CN109392055B - Sensor network cross-layer energy control method and device - Google Patents

Sensor network cross-layer energy control method and device Download PDF

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CN109392055B
CN109392055B CN201811379081.5A CN201811379081A CN109392055B CN 109392055 B CN109392055 B CN 109392055B CN 201811379081 A CN201811379081 A CN 201811379081A CN 109392055 B CN109392055 B CN 109392055B
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distance
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CN109392055A (en
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张卫冬
艾轶博
张涛
黄尚宇
陈佳
王璠
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University of Science and Technology Beijing USTB
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    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/12—Shortest path evaluation
    • H04L45/122—Shortest path evaluation by minimising distances, e.g. by selecting a route with minimum of number of hops
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/12—Shortest path evaluation
    • H04L45/124—Shortest path evaluation using a combination of metrics
    • 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
    • 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

Abstract

The invention provides a sensor network cross-layer energy control method and device, which can reduce energy consumption and prolong the service life of a network. The method comprises the following steps: determining a link d parameter between the receiving and transmitting nodes, wherein the d parameter is based on the actual distance between the receiving and transmitting nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition; according to the determined d parameter value, determining a reliable transmission distance between the receiving and transmitting nodes under the constraint of link reliability, and determining the strength of a transmitting signal according to the determined reliable transmission distance; judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes; and if so, determining the minimum hop count of the node from the base station layer by layer from inside to outside, and determining the area to which the node belongs according to the determined minimum hop count of the node from the base station and networking. The present invention relates to the field of energy control.

Description

Sensor network cross-layer energy control method and device
Technical Field
The invention relates to the field of energy control, in particular to a cross-layer energy control method and device for a sensor network.
Background
With the rapid development of technologies such as integrated circuits, Wireless communication, sensors, Micro-Electro-mechanical systems (MEMS), and the like, Wireless Sensor Network (WSN) technology is gaining more and more attention in the Automatic Meter Reading Application (AMRS) industry, and the time and cost of manual Meter Reading are greatly reduced. Among various automatic meter reading modes, the wireless meter reading system has the advantages of no strict limitation on the requirements of node positions and no need of wiring, while the wired meter reading mode has the problems of unstable channel, high engineering cost, difficult maintenance and the like.
The wireless meter reading system caters to the application direction of the current big data, not only can a user conveniently carry out expense payment and information query, but also can a hydropower company and a heating power company conveniently, quickly and inexpensively obtain the use information of the user, and therefore unified management is carried out on the data. The wireless meter reading system also provides a convenient big data integration mechanism for wireless meter reading system enterprises, and the habits of users can be obtained by analyzing and processing the data, so that the operation strategies can be adjusted according to the habits of the users, and the optimized input and output can be achieved. In view of the above considerations, the meter reading industry began to attempt to switch from wired to wireless from the beginning of 2000. In 9 months of 2005, the electric meter reading standard was established, and then the water, gas and heat meter standards were also established one after another.
However, in the meter reading industry, because the nodes are distributed at different positions of a building and the positions are scattered, the indoor meter reading has the defects of poor reliability and high energy consumption.
Disclosure of Invention
The invention aims to solve the technical problem of providing a sensor network cross-layer energy control method and device to solve the problems of poor reliability and high energy consumption of indoor meter reading caused by node dispersion in the prior art.
To solve the above technical problem, an embodiment of the present invention provides a method for controlling cross-layer energy of a sensor network, including:
determining a link d parameter between the receiving and transmitting nodes, wherein the d parameter is based on the actual distance between the receiving and transmitting nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition;
according to the determined d parameter value, determining a reliable transmission distance between the receiving and transmitting nodes under the constraint of link reliability, and determining the strength of a transmitting signal according to the determined reliable transmission distance;
judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes;
and if so, determining the minimum hop count of the node from the base station layer by layer from inside to outside, and determining the area to which the node belongs according to the determined minimum hop count of the node from the base station and networking.
Wherein the d parameter is expressed as:
d＝distance+α
α＝α_static+α_dynamic
wherein, distance represents the actual distance between the transmitting and receiving nodes, α represents the equivalent d parameter increment of the path loss, α _ static represents the equivalent d parameter increment of the path loss caused by static blocking, and α _ dynamic represents the equivalent d parameter increment of the path loss caused by dynamic blocking.
Wherein the reliable transmission distance is expressed as:
Figure BDA0001871462890000021
where ds represents the reliable transmission distance; pnRepresenting a noise floor; gamma rayU(Prr) represents the signal-to-noise ratio under d parameter corresponding to Prr, Prr represents the packet reception rate; ptIndicating the strength of the emitted signal, P L (d)0) Indicates the reference distance d0Lower path loss; n represents a path attenuation exponent; σ represents the variance of the gaussian random variable.
