CN107426804B - Auction mechanism-based energy-saving control method for wireless access point of WLAN (Wireless local area network) system - Google Patents
Auction mechanism-based energy-saving control method for wireless access point of WLAN (Wireless local area network) system Download PDFInfo
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- CN107426804B CN107426804B CN201710419853.2A CN201710419853A CN107426804B CN 107426804 B CN107426804 B CN 107426804B CN 201710419853 A CN201710419853 A CN 201710419853A CN 107426804 B CN107426804 B CN 107426804B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0203—Power saving arrangements in the radio access network or backbone network of wireless communication networks
- H04W52/0206—Power saving arrangements in the radio access network or backbone network of wireless communication networks in access points, e.g. base stations
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- 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
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- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a wireless Access Point (AP) energy-saving control method in a wireless local area network system, belonging to the technical field of communication. The scheme mainly adopts an AP dormancy-awakening energy-saving mode, selects dormant APs based on network real-time sensing data, optimizes the new AP access selection problem when users on the dormant APs unload through an access AP selection algorithm of reverse auction, and achieves optimization of energy consumption of a WLAN system. Firstly, measuring the energy consumption of AP equipment, and determining an AP dormancy-awakening threshold value through analyzing the marginal effect of the energy consumption; then, sensing the network load state in real time through a central controller to obtain an association matrix of the user and the AP, and establishing a relation model between energy consumption, coverage, user QoE and AP selection; and finally, completing the access selection of the user to be unloaded to the new AP based on a reverse auction algorithm so as to idle the AP in the dormant system. The method can effectively reduce the energy consumption of the WLAN system brought by the redundant AP on the premise of meeting the wireless coverage and the QoE of the user.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and relates to an auction mechanism-based energy-saving control method for a wireless access point of a WLAN (wireless local area network) system.
Background
In recent years, the data traffic of mobile networks has exponentially increased, and as indicated by Cisco global data traffic prediction reports, the data traffic in 2018 is expected to be more than ten times as high as 2013. To meet the increasing demand of users for high-bandwidth and high-reliability data transmission services, operators intensively deploy a large number of wireless Access Points (APs) in public and commercial places to construct a centrally managed WLAN system. Densely deployed Wireless Local Area Network (WLAN) systems can provide efficient coverage and high bandwidth access for mobile users, with an increasing number of users selecting through the wireless access network. According to the 37 th statistical report of the development conditions of the china internet published in 2016 and 1 month by a CNNIC (china internet information center), the proportion of users accessing the internet through a Wi-Fi wireless network is 91.8% as long as 2015 and 12 months. However, the problem of network redundancy energy consumption is not considered in the dense deployment of WLAN systems, and the problem of redundancy energy consumption is increasingly prominent as the network scale is continuously enlarged. Data of a typical campus network and an Intel enterprise network shows that 20% -80% of APs are in an idle state in different periods, and energy consumption generated by AP devices accounts for 70% -80% of energy consumption of a system network. Most of wireless APs in the existing WLAN are planned according to peak flow of system users, but the system can reach a peak value only at a few moments, so that more than 60% of the APs are in a low-load or no-load full-power operation state, which causes waste of energy and resources. Therefore, when the WLAN is densely deployed, how to reduce the system energy consumption brought by the AP is of great significance to reduce the operation cost and the global green WLAN construction.
Researchers have conducted a great deal of research work in response to the above-described problem of energy waste associated with redundant APs in densely deployed WLANs. The current energy-saving scheme mainly comprises the following steps:
1. and dynamically adjusting the interval time of sending Beacon frames by the AP according to the number of connected terminals of the AP and the number of received detection messages, and reducing the number of wireless frames sent by the AP to realize energy conservation.
2. Clustering the APs in the WLAN by using the spatial geometrical positions of the APs, namely dividing the APs into different clusters according to the distance between the APs. And selecting one leading AP from the cluster, and turning off the power supplies of other APs, thereby achieving the purpose of energy conservation.
3. Analyzing the distribution characteristic of data flow obeying based on the historical data flow of the system, modeling the data flow, and giving preset parameters of a system flow estimation model according to the current data flow, so that different numbers of APs are started at different time intervals to control the capacity of the system to meet the network requirement.
4. The APs cooperate with each other, and the adjacent APs exchange information such as respective associated users, the maximum service number, the adjacent APs and the like, and then the information is screened out according to the information, which APs can be closed.
However, the existing WLAN system energy saving method mainly has the following problems:
1. the energy-saving effect of adjusting Beacon frame interval time and AP transmitting power is not obvious.
2. Due to the fact that user mobility in the network is high, the network energy efficiency management energy-saving mechanism based on clustering and historical data modeling cannot adjust the network state in real time according to the change of the user state, and the situation that user service is lost is difficult to avoid.
3. The existing energy-saving algorithm based on network load perception lacks consideration on the capacity of a single node, cannot ensure that an opened AP node can meet the requirement of a network, and lacks selection consideration when a user connected with a to-be-dormant AP reselects the AP for access.
