CN107592604B - Wireless chargeable sensor network mobile data collection method based on offline model - Google Patents
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Abstract
The invention discloses a wireless chargeable sensor network mobile data collection method based on an offline model. The invention is designed for some scenes which need to collect data generated by each sensor node in the network and the network can continuously run. The method provides an offline data collection model, anchor point selection, path planning and the like, a base station globally plans a SenCar path through the offline data collection model, selects an anchor point which can serve the whole network, can predict possible death nodes in the network in advance, takes the possible death nodes as special anchor points to obtain charging opportunities, and can use as few SenCars as possible to complete the target through the path planning. The method can collect data generated in the last period of each sensor node in the network in the period, and meanwhile, the residual energy of the sensor nodes in the network is guaranteed not to be lower than the energy required by normal work. The method is suitable for reliable and efficient collection of data in special scenes.
Description
Technical Field
The invention mainly relates to the field of wireless sensor networks, in particular to a wireless chargeable sensor network mobile data collection method based on an offline model, which is suitable for a scene that data generated by each sensor node in a network needs to be collected and the network can continuously run.
Background
The wireless sensor network is a multi-hop self-organizing network formed by a large number of sensor nodes in a wireless communication mode, and the sensor nodes have the functions of information acquisition, data processing, wireless communication and the like and have the characteristics of limited energy and limited calculation and communication capacity. The wireless sensor network can work in severe or special environments where people cannot approach, such as climate monitoring, outer space, battlefield environment, information acquisition system construction and the like, and can play an important role in disaster monitoring of flood, fire or earthquake catastrophic environments, and such scenes are common application modes of the wireless sensor network. In some scenarios, it is necessary to collect each time in the networkData of individual sensor nodes and no residual energy in the network below the normal operating value EminThe sensor node of (1). However, the previously designed wireless chargeable sensor network data collection method based on the off-line model cannot be guaranteed. How to collect data of each sensor node in the network and ensure that no sensor nodes with residual energy lower than a normal working value appear in the network becomes a hotspot in the research field.
In a wireless sensor network, a traditional data collection method is to transmit data back to a base station through an ad hoc network of sensor nodes by means of multi-hop relay, but this causes that the sensor nodes closer to the base station need to transmit and receive more data, and the main energy consumption of the sensor nodes is the transmission and reception of the data, so that the faster the energy consumption of the sensor nodes closer to the base station is, the more unbalanced the energy consumption of the whole network is. In recent years, much attention has been paid to research on a wireless chargeable sensor network movement data collection method based on an offline model in the field.
The mobile data collection effectively solves the problem of unbalanced energy consumption in the network and effectively prolongs the service life of the network. Researchers have proposed different mobile data collection methods in succession for different problems, such as: wang et al, in the article of Extending the life time of wireless sensor networks through mobile relays, studied that there are some sensor nodes that can move in the network, these nodes have more energy than stationary sensor nodes and can be used as relay nodes to lighten the heavy load relay nodes, designed the moving and routing algorithm and greatly lengthened the life-span of the network; gatzianas et al in A Distributed optimized Algorithm for maximum Life Routing in Sensor Networks with Mobile Sink, by using a Mobile base station, designed a Distributed maximum life time Routing Algorithm, which comprehensively considers the energy limit of each Sensor; miao et al in "Joint mobile energy regeneration and data supply in wireless rechargeable sensor networks" for the first time combine data collection and energy replenishment, and perform mobile data collection and charging on the network through SenCar, and select the part of sensor nodes with the least residual energy as anchor points to let SenCar dock, and the problem is converted into the problem of network utility maximization, and the utility function is an increasing function of data collection amount. According to the method, constraint conditions are obtained through flow conservation, energy conservation and link capacity limitation, the problem of network utility maximization is converted into three subproblems through a mathematical method such as Lagrange dual separation, the subproblems are proved to be convergent, an optimal solution can be approached through iteration, and therefore the method for collecting mobile data in the wireless chargeable sensor network is provided.