Wherein determining the transmitted signal strength based on the determined reliable transmission distance comprises:
and aiming at the step characteristic of the intensity of the transmitted signal, if the value of the d parameter is between ds of two transmitted signal intensity steps, controlling to transmit the signal by using the transmitted signal intensity step one higher than the d parameter.
The number of the area to which the node belongs is the minimum hop count of the node from the base station;
when the node is communicated with the base station, the node sequentially transmits information according to the sequence of the region numbers from large to small.
The embodiment of the invention also provides a sensor network cross-layer energy control device, which comprises:
the first determining module is used for determining a link d parameter between the receiving and transmitting nodes, wherein the d parameter is based on the actual distance between the receiving and transmitting nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition;
the second determining module is used for determining the reliable transmission distance under the link reliability constraint between the transceiving nodes according to the determined d parameter value and determining the strength of the transmitting signal according to the determined reliable transmission distance;
the judging module is used for judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes;
and the third determining module is used for determining the minimum hop count of the node from the base station layer by layer from inside to outside if the node is located in the area, and the node determines the area to which the node belongs according to the determined minimum hop count of the node from the base station and performs networking.
Wherein the d parameter is expressed as:
d＝distance+α
α＝α_static+α_dynamic
wherein, distance represents the actual distance between the transmitting and receiving nodes, α represents the equivalent d parameter increment of the path loss, α _ static represents the equivalent d parameter increment of the path loss caused by static blocking, and α _ dynamic represents the equivalent d parameter increment of the path loss caused by dynamic blocking.
Wherein the reliable transmission distance is expressed as:
Figure BDA0001871462890000031
where ds represents the reliable transmission distance; pnRepresenting a noise floor; gamma rayU(Prr) represents the signal-to-noise ratio under d parameter corresponding to Prr, Prr represents the packet reception rate; ptIndicating the strength of the emitted signal, P L (d)0) Indicates the reference distance d0Lower path loss; n represents a path attenuation exponent; σ represents the variance of the gaussian random variable.
The second determining module is used for controlling the signal to be transmitted by using a higher transmission signal strength gear if the value of the d parameter is between ds of two transmission signal strength gears according to the transmission signal strength stepped characteristic.
The number of the area to which the node belongs is the minimum hop count of the node from the base station;
when the node is communicated with the base station, the node sequentially transmits information according to the sequence of the region numbers from large to small.
The technical scheme of the invention has the following beneficial effects:
in the scheme, a link d parameter between the receiving and transmitting nodes is determined, wherein the d parameter is based on the actual distance between the receiving and transmitting nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition; according to the determined d parameter value, determining a reliable transmission distance between the receiving and transmitting nodes under the constraint of link reliability, and according to the determined reliable transmission distance, determining the strength of a transmitting signal so as to ensure the reliability of data and ensure the quality of the data; judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes; if the node is located in the area, the minimum hop count of the node from the base station is determined layer by layer from inside to outside, the node determines the area to which the node belongs according to the determined minimum hop count of the node from the base station and conducts networking, and the networking mode based on the area can reduce energy consumption and prolong the service life of the network.
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Fig. 1 is a schematic flowchart of a cross-layer energy control method for a sensor network according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a principle of a cross-layer energy control method for a sensor network according to an embodiment of the present invention;
fig. 3 is a schematic diagram of node data transmission of an EBACR simulation run for 32 rounds according to the embodiment of the present invention;
fig. 4 is a schematic diagram of section parameters provided in the embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a relationship principle of a d-parameter model according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of three-dimensional distribution of nodes when 30 rounds of simulation operation are performed according to the embodiment of the present invention;
fig. 7 is a schematic diagram of the distribution of nodes in a floor according to an embodiment of the present invention;
fig. 8 is a schematic diagram illustrating a number of failed nodes and a change in total energy utilization rate without using a cross-layer energy control strategy according to an embodiment of the present invention;
fig. 9 is a schematic diagram illustrating a number of failed nodes and a change in total energy utilization rate after a cross-layer energy control strategy is adopted according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram of a sensor network cross-layer energy control device according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The invention provides a sensor network cross-layer energy control method and device, aiming at the problems of poor reliability and high energy consumption of indoor meter reading caused by existing node dispersion.
Example one
As shown in fig. 1 and fig. 2, a method for controlling energy across layers of a sensor network according to an embodiment of the present invention includes:
s101, determining a link d parameter between transmitting and receiving nodes, wherein the d parameter is based on the actual distance between the transmitting and receiving nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition;
s102, determining a reliable transmission distance under the link reliability constraint between the transceiving nodes according to the determined d parameter value, and determining the strength of a transmitting signal according to the determined reliable transmission distance;
s103, judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes;
and S104, if the node is located in the position, determining the minimum hop count of the node from the base station layer by layer from inside to outside, and determining the region to which the node belongs according to the determined minimum hop count of the node from the base station and networking the node.