Disclosure of Invention
The present invention is directed to solving the above problems of the prior art. The energy-saving control method for the WLAN system wireless access point based on the auction mechanism enables system energy consumption to be the lowest on the premise of guaranteeing effective network coverage and QoE of users. The technical scheme of the invention is as follows:
an auction mechanism-based energy-saving control method for a wireless access point of a WLAN system comprises the following steps:
1) determining the upper and lower load limits of the wireless access point AP of the WLAN system;
2) determining the working state of the AP by comparing the real-time load of the AP with the energy-saving upper and lower limit thresholds;
3) adopting a greedy algorithm to unload and sort the users according to the number of the associable APs of the users and the flow demand, and determining the resource allocation of an auction mechanism;
4) and determining a payment rule of an auction mechanism by adopting an improved second price mechanism, and selecting an AP (access point) with the minimum system power consumption increase for the user under the condition of meeting the data transmission rate requirement of the user.
Further, the step 1) of determining the upper and lower load limits of the wireless access point AP of the WLAN system specifically includes: the method comprises the steps of firstly, analyzing the change of the energy consumption of the AP along with the load and the packet loss rate of the AP through actual measurement data of the WLAN system to determine the upper load limit of the AP, performing regression fitting analysis on experimental data to obtain a mathematical model of the energy consumption and the load of the AP, and determining the lower load limit of the AP by using a marginal cost model.
Further, the obtaining of the mathematical model of the AP energy consumption and load by performing regression fitting analysis on the experimental data specifically includes: and constructing a discrete relation between the AP load and the energy consumption according to the actual monitoring data, analyzing by a general fitting mode and a sectional fitting mode to obtain a continuous mathematical model between the AP load and the energy consumption, and determining a load lower limit threshold of the AP by using a marginal cost model.
Further, the load value that the packet loss rate of the wireless receiving end is critical to be 1% is listed as the upper limit threshold of the load of the AP.
Further, the method for determining the AP operating state in step 2) specifically includes:
(a) the method comprises the steps that an integrated controller reads real-time load conditions of all APs in a network system;
(b) if the real-time load value of the AP is between the upper limit threshold and the lower limit threshold, the working state of the AP is not changed;
(c) if the real-time load value of the AP is lower than the lower limit threshold, the AP is listed as an AP to be dormant, and the user associated with the AP to be dormant is listed as a user to be unloaded; the processing method when the real-time load of the AP is higher than the upper limit threshold value comprises the following steps: the controller inquires the working condition of the adjacent AP of the overloaded AP and the coverage relation between the associated user and the adjacent AP; unloading part of users of the overloaded AP to the peripheral associable started APs according to the coverage relation between the started APs and the users until the load of the overloaded AP returns to the range between the upper and lower limit thresholds; if all the unloadable users complete the reassociation and the AP is still overloaded, the controller issues an instruction to awaken the adjacent dormant AP to share the users on the overloaded AP until the load of the overloaded AP returns to the range between the upper and lower limit thresholds.
Further, the AP information received and stored by the centralized controller includes the following fields: BSSID, AP serial number, current load, number of associated users, number of covered users and AP running state;
further, the AP-associated user information received and stored by the centralized controller includes the following fields: terminal MAC address, user traffic, associated AP number, terminal signal strength.
Further, the AP coverage user information received and stored by the centralized controller includes the following fields: target AP number, terminal MAC address, terminal signal strength.
Further, in step 3), resource allocation of an auction mechanism is determined by using a greedy auction algorithm, and users are sorted according to a certain rule in a manner that:
(a) the user j to be unloaded is determined according to the associable AP number | AjArranging | from small to large in sequence;
(b)|Aji users with the same are according to the current flow demand djArranged from big to small.
Further, the second lattice mechanism improved in step 104 is mainly embodied in that:
in a standard auction model summary second price bid closing auction, bidders bid secret bids, the winner is the highest bidder, the winner purchases an auction item at the second price, and the rule is not suitable in the existing network scenario, so the auction rule is designed as: the winning auction with the lowest bid price in the auction process needs to pay the next lowest bid price.