Since wireless charging is not considered in most of previous researches, the mobile data collection uses the mobile device to collect data in the network, the mobile device can be provided with the wireless charging device at the same time, the network is supplemented with energy while data collection, and a small part of researches consider that although the network is supplemented with energy, the collected data generated by each sensor node in the network cannot ensure that the residual energy of the sensor nodes in the network is not lower than a normal working value.
Disclosure of Invention
The invention aims to provide a wireless chargeable sensor network mobile data collection method based on an offline model aiming at the defects that the existing wireless chargeable sensor network data collection method can not ensure that the data of each sensor node in the network is collected and the residual energy of the sensor nodes in the network is not lower than a normal working value, and the like, so that the data generated in the last period of each sensor node in the network can be collected in each period, and the residual energy of the sensor nodes in the network can not be lower than the normal working value.
In order to achieve the above purpose, the present invention designs a scheme combining wireless charging and mobile data collection. The scheme mainly comprises an offline data collection model, anchor point selection, path planning and the like.
The technical scheme for solving the technical problem comprises the following concrete implementation steps:
step1: deploying a wireless chargeable sensor network
1-1, randomly deploying N chargeable sensor nodes in an area to be monitored, and forming a network by each sensor node through a self-organizing network.
1-2, setting the position of the base station, and initializing configuration information of all sensor nodes, such as battery capacity, communication link capacity and maximum service hop count of the sensor nodes.
1-3, the base station acquires the residual energy of the sensor nodes in the network and the topological graph of the network.
Step2: selecting anchor points
2-1 classifying the sensor nodes in the network according to the residual energy, wherein the residual energy is EminTo 10% is the first level, 10% to 20% is the second level, 20% to 30% is the second level, and so on.
And Step2, selecting the sensor node with the lowest residual energy level as an anchor point, and selecting the sensor node with the least energy consumption for acquiring unit data as the anchor point under the condition that the residual energy levels are the same. The energy consumed by each sensor node to obtain unit data is calculated as follows:
1) and calculating the data amount cached by all the sensor nodes within the maximum service hop count of the sensor nodes.
2) And calculating the energy consumed by the sensor node for collecting data within the maximum service hop count when the sensor node is selected as the anchor point. Gathering energy consumed by the data includes energy consumed by the sensor nodes receiving the data and energy consumed by the sensor nodes transmitting the data. For example, a sensor node s is two hops away from the sensor node, and a sensor node is arranged in the middle of the sensor node s as a relay node, when the sensor node is selected as an anchor point, the energy consumed by the sensor node s for transmitting data cached by the sensor node s to the anchor point includes the energy consumed by the sensor node s for transmitting the cached data, the relay node receives the energy consumed by the cached data, the relay node transmits the energy consumed by the cached data, the anchor point receives the energy consumed by the cached data, and the anchor point transmits the cached data to the energy consumed by the SenCar.
3) The energy consumption ratio is the data amount which is the energy consumed for obtaining the unit data.
Step3 prediction of a potential death node asThe special anchor point gets a charging opportunity. During network operation, it may occur that the remaining energy is lower than EminThe sensor nodes are selected as special anchor points in advance to obtain charging opportunities, and at the beginning of a certain cycle, if the residual energy of the sensor nodes is subtracted by the maximum energy consumption of the cycle, the residual energy is subtracted by EminAnd if the energy consumption value is less than the energy consumption value of the self-monitoring event of the sensor node in one period, the node is selected as the special anchor point. The energy consumption of the sensor node includes energy consumption of the sensor node itself monitoring event, energy consumption of transmitting data, and energy consumption of transmitting data, wherein the energy consumption of the sensor node itself monitoring event is constant in the offline model, and the energy consumption of transmitting or receiving data is proportional to the amount of data transmitted or received. The difference between the transmitted data amount and the received data amount is the data amount generated by the sensor node itself, and in the offline model, the data amount of the part is also constant. The maximum energy consumption corresponds to the maximum data volume, so that the maximum energy consumption can be calculated only by knowing the maximum data receiving volume of the sensor node in the period. The maximum data receiving quantity of the sensor node in the period is calculated as follows:
1) and calculating the shortest hop count between any two sensor nodes in the network.
2) If sensor node SiAnd a sensor node SjThe shortest hop count between is h1Sensor node SjAnd the shortest hop count of anchor point is h2Sensor node SiAnd the shortest hop count of anchor point is h3。
3) If h1+h2＝h3Then sensor node SiThe generated data may pass through the sensor node SjTransmitting, sensor node SiThe resulting data is incorporated into the sensor node SjThe data reception amount of (2).
Step4: the anchor selected in step2 can serve the entire network, and therefore the selected potential dead node (special anchor) is sure to belong to the anchor. And setting the service hop count of the special anchor point as the service hop count of the anchor point minus the shortest hop count between the anchor point and the special anchor point.
And step3: access path planning
Step1, finding a path of travel trader for the anchor point by using the heuristic method of the nearest neighbor point method.
Step2, inserting special anchor points (death nodes) into the path of the station traveler, wherein each special anchor point belongs to at least one anchor point, and after inserting the special anchor points into the anchor points, accessing the special anchor points first and then the anchor points to which the special anchor points belong, if a plurality of special anchor points exist in the maximum service hop count of the anchor points, finding a Hamilton path for the special anchor points first, and then accessing the Hamilton path.
Step3 the traveler path is divided into a set of access paths according to the restrictions of SenCar battery capacity and access time. In the dividing process, it is also ensured that the special anchor (possibly dead node) and the anchor to which the special anchor belongs are in the same access path and cannot be divided into different access paths, that is, in the dividing process, the special anchor (possibly dead node) and the anchor to which the special anchor belongs are inseparable.
Step4 assignment of access path sets to SenCars, the assignment problem can be translated into a one-dimensional binning problem, which has been proven to be a NP-hard problem, designed to be solved by heuristic algorithms. And sequencing the access paths in the access path set from small to large according to the time required by the SenCar for completing, sequentially allocating the sequenced access paths to the SenCar, and allocating the access paths to the next SenCar if the accumulated time exceeds a period interval T.
The invention has the beneficial effects that:
1. the invention adopts an off-line model, namely the data generation rate and the energy consumption rate of the sensor nodes are considered to be constant, and the base station can predict the residual energy of the sensor nodes. A centralized scheme is conveniently designed under an offline model, and the network overall situation can be considered.
2. The invention adopts the anchor points as the stop points of the sensor nodes, and the designed anchor point selection scheme can ensure that the selected anchor points can serve the whole network and can collect the data generated by each sensor node in the network, thereby avoiding missing events in the network within a certain period of time.
3. The invention selects the nodes which are possibly dead in advance as the special anchor points to obtain the opportunity of charging, thereby ensuring that the dead sensor nodes can not appear in the running process of the network. If the sensor node is dead, the events in the monitoring area of the sensor node cannot be acquired. The invention is suitable for the environment with higher requirement on network monitoring.
4. The invention seeks a traveler path for the anchor point, so that the cost of SenCar on the road is as low as possible. And the route of the traveling salesman is divided, and the divided access route can be distributed to SenCar as few as possible through a greedy strategy.
Drawings
FIG. 1 is a schematic diagram of mobile data collection for a wirelessly rechargeable sensor network as utilized by the present technology;
FIG. 2 is a schematic diagram of anchor point selection according to the present invention;
FIG. 3 is a diagram illustrating the calculation of maximum data transfer according to the present invention;
FIG. 4 is a diagram illustrating the setting of service hop counts for a particular anchor according to the present invention;
FIG. 5 is a schematic diagram of the calculation of traveler paths for anchor points according to the present invention;
FIG. 6 is a schematic diagram of the present invention inserting a special anchor point into a traveler path;
FIG. 7 is a schematic diagram illustrating the present invention dividing a traveler path into a set of access paths;
FIG. 8 is a detailed flow chart of the present technique.
