特系统股份有限公司 Configuring and optimizing a wireless mesh network
CN101835277A (en) * 2010-02-09 2010-09-15 重庆理工大学 Wireless sensor network topology control method based on LEACH-ANT algorithm
CN102065575A (en) * 2009-11-11 2011-05-18 中国科学院沈阳自动化研究所 Method for constructing mesh and star hybrid topological wireless sensor network based on IEEE 802.15.4
CN103281746A (en) * 2013-06-03 2013-09-04 南昌大学 Wireless sensing network routing method of quotient topology energy hierarchical dynamic programming
EP2811796A1 (en) * 2013-06-07 2014-12-10 Stichting Vu-Vumuc Position-based broadcast protocol and time slot schedule for a wireless mesh network
EP3062178A1 (en) * 2013-10-24 2016-08-31 Yokogawa Electric Corporation Wireless device, wireless communication system, wireless module, interface module, and communication method
CN106604399A (en) * 2016-12-29 2017-04-26 深圳天珑无线科技有限公司 Energy collecting method and device
CN107426826A (en) * 2017-04-27 2017-12-01 成都瑞沣信息科技有限公司 The MAC protocol for wireless sensor networks design method collected based on RF energy
CN107911859A (en) * 2017-10-24 2018-04-13 天津大学 The life cycle of underwater wireless sensor network based on cross layer design extends method
CN108696926A (en) * 2018-05-09 2018-10-23 河海大学常州校区 A kind of underwater wireless sensor network cross-layer reliable data transmission method
CN109831344A (en) * 2019-03-25 2019-05-31 大连理工大学 A kind of UWSNs space-time routing framework acquisition methods based on SDN
WO2019108940A1 (en) * 2017-12-01 2019-06-06 Interdigital Patent Holdings, Inc. Network initiated on-demand zero-energy paging method and apparatus
CN110113785A (en) * 2019-05-07 2019-08-09 重庆邮电大学 Cooperation transmission method based on energy mutual assistance in a kind of collection of energy wireless sense network
CN110809904A (en) * 2017-07-01 2020-02-18 英特尔公司 Method and apparatus for vehicle radio communication
CN111132261A (en) * 2019-12-03 2020-05-08 华南理工大学 Power control, relay selection and time slot allocation method based on gait cycle
CN111988797A (en) * 2020-08-10 2020-11-24 国网能源研究院有限公司 Method and system for analyzing performance of two-hop multi-relay network driven by wireless energy transmission
CN112073931A (en) * 2020-08-20 2020-12-11 东南大学 Linear sensor network multi-hop data collection method based on redundant nodes
CN112235824A (en) * 2020-10-27 2021-01-15 国网能源研究院有限公司 Two-hop multi-relay network performance analysis method, system and device
CN112243258A (en) * 2020-10-14 2021-01-19 中国联合网络通信集团有限公司 Method and device for determining user perception rate
CN112469100A (en) * 2020-06-10 2021-03-09 广州大学 Hierarchical routing algorithm based on rechargeable multi-base-station wireless heterogeneous sensor network
CN113242587A (en) * 2021-01-04 2021-08-10 湖州师范学院 Cluster routing method based on hexagonal centroid cluster head election and dynamic time slot allocation

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101572649A (en) * 2008-04-30 2009-11-04 华为技术有限公司 Method and device for time slot allocation
CN102036335B (en) * 2009-09-27 2015-07-01 北京邮电大学 Route cognizing protocol for wireless network