The sensor network cross-layer energy control method determines a link d parameter between transmitting and receiving nodes, wherein the d parameter is based on the actual distance between the transmitting and receiving nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition; according to the determined d parameter value, determining a reliable transmission distance between the receiving and transmitting nodes under the constraint of link reliability, and according to the determined reliable transmission distance, determining the strength of a transmitting signal so as to ensure the reliability of data and ensure the quality of the data; judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes; if the node is located in the area, the minimum hop count of the node from the base station is determined layer by layer from inside to outside, the node determines the area to which the node belongs according to the determined minimum hop count of the node from the base station and conducts networking, and the networking mode based on the area can reduce energy consumption and prolong the service life of the network.
The sensor network cross-layer energy control method described in this embodiment optimizes from two aspects of a network layer and a data link layer:
on one hand, according to a network layer of an indoor wireless meter reading sensor network, on the basis of a node role selection mechanism of an Energy-consumption-balanced Adaptive Clustering Routing (EBACR), an area Energy consumption balancing strategy is provided, the Energy consumption balancing of nodes around a base station is emphasized, and a Section-Energy-consumption-balanced Adaptive Clustering Routing (S-EBACR) algorithm is determined in consideration of unavailability of Energy holes.
For a better understanding of the present embodiment, a brief explanation of EBACR is given:
the EBACR is a self-adaptive clustering routing algorithm which is specially designed for indoor application and has balanced energy, the clustering characteristic of the EBACR is more suitable for indoor meter reading application, and therefore the S-EBACR is designed by combining special requirements of indoor meter reading application on the basis of the EBACR.
The advantages of EBACR are mainly reflected in both the adaptation to the environment and the energy balance. The basic design idea is as follows: when selecting a cluster head, firstly, a multi-attribute decision method is used to comprehensively consider the node residual energy and the value of Received Signal Strength Indication (RSSI) to a base station to obtain an F value, and then the magnitude comparison of the F value is used to judge whether the node is to become the cluster head. It should be noted that the EBACR also gives a selection criterion of the forwarding node, and the calculation method of the F value is the same as the cluster head, but the forwarding node will pay more attention to the position of the node from the base station during calculation; the F value represents the result of the multi-attribute decision of the sensor node, and the calculation method comprises the following steps:
Figure BDA0001871462890000061
wherein (section-section j) { -1, 0, 1}) section represents a section of the node; section j represents the section of the jth neighbor node; omegakRepresenting a subjective weight coefficient; omegak' represents an objective weight coefficient; λ represents a ratio of subjective and objective weight coefficients; u. ofjd to BSRepresents the normalized attribute of the jth neighbor node d to the BS; u. ofjkA kth normalized attribute representing a jth neighbor node of the node; section gradientjRepresenting the gradient of the normalized j-th node.
In this embodiment, section gradientjExpressed as:
Figure BDA0001871462890000062
Figure BDA0001871462890000063
Figure BDA0001871462890000064
by the formula
Figure BDA0001871462890000071
Carrying out normalization processing to obtain the gradient of the neighbor node with the number j; u shapejkA kth corresponding evaluation attribute value (e.g., a benefit attribute, a cost attribute) representing a jth neighbor node of the node;
Figure BDA0001871462890000072
indicating different evaluation attribute values for which the row vector represents a neighbour node, e.g.
Figure BDA0001871462890000073
m represents the number of neighbor nodes; k1、K2Respectively representing a benefit attribute and a cost attribute.
After a new round of networking of the EBACR is completed, the nodes can be divided into 5 roles, namely member nodes, cluster head nodes, forwarding nodes, relay nodes and base stations; once the role of the base station is determined to be unchangeable, the base station is generally heterogeneous to other types of nodes, that is, a General base station has a strong data processing function and a data sending function, has a constant power supply, and is responsible for processing a large amount of necessary data and sending the data to a server through the internet or General Packet Radio Service (GPRS).
The acquired data is finally transmitted to the base station by the data terminal taking the role as the member node, and the complete path has the following possibilities:
route 1: data acquisition terminal (member node) → base station
Route 2: data acquisition terminal (member node) → cluster head node → base station
Route 3: data acquisition terminal (member node) → cluster head node → forwarding node → base station
Path 4: data acquisition terminal (member node) → cluster head node → forwarding node → relay node 1 → … relay node n → base station
Due to the large distribution range of the indoor nodes, most of data is uploaded according to the path 4, that is, the data can be transmitted to the base station through one or more relay nodes. Since the EBACR only uses two attributes, namely, the remaining node energy and the RSSI value signaled by the base station, as key attributes of the multi-attribute decision, in the actual networking process, selecting the next-hop relay node according to the F value calculated by the multi-attribute decision may cause too many times of relay node forwarding, and a situation occurs that data is transmitted to the far end of the base station and then transmitted to the base station, although the energy consumption balance of the entire network is enhanced, a great amount of unnecessary forwarding energy waste is caused. Fig. 3 shows that when the EBACR is randomly distributed on a plane by 100 nodes, the simulation algorithm runs 32 rounds of network topology connection, and it can be seen that data collected by two nodes with numbers 61 and 42 needs to be forwarded for 12 times before being transmitted to the base station with number 101.
In the simulation process, since the EBACR emphasizes the energy balance of the whole network excessively and does not take the energy hole effect into consideration, the nodes within three hops away from the base station are forwarded to the far base station end due to the global energy consumption balance, and unnecessary energy consumption in forwarding is increased.
For the problem of unnecessary energy consumption caused by excessive forwarding times and energy hole effect, a region (section) is introduced as a new attribute in the embodiment, a region energy consumption balancing strategy is proposed, and fig. 4 is a section parameter schematic diagram.
In this embodiment, the section is improved, and energy balance is considered according to different topological areas. Before networking, a sink node (i.e. a base station) is defined as section1, a node capable of directly communicating with the sink node is defined as section2, a node which needs to transmit to the sink via one hop is defined as section3, and so on, so that: the number of the area to which the node belongs is the minimum hop count of the node from the base station. It should be noted that in fig. 4, the points are distinguished according to the section by using a circular ring, which is a simple representation in the topological case, and in the actual non-line-of-sight condition, due to the asymmetry of the link and the existence of the path loss of the link, two nodes possibly in the same section are not exactly close to the distance between the sink nodes in the geographical position.
In the actual operation process of the wireless meter reading system network, the base station, that is, the sink node is generally located in the geometric center of the area where the sink node is located, so that the distribution of the nodes on the two sides of the base station can be assumed to be uniformly distributed in the rectangular floor. The data transmission quantity should be balanced in the peripheral topology of the base station as much as possible, so that the energy balance of the nodes near the base station is achieved, and the energy consumed by the nodes near the base station due to forwarding is reduced. How to select the node with the smaller number from the nodes with the larger number of the sections is a problem to be solved.
Because the nodes are distinguished according to the hop count of communication with the base station, the nodes should be sequentially transmitted according to the sequence of the section numbers from large to small as much as possible in the actual operation process of the network, and the transmission in the same section or the transmission of the section numbers from small to large is avoided as much as possible.
In the regional energy consumption balancing strategy, the concept of the F value in the EBACR is also used, and different calculation methods are used for node role types which are greatly distinguished in the two major functions of cluster heads and forwarding/relaying. The algorithm calculates F of the cluster head based on the residual energy of the nodes and the distance between the nodes and the base station as two key parametersCHThe algorithm of the value pays more attention to the residual energy of the node, because the cluster head needs to carry out certain integration on the data of the child node, and needs extra energy support; f for calculating forwarding and relay nodesRThe algorithm of values is more focused on the distance between the node and the base station, since the forwarding or relaying node has the task of transmitting data remote from the base station to the base station. Each sensor node compares its own with its neighbor nodes FCHOr FRValue if own FCHOr FRAt the maximum, this node becomes a cluster head node or a forwarding/relaying node, respectively.
In this embodiment, a simulation experiment is compared with the original EBACR algorithm, which verifies that the improved S-EBACR algorithm has a better effect in terms of energy saving in forwarding, as shown in table 1. As can be seen from table 1, when 100 sensor nodes are randomly distributed, the nodes can obviously reduce the average forwarding number of each round of the nodes under the condition of complete network by using an S-EBACR networking mode, thereby reducing the energy consumed by excessive forwarding. In the aspect of network life, due to the inhibition effect of S-EBACR on the energy cavity effect, the network life is improved by 11 percent based on the original EBACR. It can be seen from comparison between the energy consumption balance of the whole network and the energy consumption balance of the nodes with the Section2 and 3 that the energy consumption balance of the nodes near the base station is emphasized more by the S-EBACR, when the first energy-exhausted node appears, the energy consumption balance is improved by 20% compared with the EBACR, and the energy consumption balance of the S-EBACR is relatively poor for the peripheral nodes, but because the energy consumption balance is less in the load of forwarding and data processing, the energy consumption balance does not need to be pursued too much.
TABLE 1100 optimization Effect comparison under random distribution of sensor nodes
Figure BDA0001871462890000091
And on the other hand, according to a data link layer of the indoor wireless meter reading sensor network, determining a d-parameter link quality estimation method based on the position information, and determining a transmission signal strength self-adaptive control strategy based on the d-parameter.
(1) And determining a d-parameter link quality estimation method based on the position information according to the characteristic that the position of the wireless sensor node is known in the indoor wireless meter reading application.
In this embodiment, a new d parameter is defined to reflect the change of the link quality, and other link quality evaluation methods, such as RSSI, are not used, mainly because the d parameter is based on the actual distance between the transceiving nodes, and the path loss caused by dynamic blocking and static blocking under the non-line-of-sight condition in the transmission process is equivalent to the increment of the distance under the line-of-sight condition, so that the position information and the environment information of the node under the indoor wireless meter reading condition are fully utilized.
In this embodiment, the d parameter is a key parameter relating to transmission energy consumption, packet reception rate, and packet retransmission times, and is based on the actual distance between the transceiving nodes, the path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to an increment in the distance under the line-of-sight condition, and the d parameter is respectively counted in the form of an increment of α _ dynamic and an increment of α _ static to obtain a d parameter increment dynamic change model, which is expressed as:
d＝distance+α (1)
α＝α_static+α_dynamic (2)
the distance represents the actual distance between the transmitting and receiving nodes and is a unit m, α represents the equivalent d parameter increment of the path loss, including the increment of the dynamic path loss and the increment of the static path loss, α _ static represents the equivalent d parameter increment of the path loss caused by static blocking and is a unit m, and α _ dynamic represents the equivalent d parameter increment of the path loss caused by dynamic blocking and is a unit m.
In this embodiment, in order to relate the energy consumption of the network layer to the link quality of the data link layer, a model is built by combining several parameters, such as transmission energy consumption, packet receiving rate and packet retransmission times, using a parameter d; wherein the content of the first and second substances,
in the process of calculating transmission energy consumption, for example, a transmission energy consumption model corresponding to a certain parameter d under an actual condition can be calculated according to the programmable transmission signal intensity step characteristic of the CC 1100;
in the process of calculating the packet receiving rate, establishing a model according to the relation of distance and packet receiving rate;
when the retransmission times are calculated, a packet loss time calculation model is established based on the continuous packet loss time statistical matrix and the packet loss probability model, so that the energy consumption caused by packet loss retransmission is calculated.
When the energy consumption calculation of the network layer simulation is carried out, the d parameter is converted into the predicted energy consumption. Considering the step-by-step controllable characteristic (abbreviated as step-by-step characteristic) of the transmitted signal strength of CC1100, a series of d parameters corresponding to certain reliability needs to be established in advance, and then the d parameters obtained in real time are judged to determine the used transmitted signal strength gear.
When the parameter value d is located between the reliable transmission distances of the two transmission signal strength gears, the reliability of the link between the receiving and transmitting nodes is taken as a primary constraint, namely the single transmission success rate is taken as a dependent variable, and the reliable transmission distance is determined by using the following relation:
Figure BDA0001871462890000101
where ds represents the reliable transmission distance; pnRepresenting a noise floor; gamma rayU(Prr) represents a signal-to-noise ratio at a d-parameter distance corresponding to the Prr, the Prr representing a Packet Reception Rate (Packet Reception Rate); ptIndicating the strength of the emitted signal, P L (d)0) Indicates the reference distance d0The lower path loss, for example, can be 35dB in this embodiment; n represents a path decay exponent (signal decay rate); σ represents the variance of the gaussian random variable.
It should be noted that: the packet reception rate is usually used as an evaluation criterion of link quality, and it is generally considered that a new evaluation criterion of link quality can accurately reflect the change of the packet reception rate, so that the packet reception rate has better accuracy. In this embodiment, it can be assumed that when PRR is 98%, γ isU(Prr) represents the signal-to-noise ratio at the distance of the corresponding d-parameter at a packet reception rate of 98%.
(2) Determining transmit signal strength adaptive control strategy based on d parameter
For the randomly changed d parameter value, if the d parameter value of the link between two nodes is between ds of two transmission signal strength gears, the transmission signal strength gear higher by one level is controlled to meet the requirement of single transmission success rate.
After the d parameter value is obtained in the step (1), judging which ds interval the d parameter value belongs to and deciding which transmission signal intensity gear is used; the transmitting signal strength and the corresponding reliable transmission distance are shown in table 2; therefore, the link can obtain the conservative signal strength, the reliability requirement is met, the influence of fluctuation caused by the RSSI value contained in the d parameter can be overcome, complex calculation is not needed, and the robustness of the control of the transmitted signal strength is enhanced.
TABLE 2 emission signal strength and corresponding reliable transmission distance
Figure BDA0001871462890000111
(3) Simulating a transmit signal strength adaptive control strategy based on a d parameter
In this embodiment, based on the d parameter, the d parameter incremental dynamic change model (equation (1)) is used as the external interference by using the corresponding distance-energy consumption model based on the line-of-sight condition, so as to verify the validity of the d parameter incremental dynamic change model, and a model relationship framework is shown in fig. 5.
In this embodiment, the parameter d of the link quality estimation method for the indoor link is designed and verified, and a model relationship among reliability constraint, energy consumption, and retransmission times is established around the parameter d, thereby forming a whole set of simulation theory. Based on the d parameter, an energy consumption control strategy combining the CC1100 transmitted signal strength step characteristic is established, and the transmitted signal strength control strategy adopting the RSSI and the d parameter is compared in a simulation mode, so that the effectiveness of the transmitted signal strength control strategy based on the d parameter in the aspects of reliability and energy consumption adaptive control is proved.
And finally, determining a network cross-layer energy control strategy according to the proposed regional energy consumption balance strategy and the parameter d, and performing simulation verification on the network cross-layer energy control strategy:
in the operation process of a network layer S-EBACR algorithm, determining section parameters requires calculating reliable transmission distance under the constraint of link reliability between receiving and transmitting nodes according to a link d parameter strategy between the data receiving and transmitting nodes, and determining the strength of a transmitting signal according to the determined reliable transmission distance; judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes; and if so, the S-EBACR determines the minimum hop count of the node from the base station layer by layer from inside to outside, and the node determines which section belongs to and performs networking according to the minimum hop count from the node to the base station.
In this embodiment, a cross-layer energy control strategy for simulating an indoor environment by using a transmit signal strength adaptive adjustment scheme based on a d parameter in combination with an S-EBACR algorithm is compared with a network performance without the cross-layer energy control strategy, so as to verify the effect of the sensor network cross-layer energy control method in terms of network lifetime and energy utilization. Fig. 6 is a three-dimensional distribution of nodes when the simulation runs for 30 rounds, and fig. 7 is a distribution of the nodes in floors. The lines between the nodes represent the connection status between the nodes in the current round.
In this embodiment, the network lifetime is the number of rounds of the node passing from the beginning of the network operation to the first energy of 0; the energy utilization rate is represented by the percentage of the total energy remaining, and the percentage of the total energy remaining is the ratio of the network total energy remaining when the first node with the energy of 0 appears to the initial network total energy.
Fig. 8 and 9 are schematic diagrams of the number of failed nodes before and after adopting a cross-layer energy control strategy and the change of the total energy utilization rate; when the cross-layer energy control strategy is not used, the network has a service life of 34 rounds, and the percentage of the remaining total energy is 36%; after using the cross-layer energy control strategy, the network has a lifetime of 78 rounds with a remaining energy percentage of 23%.
By combining the above results, it can be seen that after the cross-layer control strategy is adopted, the network life of the node can be improved to 229% of the original life on the basis of meeting the reliability of the industry specification, and the energy utilization rate of the node can be improved to 156% of the original life on the basis of meeting the reliability of the industry specification, so that the cross-layer energy control strategy can be proved to have the effects of improving the node energy utilization efficiency in practical application and reducing the node battery replacement cost.
In summary, according to the application characteristics of indoor wireless meter reading and the requirement analysis of network layer topology algorithm and link layer link quality estimation thereof, the embodiment determines a sensor network cross-layer energy control method suitable for indoor wireless meter reading aiming at two main indexes of data transmission reliability and energy, and mainly aiming at a network layer and a data link layer of a wireless sensor network protocol stack; wherein the content of the first and second substances,
in the aspect of a network layer, the characteristics of a topology control algorithm are analyzed, and an area Energy consumption balancing strategy is provided on the basis of a node role selection mechanism of an Energy consumption balancing self-Adaptive Clustering Routing (EBACR) in combination with the requirements of an indoor wireless meter reading system, so that the Energy consumption balancing of nodes around a base station is emphasized, and a Section-Energy-balanced self-Adaptive Clustering Routing (S-EBACR) algorithm is determined in consideration of the unavailability of Energy holes, thereby avoiding the problem of the Energy holes and improving the area Energy consumption balancing of the network;
in the aspect of a data link layer, a new link quality estimation mode, namely a mode of a link d parameter between receiving and transmitting nodes is defined, and a transmission signal strength self-adaptive control strategy considering the actual transmission signal strength grading condition is established around the d parameter; and establishing a corresponding simulation energy consumption calculation algorithm and a d parameter dynamic change model, and proving the effectiveness of the transmitted signal strength adaptive control strategy based on the d parameter.
On the basis of an S-EBACR networking topological algorithm of a network layer and a d parameter transmitting signal intensity self-adaptive control strategy of a data link layer, a cross-layer energy control strategy is provided in combination, and the optimization effect of the cross-layer energy control method on the aspects of total energy utilization rate and network service life is proved by simulating the network performance before and after the cross-layer energy control method is adopted in an actual three-dimensional environment, so that the method has double meanings of theory and practice.
The sensor network cross-layer energy control method described in this embodiment performs targeted optimization design on requirements from two aspects, namely, a network layer and a data link layer, aiming at two main indexes, namely, data transmission reliability and energy, so as to achieve the following effects:
(1) in the aspect of reliability, the reliability of the link is used as the primary constraint, so that the reliability of the data is ensured, and the quality of the data is ensured.
(2) In the aspect of energy, a self-adaptive emission signal intensity control mechanism is adopted under the condition of firstly meeting the reliability constraint, so that the energy consumption is reduced, and the service life of a network is prolonged; and by adopting an S-EBACR networking mode, the nodes can obviously reduce the average forwarding number of each round of the nodes under the condition of complete network, thereby reducing the energy consumed by excessive forwarding.
(2) In the aspect of network life, due to the inhibition effect of S-EBACR on the energy cavity effect, the network life is improved by 11 percent on the basis of the original EBACR.
Example two
The present invention further provides a specific embodiment of a sensor network cross-layer energy control device, which corresponds to the specific embodiment of the sensor network cross-layer energy control method, and the sensor network cross-layer energy control device can achieve the purpose of the present invention by executing the flow steps in the specific embodiment of the method, so the explanation in the specific embodiment of the sensor network cross-layer energy control method is also applicable to the specific embodiment of the sensor network cross-layer energy control device provided by the present invention, and will not be described in detail in the following specific embodiment of the present invention.
As shown in fig. 10, an embodiment of the present invention further provides a sensor network cross-layer energy control device
A first determining module 11, configured to determine a parameter d of a link between the transceiver nodes, where the parameter d is based on an actual distance between the transceiver nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in a transmission process is equivalent to an increment of the distance under the line-of-sight condition;
a second determining module 12, configured to determine, according to the determined d parameter value, a reliable transmission distance under the link reliability constraint between the transceiver nodes, and determine, according to the determined reliable transmission distance, a transmission signal strength;
a judging module 13, configured to judge whether the reliable transmission distance is within a maximum transmission distance under a link reliability constraint between the transceiver nodes;
and a third determining module 14, configured to determine, layer by layer, the minimum hop count of the node from the base station from inside to outside if the node is located, and determine, according to the determined minimum hop count of the node from the base station, an area to which the node belongs and perform networking.
The sensor network cross-layer energy control device determines a link d parameter between the transmitting and receiving nodes, wherein the d parameter is based on the actual distance between the transmitting and receiving nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition; according to the determined d parameter value, determining a reliable transmission distance between the receiving and transmitting nodes under the constraint of link reliability, and according to the determined reliable transmission distance, determining the strength of a transmitting signal so as to ensure the reliability of data and ensure the quality of the data; judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes; if the node is located in the area, the minimum hop count of the node from the base station is determined layer by layer from inside to outside, the node determines the area to which the node belongs according to the determined minimum hop count of the node from the base station and conducts networking, and the networking mode based on the area can reduce energy consumption and prolong the service life of the network.
In an embodiment of the foregoing sensor network cross-layer energy control apparatus, further, the d parameter is expressed as:
d＝distance+α
α＝α_static+α_dynamic
wherein, distance represents the actual distance between the transmitting and receiving nodes, α represents the equivalent d parameter increment of the path loss, α _ static represents the equivalent d parameter increment of the path loss caused by static blocking, and α _ dynamic represents the equivalent d parameter increment of the path loss caused by dynamic blocking.
In an embodiment of the foregoing sensor network cross-layer energy control apparatus, further, the reliable transmission distance is expressed as:
Figure BDA0001871462890000151
where ds represents the reliable transmission distance; pnRepresenting a noise floor; gamma rayU(Prr) represents the signal-to-noise ratio under d parameter corresponding to Prr, Prr represents the packet reception rate; ptIndicating the strength of the emitted signal, P L (d)0) Indicates the reference distance d0Lower path loss; n represents a path attenuation exponent; σ represents the variance of the gaussian random variable.
In an embodiment of the foregoing sensor network cross-layer energy control apparatus, further, the second determining module is configured to control, for a transmission signal strength step characteristic, to transmit a signal using a higher transmission signal strength step if the d parameter value is between ds of two transmission signal strength steps.