Detailed Description
Referring to fig. 1, a schematic diagram of mobile data collection is shown, in which the wireless rechargeable sensor network adopted by the technology of the present invention is: n sensor nodes are randomly deployed in an L multiplied by L monitoring area, and base stations are placed at the edge of the monitoring area. The sensor node is powered by a battery, the communication radius is R, and the communication link capacity is C. SenCar is powered by a large-capacity battery, has limited power, and is equipped with charging and data collection devices, so that data collection can be carried out on a certain sensor node at a certain moment and the sensor node can be charged. When the SenCar stops at a certain sensor node, a TTL (TTL is an abbreviation of Time To Live, which refers To a survival hop count of the message) message can be sent To the sensor node, and other sensor nodes in the node hop can transmit data To the SenCar through the node. SenCar returns the base station and can change the battery, and the time of changing the battery is negligible. SenCar returns to the base station and will give the data that collect to the base station, contains the electric quantity consumption rate of sensor node in the data that submit, and the base station can accurate prediction sensor node's remaining capacity. Each time SenCar starts from the base station, the base station will instruct SenCar the anchor points and the sequence to be visited this time.
The technology mainly comprises three parts of an offline data collection model, anchor point selection and path planning:
an offline data collection model:
the offline model considers the energy consumption rate of the sensor network to be constant. Once the energy consumption rate of the sensor node is determined and fixed, the data generation rate of the sensor node is also determined. The base station can accurately know the residual energy and the data accumulation amount of each sensor node in the network according to historical data, and can arrange that SenCar accesses anchor points in the network according to a certain sequence.
Selecting an anchor point:
the anchor selection can ensure that the selected sensor nodes can serve the whole network. Taking fig. 2 as an example, each circle represents a sensor node, the number in the circle is the sensor node number, the number beside the sensor node is the remaining energy percentage, the parenthesis represents the data volume generated in the previous cycle, i.e., the data volume to be collected in the present cycle, and the unit of the data volume is M. Now assume that the sensor node can serve 3 hops at most as an anchor point, accepting data within 3 hops. For convenience of discussion, it is assumed that 1J of power is consumed for transmitting or receiving 1M of data. The anchor point selection algorithm preferentially selects the sensor node with the lowest residual electric quantity grade as the anchor point, and the electric quantity grades of the No. 2 sensor node and the No. 7 sensor node in the graph are both the first grade. The amount of power consumed to obtain the unit data is then calculated. If sensor node No. 2 is selected as the anchor, the power consumption for acquiring unit data is 2.37J/M, and if sensor node No. 7 is selected as the anchor, the power consumption for acquiring unit data is 2.75J/M. Since the number 7 sensor node is selected as the anchor point, the data amount obtained is 2.6M + (2M +3M) + 2.6M-10.2M. Since it is assumed that 1J of power is consumed for transmitting or receiving 1M of data, the power consumed in three hops is 2.6J (data of the sensor node No. 7 only needs to be transmitted to SenCar) + (2J +3J) × 3 (data of the node No. 6 and the node No. 8 are transmitted to the node No. 7 first, the node No. 7 receives data once, the node No. 7 transmits data to SenCar) +2.6J 4 (data of the node No. 9 is transmitted to the node No. 8 first, the node No. 8 receives data once, then transmits data to the node No. 7, and the node No. 7 receives data once and then transmits data to SenCar) — 28J. Therefore, the power consumption for acquiring the unit data is 28J/10.2M-2.75J/M. Similarly, sensor No. 2 can be used as an anchor, and the power consumption for acquiring unit data is 2.2J + (2.8J +2J) × 3]/7M ═ 2.37J/M, so sensor No. 2 node is selected as the anchor. Sensor node No. 2 is selected as the anchor point and sensor node No. 2 is removed from the network along with those nodes served by sensor node No. 2. And after the removal, recalculating the power consumption of each sensor node in the network for acquiring the unit data, and selecting the next anchor point until the selected anchor point can serve the whole network.
And meanwhile, the potential death nodes are selected in advance to serve as special anchor points, so that the sensor nodes in the network cannot die. In the offline model, knowing the maximum data transfer volume allows knowing the maximum energy consumption and thus whether the sensor node is likely to die. As shown in fig. 3, the shortest hop count between the circular node and the quadrangular node, the shortest hop count between the quadrangular node and the triangular node, and the shortest hop count between the circular node and the triangular node are shown. If h is1+h2＝h3It is considered that the data generated by the circular node may be transmitted to the anchor point (triangle node) through the four-corner node, and thus the data is added when calculating the maximum data transmission amount of the four-corner node. By analogy, the maximum data transmission quantity of the quadrangle node can be calculated. The maximum data transmission amount minus the data generation amount of the sensor node is the maximum data receiving amount, so that the maximum energy consumption of the quadrangle node can be known. Possibly dead node acts asFig. 4 shows the service hop count for a special anchor point, where the service hop count of the anchor point is h, the shortest hop count of a possible dead node and the anchor point is h ', and the service hop count of the special anchor point is h-h'.
Path planning:
the invention first asks for a traveler path for an anchor point, if there is a network as shown in fig. 5. The triangles in fig. 5 represent anchors and the tetragons represent potential death nodes (special anchors). The path indicated by the arrow in fig. 5 is the anchor traveler path. Next, inserting possible dead nodes (special anchor points) into the path of the traveler, wherein each possible dead node belongs to at least one anchor point, before inserting the possible dead nodes into the anchor points, accessing the possible dead nodes first, then accessing the anchor points to which the possible dead nodes belong, if a plurality of possible dead nodes exist in the service hop count of the anchor points, firstly searching a Hamilton path for the possible dead nodes, and then accessing the Hamilton path. The potential dead nodes in fig. 5 are inserted into the traveler path as shown in fig. 6.
After the traveler path is obtained, the traveler path is divided into access path sets according to the energy limit of SenCar. That is, the divided access path ensures that the energy consumption of the SenCar per pass is not larger than the battery capacity of the SenCar, that is, the divided access path allows the SenCar to service one pass, and the SenCar will not die in the middle. In the dividing process, it is also ensured that the possible dead node (special anchor) and the anchor to which the possible dead node belongs are in the same access path and cannot be divided into different access paths, that is, in the dividing process, the possible dead node (special anchor) and the anchor to which the possible dead node belongs are inseparable. The division into three access paths in the example of fig. 6 is shown in fig. 7.
The specific flow chart of the invention is shown in fig. 8.
Claims (4)
1. A wireless chargeable sensor network mobile data collection method based on an off-line model is characterized by comprising the following steps:
step1: deploying a wireless chargeable sensor network
1-1, randomly deploying N chargeable sensor nodes in an area to be monitored, and forming a network by each sensor node through a self-organizing network;
1-2, setting the position of a base station, and initializing configuration information of all sensor nodes;
1-3, a base station acquires the residual energy of a sensor node in a network and a topological graph of the network;
step2: selecting anchor points
2-1 classifying the sensor nodes in the network according to the residual energy, wherein the residual energy is EminThe first grade is 10 percent, the second grade is 10 percent to 20 percent, the third grade is 20 percent to 30 percent, and the like;
2-2, selecting the sensor node with the lowest residual energy level as an anchor point, and selecting the sensor node with the lowest energy consumption for acquiring unit data as the anchor point under the condition that the residual energy levels are the same; the energy consumed by each sensor node to obtain unit data is calculated as follows:
2-2-1, calculating the data volume cached by all the sensor nodes within the maximum service hop count of the sensor nodes;
2-2-2, calculating the energy consumed by the sensor node due to data collection within the maximum service hop count when the sensor node is selected as an anchor point; collecting energy consumed by the data comprises energy consumed by the sensor nodes for receiving the data and energy consumed by the sensor nodes for transmitting the data; specifically, the method comprises the following steps: the sensor node s is two hops away from the sensor node, a sensor node is arranged in the middle of the sensor node s and serves as a relay node, when the sensor node is selected as an anchor point, the energy consumed by the sensor node s for transmitting the data cached by the sensor node s to the anchor point comprises the energy consumed by the sensor node s for transmitting the cached data, the relay node receives the energy consumed by the cached data, the relay node transmits the energy consumed by the cached data, the anchor point receives the energy consumed by the cached data, and the anchor point transmits the cached data to the energy consumed by the SenCar;
2-2-3, the data quantity in the energy consumption ratio is the energy consumed by obtaining unit data;
2-3, predicting death nodes to be used as special anchor points to obtain charging opportunities;
during the operation of the network, the residual energy is lower than EminSensor node of, below EminThe sensor node is selected as a special anchor point in advance to obtain the opportunity of charging, and at the beginning of a certain cycle, if the residual energy of the sensor node is subtracted by the maximum energy consumption of the cycle and E is subtractedminIf the energy consumption value is less than the energy consumption value of the self-monitoring event of the sensor node in one period, the node is selected as a special anchor point; the energy consumption of the sensor node comprises the energy consumption of the self-monitoring event of the sensor node, the energy consumption of transmitting data and the energy consumption of transmitting data, wherein the energy consumption of the self-monitoring event is constant in an offline model, and the energy consumption of transmitting or receiving data is in direct proportion to the amount of the transmitted or received data; the difference value between the transmitted data volume and the received data volume is the data volume generated by the sensor node, and in the offline model, the data volume of the part is also constant; the maximum energy consumption corresponds to the maximum data volume, so that the maximum energy consumption can be calculated only by knowing the maximum data receiving volume of the sensor node in the period; the maximum data receiving quantity of the sensor node in the period is calculated as follows:
2-3-1, calculating the shortest hop count between any two sensor nodes in the network;
2-3-2. if sensor node SiAnd a sensor node SjThe shortest hop count between is h1Sensor node SjAnd the shortest hop count of anchor point is h2Sensor node SiAnd the shortest hop count of anchor point is h3；
2-3-3. f.h1+h2＝h3Then sensor node SiThe generated data passes through the sensor node SjTransmitting, sensor node SiThe resulting data is incorporated into the sensor node SjThe data reception amount of (2);
2-4, the anchor points selected in the step2 can serve the whole network, so that the selected death nodes are definitely within the service range of a certain anchor point selected in the step 2; setting the service hop count of the special anchor point as the service hop count of the anchor point minus the shortest hop count between the anchor point and the special anchor point;
and step3: access path planning
3-1, solving a travel quotient path for the anchor point by using a heuristic method of a nearest neighbor point method;
3-2 inserting special anchor points into a route of a traveling salesman, wherein each special anchor point at least belongs to one anchor point, and accessing the special anchor point first and then accessing the anchor point to which the special anchor point belongs, if a plurality of special anchor points exist in the maximum service hop number of the anchor points, firstly solving a Hamilton route for the special anchor points, and then accessing the Hamilton route;
3-3 dividing the traveler path into access path sets according to the restrictions of SenCar battery capacity and access time; in the dividing process, the special anchor point and the anchor point which the special anchor point belongs to are ensured to be in the same access path and cannot be divided into different access paths, namely, in the dividing process, the special anchor point and the anchor point which the special anchor point belongs to are inseparable;
3-4, allocating the access path set to SenCars, wherein the allocation problem can be converted into a one-dimensional boxing problem which is proved to be an NP-hard problem, and a heuristic algorithm is designed to solve the problem; and sequencing the access paths in the access path set from small to large according to the time required by the SenCar for completing, sequentially allocating the sequenced access paths to the SenCar, and allocating the access paths to the next SenCar if the accumulated time exceeds a period interval T.
2. The method of claim 1, wherein the method comprises:
in order to calculate the energy consumption for acquiring unit data, the shortest hop count and the energy consumption required by each sensor node in the local range to transmit data to SenCar are calculated in turn.
3. The method of claim 1, wherein the method comprises: in order to predict dead nodes in advance, the maximum energy consumption of the sensor nodes in the current period needs to be known in advance, and the maximum energy consumption corresponds to the maximum data transmission amount; the data of other sensor nodes are required to be known for calculating the maximum data transmission quantity; and according to the characteristic of the shortest hop count transmission data, judging the maximum data transmission quantity of the sensor nodes by calculating the shortest hop count between any two sensor nodes.
4. The method of claim 1, wherein the method comprises: in step3, in order to complete the access to the anchor point by using the least SenCar, a traveler path is calculated for the anchor point, and a special anchor point is inserted into the traveler path; then dividing the path of the traveling salesman into an access path set; and a greedy policy is designed to assign the set of access paths to the fewest sencars.
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