Patent Citations (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388793A (en) * 2007-08-31 2009-03-18 费舍-柔斯芒特系统股份有限公司 Configuring and optimizing a wireless mesh network
CN102065575A (en) * 2009-11-11 2011-05-18 中国科学院沈阳自动化研究所 Method for constructing mesh and star hybrid topological wireless sensor network based on IEEE 802.15.4
CN101835277A (en) * 2010-02-09 2010-09-15 重庆理工大学 Wireless sensor network topology control method based on LEACH-ANT algorithm
CN103281746A (en) * 2013-06-03 2013-09-04 南昌大学 Wireless sensing network routing method of quotient topology energy hierarchical dynamic programming
US20160212729A1 (en) * 2013-06-07 2016-07-21 Stichting Vu-Vume Position-based broadcast protocol and time slot schedule for a wireless mesh network
WO2014195477A1 (en) * 2013-06-07 2014-12-11 Stichting Vu-Vumc Position-based broadcast protocol and time slot schedule for a wireless mesh network
EP2811796A1 (en) * 2013-06-07 2014-12-10 Stichting Vu-Vumuc Position-based broadcast protocol and time slot schedule for a wireless mesh network
EP3062178A1 (en) * 2013-10-24 2016-08-31 Yokogawa Electric Corporation Wireless device, wireless communication system, wireless module, interface module, and communication method
US20160261972A1 (en) * 2013-10-24 2016-09-08 Yokogawa Electric Corporation Wireless device, wireless communication system, wireless module, interface module, and communication method
CN106604399A (en) * 2016-12-29 2017-04-26 深圳天珑无线科技有限公司 Energy collecting method and device
CN107426826A (en) * 2017-04-27 2017-12-01 成都瑞沣信息科技有限公司 The MAC protocol for wireless sensor networks design method collected based on RF energy
CN110809904A (en) * 2017-07-01 2020-02-18 英特尔公司 Method and apparatus for vehicle radio communication
CN107911859A (en) * 2017-10-24 2018-04-13 天津大学 The life cycle of underwater wireless sensor network based on cross layer design extends method
WO2019108940A1 (en) * 2017-12-01 2019-06-06 Interdigital Patent Holdings, Inc. Network initiated on-demand zero-energy paging method and apparatus
CN108696926A (en) * 2018-05-09 2018-10-23 河海大学常州校区 A kind of underwater wireless sensor network cross-layer reliable data transmission method
CN109831344A (en) * 2019-03-25 2019-05-31 大连理工大学 A kind of UWSNs space-time routing framework acquisition methods based on SDN
CN110113785A (en) * 2019-05-07 2019-08-09 重庆邮电大学 Cooperation transmission method based on energy mutual assistance in a kind of collection of energy wireless sense network
CN111132261A (en) * 2019-12-03 2020-05-08 华南理工大学 Power control, relay selection and time slot allocation method based on gait cycle
CN112469100A (en) * 2020-06-10 2021-03-09 广州大学 Hierarchical routing algorithm based on rechargeable multi-base-station wireless heterogeneous sensor network
CN111988797A (en) * 2020-08-10 2020-11-24 国网能源研究院有限公司 Method and system for analyzing performance of two-hop multi-relay network driven by wireless energy transmission
CN112073931A (en) * 2020-08-20 2020-12-11 东南大学 Linear sensor network multi-hop data collection method based on redundant nodes
CN112243258A (en) * 2020-10-14 2021-01-19 中国联合网络通信集团有限公司 Method and device for determining user perception rate
CN112235824A (en) * 2020-10-27 2021-01-15 国网能源研究院有限公司 Two-hop multi-relay network performance analysis method, system and device
CN113242587A (en) * 2021-01-04 2021-08-10 湖州师范学院 Cluster routing method based on hexagonal centroid cluster head election and dynamic time slot allocation

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
"\"2019-5G-Americas-Rysavy-Implications-of-a-Transformational-Technology-White-Paper\"" *
SAIKUMAR: "A_systematic_approach_for_analyzing_hop_count_and_path_reliability_of_mobile_Ad_Hoc_networks" *
陈加法: "基于混合能量收集的移动边缘计算系统资源分配策略" *

Also Published As

Publication number Publication date
CN114585043B (en) 2023-07-21

Similar Documents

Publication Publication Date Title
Iova et al. Using multiparent routing in RPL to increase the stability and the lifetime of the network
CN111132299B (en) Resource allocation method and device for relay system
CN106162798A (en) The joint Power distribution of radio sensing network energy acquisition node cooperation transmission and relay selection method
Hu et al. An energy-efficient overlapping clustering protocol in WSNs
Xu et al. Joint relay assignment and power allocation for cooperative communications
Li et al. Optimal routing with scheduling and channel assignment in multi-power multi-radio wireless sensor networks
CN107911859A (en) The life cycle of underwater wireless sensor network based on cross layer design extends method
JP5861701B2 (en) Network control method, path control device, network control system, and path control program
CN102970392A (en) Efficient and rapid address assignment method for LR-WPAN (low rate-wireless personal area network) Mesh network nodes
KR101751757B1 (en) Time slot allocation and frequency slot allocation algorithm in a tree-based wireless sensor network
Kumbhkar et al. Rate optimal design of a wireless backhaul network using TV white space
Liu et al. Resource allocation for performance enhancement in mobile ad hoc networks
CN114585043A (en) Routing method, device, computer equipment and storage medium
KR101460946B1 (en) Network system and routing method thereof
Hahm et al. A case for time slotted channel hopping for ICN in the IoT
Mendes et al. Lifetime analysis of a slotted ALOHA-based wireless sensor network using a cross-layer frame rate adaptation scheme
CN111432351B (en) Method and system for networking tree-shaped multi-hop network
Zhang et al. Energy efficient joint data aggregation and link scheduling in solar sensor networks
Guo et al. On relay node placement and assignment for two-tiered wireless networks
Sabbah et al. Integrating energy harvesting and dynamic spectrum allocation in Cognitive Radio Networks
Zhang et al. Utility energy-based opportunistic routing for lifetime enhancement in wireless sensor networks
Wang et al. Hybrid placement of internet gateways and rechargeable routers with guaranteed QoS for green wireless mesh networks
Wu et al. Robust QoS Scheduling using alternate path for recovery from link failures in IEEE 802.15. 4e
Yallappa An enhanced routing protocol for energy harvesting-wireless sensor networks for optimal execution of iot applications
Samala et al. Energy harvest cognitive radio networks (EH-CRNs): A review paper

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant