CN103974370A - Wireless body area network routing method based on instantaneous difference learning - Google Patents
Wireless body area network routing method based on instantaneous difference learning Download PDFInfo
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Abstract
The invention provides a wireless body area network routing method based on instantaneous difference learning. According to the method, on the basis of instantaneous difference energy prediction, by the combination of a DSR protocol, communication routing of a wireless body area network is finished. Due to the fact that the state of human body nodes in the wireless body area network is scattered, the network is a small network, energy prediction is conducted on neighbor nodes through an instantaneous algorithm, rest energy of the nodes is taken into consideration, energy consumed by the nodes to send certain bit information is also taken into consideration, and based on energy prediction on surrounding nodes, the tendency of routing selection is achieved. According to the method, the life cycle of the wireless body area network can be effectively prolonged, and overall energy consumption of the wireless body area network is reduced.
Description
Technical field
The present invention relates to a kind of wireless body area network method for routing, mainly utilize instantaneous point of poor study to solve the energy efficiency problem that improves wireless body area network, belong to the interleaving techniques application of wireless body area network, machine learning.
Background technology
Along with the development of wireless sensor network, the frequency that small portable sensor device occurs in daily life is more and more frequent, small-/medium-sized Intranet has also attracted increasing people's concern and use, and academia and various circles of society have also given extensive concern to wireless body area network.Why wireless body area network can obtain popular favor, stems from its microminiaturized equipment and wireless body area network and has intelligent processing method, and researcher is also progressively promoting for the research interest of wireless body area network.Wireless body area network is placed in human body surface or inside of human body by various microsensor device exactly, and for the each moment situation of monitoring human, daily routines, amusement, sports and all kinds of different field to our future all will have far-reaching influence.
Chinese scholars has dropped into a large amount of time and energy for the study and the research that strengthen learning algorithm at present, have at present the algorithm of most of maturation, comprising dynamic programming algorithm, Q learning algorithm, instantaneous point of difference algorithm and Markovian decision process etc.Strengthening study is exactly so a kind of mode of learning, it be one by with constantly being fed back alternately of environment, thereby continuous trial and error finally finds the process of optimal solution.By investigation domestic and foreign literature, find the routing algorithm in relatively more close with wireless body area network wireless sense network and wireless self-organization network, much all relate to instantaneous point of difference algorithm,
Wireless body area network energy constraint, how averaging network energy loss, becomes only energy efficient utilization the most important thing of wireless body area network research field.Instantaneous point poor, and to strengthen learning algorithm be the algorithm based on forecasting type, applied in wireless body area network, and variation that can sensing network energy, is in these years being paid close attention to by numerous researchers.
For energy loss problem in wireless body area network, the present invention has designed the method for routing based on instantaneous point of poor study, utilize the forecast assessment ability of instantaneous point of difference algorithm, set up the remaining energy mechanism to human body sensor network adjacent node, in order to predict the energy consumption of neighbor node, according to prediction, select optimal path, thereby reduction energy consumption, the life cycle of prolongation body area network network.Instantaneous point of difference algorithm combines the advantage of dynamic programming algorithm and other enhancing learning algorithms, and in the application of wireless body area network, abandoned the inadaptability of these two kinds of algorithms in wireless body area network.Dynamic programming algorithm needs environmental model, and in human body environment, environmental model is not unalterable, and wireless planning algorithm only meets the particular case with network, cannot meet for the universality of body area network, this enhancing learning algorithm of Dynamic Programming can strengthen the delay that wireless body area network network route sends, because the method needs the end of waiting for study just can carry out the study of a new round in the process of study, instantaneous point of difference algorithm caught up with and stated two kinds of method differences, make up the defect of above two kinds of algorithms in wireless body area network Design of Routing Protocol, it can not need to predict surrounding environment and learn, do not need to wait for yet one take turns study after just carry out self study, can learn at any time, that is to say that instantaneous point of difference algorithm is a kind of study of multistep accumulation, and have the turntable simultaneously carrying out, be instantaneous point of poor study.The step number of the parameter representative study in instantaneous point of difference algorithm, from the angle of wireless body area network network, object is to be to reduce the prediction of making under different time state with actual gap, makes prediction more accurate.Instantaneous point of difference algorithm comprised instantaneous point of difference algorithm of form and instantaneous point of difference algorithm of value function approximation.
Summary of the invention
Technical problem: wireless body area network node is generally wanted monitoring human situation, such as blood pressure, body temperature, pulse etc., but the general power supply of node is limited, once depleted of energy, the significant data of human body can not get effective transmission, so route planning is one of very important network design issue efficiently, the object of this invention is to provide a kind of wireless body area network self-organizing method for routing based on instantaneous point of poor study, address the above problem.
Technical scheme: the method for routing based on instantaneous point of poor study of the present invention can utilize at node the forecast assessment ability of instantaneous point of difference algorithm, set up the remaining energy mechanism to human body sensor network adjacent node, in order to predict the energy consumption of neighbor node, according to prediction, select optimal path.
Wireless body area network method for routing step based on instantaneous point of difference of the present invention is as follows:
Step 1: user is at human body deploy aggregation node and sensor node, in sensor node, specify the source node that need to send human body message, on each sensor node the numbering of pre-stored its neighbours' sensor node and position, to the communication energy consumption value of neighbours' sensor node, user's fixed time threshold value T
1, in aggregation node and sensor node, between adjacent node, communicate and shake hands at time threshold T
1interior confirmation wireless channel is unobstructed, and each node builds routing table and successful communication handshake adjacent node is put in this routing table.Described communication handshake is the process that sends mutually message authentication wireless communication link in wireless body area network between receiving node and sending node.
Step 2: the period of time T that source node is specified according to user
2collect human body message, after each time cycle, source node starts to aggregation node transmission human body message, and source node checks the available route whether having to adjacent node in routing table, if do not had, network quits work; If exist and only have a paths, so directly transmitting human body message with this paths as transmission channel; If exist and have two with upper pathway, source node is obtained an optimal path by repeated execution of steps 5 to step 8, human body message is sent to adjacent node by this optimal path, and then repeated execution of steps 3 and step 4, until human body message successfully arrives aggregation node.
Step 3: sensor node is received after the human body message that source node or neighboring sensors node send, and checks the available route whether having to adjacent node in routing table, if do not had, network quits work; If exist and only have a paths, so directly transmitting human body message with this paths as transmission channel; If exist and have two with upper pathway, source node is obtained an optimal path by repeated execution of steps 5 to step 8, and human body message is sent to adjacent next-hop node by this optimal path.
Step 4: aggregation node is received the human body message that source node or neighboring sensors node send, and the message collection of one-period human body and transformation task finish.
Step 5: user specifies the primary power of any one sensor node to consume E
0=0, first cycle node consumed energy is E
1=EC
1, it is the energy value E of required consumption that source node or sensor node calculate each neighbor node reception human body message in routing table
k+1=E
k+ α (EC
k+ γ E
k+1-E
k), k=1,2 ..., described EC
1real energy loss value of first cycle of representation node, E
k+1representing that people's body node is at T
k, (k+1)the result that the k+1 time energy predicting carrying out of this cycle obtains, EC
krepresent T
k-1, kreal energy loss value of this cycle, α is the learning parameter of instantaneous point of difference, α ∈ (0,1), γ is an important parameter, represent iterations, γ is less, and execution efficiency is higher, λ ∈ [0,1], source node or sensor node notice neighbor node send its residual energy value and send to source node subsequently.
Step 6: source node or sensor node pass through
Calculate the energy consumption of each neighbor node in routing table, described R
k+1that sensor node is at T
k, (k+1)the residual energy value of the prediction in this cycle, R
0the prediction residual energy value of representation node within first cycle, E
k+1representing that people's body node is at T
k, (k+1)the result that the k+1 time energy predicting carrying out of this cycle obtains, E
0it is primary power value.
Step 7: source node or sensor node calculate the prediction proportion of goods damageds of each neighbor node in routing table
the true proportion of goods damageds
described E
krepresenting that people's body node is at T
(k-1), kthe result that the k time energy predicting carrying out of this cycle obtains, R
kthat human body sensor node is at T
(k-1), kthe residual energy value of the prediction in this cycle, EC
krepresent T
k-1, kreal energy loss value of this cycle, RC
kthat human body sensor node is at T
(k-1), kthe real residual energy value in this cycle.
Step 8: source node or sensor node calculate the prediction proportion of goods damageds of each neighbor node in routing table and the difference of the true proportion of goods damageds, tunes up parameter alpha if this difference is greater than the threshold value of user's appointment, enters step 5; If this difference is not more than the threshold value that user specifies, source node or sensor node select a neighbor node of difference minimum as the next-hop node of human body transmission of messages, determine that source node or sensor node send the current optimal path of human body message.
Beneficial effect: the present invention proposes a kind of wireless body area network self-organizing method for routing based on instantaneous point of poor study.The method for routing that the application of the invention proposes is realized the optimum path search of wireless body area network, namely utilize instantaneous point of poor energy predicting method to predict nodal information, make its designed wireless body area network self-organizing method for routing based on instantaneous point of poor study can finely must solve energy in network and consume inhomogeneous problem, thereby extend network life cycle.Specifically, method of the present invention has following beneficial effect:
(1) the wireless body area network self-organizing method for routing based on instantaneous point of poor study of the present invention, can reach and solve well energy in network and consume inhomogeneous problem, saving network energy.
(2) the wireless body area network self-organizing method for routing based on instantaneous point of poor study of the present invention, predicts neighbor node energy, by tuning up parameter, makes predicted value constantly approach actual value, thus realizing route optimizing.
(3) the wireless body area network self-organizing method for routing based on instantaneous point of poor study of the present invention, the routing algorithm that adopts instantaneous point of poor study mechanism to propose, in path optimizing process, energy consumption and dump energy to path are optimized, make source node less to the energy of loss on destination node path, balanced network energy consumption, has delayed time of node failure greatly, thereby extend network life cycle, improved the ability of network self-adapting.
Brief description of the drawings
Fig. 1 is the concrete implementing procedure schematic diagram of wireless body area network method for routing based on instantaneous point of poor study,
Fig. 2 is people's body node schematic diagram.
Embodiment
For a more detailed description to the present invention according to drawings and embodiments below.
The present invention proposes a kind of wireless body area network method for routing based on instantaneous point of poor study, and the concrete implementing procedure of the method as shown in Figure 1.The specific embodiment of the present invention is:
First stage: route initial phase
The peripherad neighbor node of node that is positioned at human body waist sends learning training information, starts path process of establishing.As node i sends learning training bag to neighbor node j, also can be called energy information bag, in this bag, contain dump energy and the specific energy loss of node i.In order to solve energy information packet loss or out-of-date situation, in issuing the energy information bag of node j, node i adds a time sequence number, representing the priority of the transmitting time of this bag, in the time that the time that node j receives, sequence number was incorrect, can feed back to node i, requirement resends energy information bag, and packet loss phenomenon has occurred in this situation explanation; Want Zao when the time sequence number that node j receives than the time sequence number of receiving before, illustrate that this bag is out-of-date, this energy information bag will be dropped; Only have the node j of working as to receive an energy information bag with entirely true time sequence number, can send and confirm that bag is to node i, node i no longer resends energy information bag.
Second stage: energy predicting stage
In the energy predicting stage, the energy value that some neighbor node j that can computing node i consume at certain one-phase, then calculates the residual energy value after neighbor node j a period of time.
Suppose human body node diagram as shown in Figure 2, all nodes are carried out to label, be positioned at the node 14 of waist as aggregation node, its neighbor node comprises node 24, node 13, node 10, node 11 and node 20, aggregation node can be predicted the energy consumption of these nodes, the like, this neighbor node also has the neighbor node of self, can predict equally the energy consumption of node.Taking node 13,10 prediction nodes 9 as example, concrete steps are as follows:
Step 1) be positioned at node 14 broadcasts of human body waist, the route of each node is set up substantially, definition energy information bag, each node sends energy information bag to neighbor node, successively by flag bit energy information bag 1, energy information bag 2 ... etc., at T
k-1, k sends k energy information bag period, and node 13, node 10 send an energy information bag to node 9, and node 9 is received that confirmation of rear reply is wrapped and is stated two nodes.An energy information table is being deposited in each node this locality.
Step 2): node 9,10,13 calculates the value of the dump energy that node will have in next round separately according to TD energy predicting, and by following formula calculation error.Error is the difference of predicted value and actual value.
Step 3): the percentage that the actual energy consumption of comparison node and predict energy consume, if this value is less than threshold value d, carry out the prediction of next round, if this value is greater than threshold value, so just tune up α value, make the specific energy loss of prediction more approach current specific energy loss.
Phase III: Route establishment and maintenance phase
DSR route is revised according to above-mentioned two stages, each node has increased energy information table, energy-optimised being expressed as in data transmission procedure, when source node sends message to destination node, first source node checks in routing table cache, whether there is the available route to destination node, if do not had, route requests is initiated in broadcast request, if exist and only have a paths, so just directly use the passage of this paths as transmission of messages, and do not consider the energy consumption in this path, in order to reduce time delay, if having two or above path predicts the energy consumption of neighbor node by the method for instantaneous point of poor energy predicting, thereby selection optimal path.
Claims (1)
1. the wireless body area network method for routing based on instantaneous point of poor study, is characterized in that the step that the method comprises is:
Step 1: user is at human body deploy aggregation node and sensor node, in sensor node, specify the source node that need to send human body message, on each sensor node the numbering of pre-stored its neighbours' sensor node and position, to the communication energy consumption value of neighbours' sensor node, user's fixed time threshold value T
1, in aggregation node and sensor node, between adjacent node, communicate and shake hands at time threshold T
1interior confirmation wireless channel is unobstructed, and each node builds routing table and successful communication handshake adjacent node is put in this routing table; Described communication handshake is the process that sends mutually message authentication wireless communication link in wireless body area network between receiving node and sending node;
Step 2: the period of time T that source node is specified according to user
2collect human body message, after each time cycle, source node starts to aggregation node transmission human body message, and source node checks the available route whether having to adjacent node in routing table, if do not had, network quits work; If exist and only have a paths, so directly transmitting human body message with this paths as transmission channel; If exist and have two with upper pathway, source node is obtained an optimal path by repeated execution of steps 5 to step 8, and human body message is sent to adjacent node by this optimal path, then repeated execution of steps 3 and step 4, until human body message successfully arrives aggregation node
Step 3: sensor node is received after the human body message that source node or neighboring sensors node send, and checks the available route whether having to adjacent node in routing table, if do not had, network quits work; If exist and only have a paths, so directly transmitting human body message with this paths as transmission channel; If exist and have two with upper pathway, source node is obtained an optimal path by repeated execution of steps 5 to step 8, and human body message is sent to adjacent next-hop node by this optimal path;
Step 4: aggregation node is received the human body message that source node or neighboring sensors node send, and the message collection of one-period human body and transformation task finish;
Step 5: user specifies the primary power of any one sensor node to consume E
0=0, first cycle node consumed energy is E
1=EC
1, it is the energy value E of required consumption that source node or sensor node calculate each neighbor node reception human body message in routing table
k+1=E
k+ α (EC
k+ γ E
k+1-E
k), k=1,2 ..., described EC
1real energy loss value of first cycle of representation node, E
k+1representing that people's body node is at T
k, (k+1)the result that the k+1 time energy predicting carrying out of this cycle obtains, EC
krepresent T
k-1,
kreal energy loss value of this cycle, α is the learning parameter of instantaneous point of difference, α ∈ (0,1), γ is an important parameter, represent iterations, γ is less, and execution efficiency is higher, λ ∈ [0,1], source node or sensor node notice neighbor node send its residual energy value and send to source node subsequently;
Step 6: source node or sensor node pass through
Calculate the energy consumption of each neighbor node in routing table, described R
k+1that sensor node is at T
k, (k+1)the residual energy value of the prediction in this cycle, R
0the prediction residual energy value of representation node within first cycle, E
k+1representing that people's body node is at T
k, (k+1)the result that the k+1 time energy predicting carrying out of this cycle obtains, E
0it is primary power value;
Step 7: source node or sensor node calculate the prediction proportion of goods damageds of each neighbor node in routing table
the true proportion of goods damageds
described E
krepresenting that people's body node is at T
(k-1), kthe result that the k time energy predicting carrying out of this cycle obtains, R
kthat human body sensor node is at T
(k-1), kthe residual energy value of the prediction in this cycle, EC
krepresent T
k-1, kreal energy loss value of this cycle, RC
kthat human body sensor node is at T
(k-1), kthe real residual energy value in this cycle;
Step 8: source node or sensor node calculate the prediction proportion of goods damageds of each neighbor node in routing table and the difference of the true proportion of goods damageds, tunes up parameter alpha if this difference is greater than the threshold value of user's appointment, enters step 5; If this difference is not more than the threshold value that user specifies, source node or sensor node select a neighbor node of difference minimum as the next-hop node of human body transmission of messages, determine that source node or sensor node send the current optimal path of human body message.
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| CN109219101A (en) * | 2018-09-21 | 2019-01-15 | 南京理工大学 | Method for routing foundation based on Double moving average predicted method in wireless body area network |
| CN109862320A (en) * | 2019-02-15 | 2019-06-07 | 苏州宏裕千智能设备科技有限公司 | Image collection and processing system and its method |
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Granted publication date: 20170329 |