In a specific embodiment of the foregoing sensor network cross-layer energy control apparatus, further, the number of the area to which the node belongs is the minimum hop count of the node itself from the base station;
when the node is communicated with the base station, the node sequentially transmits information according to the sequence of the region numbers from large to small.
It is noted that, herein, 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.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (6)

1. A sensor network cross-layer energy control method is characterized by comprising the following steps:
determining a link d parameter between the receiving and transmitting nodes, wherein the d parameter is based on the actual distance between the receiving and transmitting nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition;
according to the determined d parameter value, determining a reliable transmission distance between the receiving and transmitting nodes under the constraint of link reliability, and determining the strength of a transmitting signal according to the determined reliable transmission distance;
judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes;
if the node is located in the area, determining the minimum hop count of the node from the base station layer by layer from inside to outside, and determining the area to which the node belongs according to the determined minimum hop count of the node from the base station and networking the node;
wherein the reliable transmission distance is expressed as:
Figure FDA0002474453140000011
where ds represents the reliable transmission distance; pnRepresenting a noise floor; gamma rayU(Prr) represents the signal-to-noise ratio under d parameter corresponding to Prr, Prr represents the packet reception rate; ptIndicating the strength of the emitted signal, P L (d)0) Indicates the reference distance d0Lower path loss; n represents a path attenuation exponent; σ represents the variance of the gaussian random variable;
wherein determining the transmitted signal strength based on the determined reliable transmission distance comprises:
and aiming at the step characteristic of the intensity of the transmitted signal, if the value of the d parameter is between ds of two transmitted signal intensity steps, controlling to transmit the signal by using the transmitted signal intensity step one higher than the d parameter.
2. The sensor network cross-layer energy control method of claim 1, wherein the d parameter is expressed as:
d＝distance+α
α＝α_static+α_dynamic
wherein, distance represents the actual distance between the transmitting and receiving nodes, α represents the equivalent d parameter increment of the path loss, α _ static represents the equivalent d parameter increment of the path loss caused by static blocking, and α _ dynamic represents the equivalent d parameter increment of the path loss caused by dynamic blocking.
3. The sensor network cross-layer energy control method according to claim 1, wherein the number of the area to which the node belongs is the minimum hop count of the node from the base station;
when the node is communicated with the base station, the node sequentially transmits information according to the sequence of the region numbers from large to small.
4. A sensor network cross-layer energy control apparatus, comprising:
the first determining module is used for determining a link d parameter between the receiving and transmitting nodes, wherein the d parameter is based on the actual distance between the receiving and transmitting nodes, and path loss caused by dynamic blocking and static blocking under a non-line-of-sight condition in the transmission process is equivalent to increment of the distance under the line-of-sight condition;
the second determining module is used for determining the reliable transmission distance under the link reliability constraint between the transceiving nodes according to the determined d parameter value and determining the strength of the transmitting signal according to the determined reliable transmission distance;
the judging module is used for judging whether the reliable transmission distance is within the maximum transmission distance under the link reliability constraint between the receiving and transmitting nodes;
the third determining module is used for determining the minimum hop count of the node from the base station layer by layer from inside to outside if the node is located in the position, and the node determines the area to which the node belongs according to the determined minimum hop count of the node from the base station and performs networking;
wherein the reliable transmission distance is expressed as:
Figure FDA0002474453140000021
where ds represents the reliable transmission distance; pnRepresenting a noise floor; gamma rayU(Prr) represents the signal-to-noise ratio under d parameter corresponding to Prr, Prr represents the packet reception rate; ptIndicating the strength of the emitted signal, P L (d)0) Indicates the reference distance d0Lower path loss; n represents a path attenuation exponent; σ represents the variance of the gaussian random variable;
the second determining module is used for controlling the signal to be transmitted by using a higher transmission signal strength gear if the value of the d parameter is between ds of two transmission signal strength gears according to the transmission signal strength stepped characteristic.
5. The sensor network cross-layer energy control device of claim 4, wherein the d parameter is expressed as:
d＝distance+α
α＝α_static+α_dynamic
wherein, distance represents the actual distance between the transmitting and receiving nodes, α represents the equivalent d parameter increment of the path loss, α _ static represents the equivalent d parameter increment of the path loss caused by static blocking, and α _ dynamic represents the equivalent d parameter increment of the path loss caused by dynamic blocking.
6. The sensor network cross-layer energy control device according to claim 4, wherein the number of the area to which the node belongs is the minimum hop count of the node from the base station;
when the node is communicated with the base station, the node sequentially transmits information according to the sequence of the region numbers from large to small.
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