Further, the payment rule of the auction mechanism in step 4) is specifically as follows:
(a) AP for providing access network service for user to be switched by using user to be switched as buyeriAs a seller, the seller is willing to leave the remaining capacity CiTake out part or all of them for sale;
(b) utilizing cost function P, vendor APiAccording to the flow d of the user j to be unloadedjAnd the current own load l0Cost estimate v is given faithfullyijAnd use it as the tender price bijParticipating in contests, i.e. bij＝vij；
(c) When the user to be unloaded has a plurality of associatively and selectively accessed auction APs, the method is changedDetermining the AP with the lowest bid price to win the auction by a generalized second price mechanism, so that the AP benefit function of the system
Maximum, n is the total number of APs, wherein
UiIs a network interface with APiA set of all associated users;
(d) according to the second price mechanism rule, auction payment p needed to be given by the winning APijFor the medium-low bid price of the auction player, p is determined by formula (4)ij；
The invention has the following advantages and beneficial effects:
in the invention, a controller acquires load information of each AP and associated information of users and the AP in real time based on a centralized control framework, analyzes upper and lower limit thresholds of the load of the AP through actual performance data of the AP, solves the problem of selecting a new access AP of a user to be unloaded by using a reverse auction mechanism, and realizes optimization of system energy consumption by sleeping redundant APs and optimizing an associated mode of the user-AP on the premise of considering node performance and user QoE. The method of the invention not only can achieve the purpose of energy saving, but also can ensure that the user can effectively cover the loss, and reduce the negative influence on the terminal communication experience and the network service quality. The main advantages of the invention are as follows: firstly, regression analysis is carried out on measured data to obtain a mathematical relation model of AP energy consumption and load, and a load threshold value is determined by combining an economic model of marginal cost. The method is based on the actual characteristics of the AP, deeply analyzes the relation between the AP indexes, and ensures that the threshold is more scientific and reasonable to determine; secondly, the load of each node, the flow demand of the user and the real-time information related between the user and the AP, which are acquired by the controller, are used as data bases for switching on and off the AP, so that the coverage and the demand of the user can be ensured from the perspective of a terminal, and real-time and global decision can be realized; secondly, designing an auction resource allocation mode by utilizing a greedy idea, sequencing the unloading sequence of the users according to the dual conditions of the number of dormant APs and the AP flow of the terminal, greatly reducing the calculation time compared with an optimized decision mode, and effectively ensuring the maximization of the number of the dormant APs; finally, a greedy reverse auction mechanism is designed through a second closed price mechanism, so that how to re-associate unloaded users can be effectively decided, the energy consumption of the system is the lowest, and dual energy conservation of dormant AP and optimized user-AP association is realized.
Drawings
Fig. 1 is a diagram of a WLAN centralized control network architecture in accordance with a preferred embodiment of the present invention;
fig. 2 is a flow chart of a WLAN power saving method;
fig. 3 shows the variation trend of AP load and energy consumption and packet loss rate;
FIG. 4 shows fitting results of AP load versus energy consumption;
fig. 5 shows the variation trend of the AP power consumption rate and the load.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail and clearly with reference to the accompanying drawings. The described embodiments are only some of the embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
an auction mechanism-based energy-saving control method for a wireless access point of a WLAN system comprises the following steps:
step 1: the method comprises the steps of respectively applying 0-80Mbps downlink loads (namely, data flow is issued to a user associated in a wireless mode through a wired end) with 5Mbps intervals to an AP, reading actual energy consumption data P of the AP in real time through a power monitor, and simultaneously acquiring a loss rate lose _ rate in real time through packet loss rate monitoring of a wireless user end, so as to obtain a discrete relation graph of the AP load, energy consumption and loss rate as shown in fig. 3.
Step 2: fig. 3 shows that when the network load reaches 70Mbit/s, the packet loss rate of the system reaches 0.94%, and at this time, as the AP load continuously increases, the packet loss rate sharply increases, and the AP is currently connected for useThe quality of service of the user cannot be guaranteed. The method determines the maximum load value of the AP when the packet loss rate is less than 1% as an upper limit threshold value lmaxI.e. 70 Mbit/s.
And step 3: the functional relation between the AP load and the energy consumption is obtained by performing least square fitting regression analysis on experimental data. The number of data sampling points is increased from 40 to 160, each sampling point being the median of 10 measurements. The effect of the fit is shown in figure 4. The method adopts two fitting modes of general fitting and piecewise fitting, takes 40Mbit/s as a boundary, and fits the discrete data into two cubic polynomials. The functional relationship between the AP load and the energy consumption is set as follows:
wherein l represents the load of the AP, and P (l) represents the power consumption of the AP when the load is l.
And 4, step 4: the energy consumption model obtained by fitting can be obtained in the range of 0,40Mbit/s]The curve P' (l) of the AP energy consumption rate versus load variation function in the load variation region is shown in fig. 5. From fig. 5, it can be seen that the power consumption change rate of the AP shows a tendency of decreasing first and then increasing as the AP load increases, and reaches a minimum value at 20 Mbit/s. If the AP energy consumption is defined as the cost of the AP due to the increased load, the graph of the function variation relationship conforms to the marginal cost model. According to the marginal cost characteristic of AP energy consumption, the existence of a minimum value l in P' (l) can be obtainedsAnd an inflection point appears in the unit energy consumption utilization rate of the AP at the point, and the energy consumption utilization rate of the AP is lower when the load is lower than the value. Therefore, the invention determines the lower load threshold l of the APmin＝ls＝20Mbit/s。。
And 5: as shown in FIG. 1, an AP in a WLAN networkiMonitoring data flow and AP of users in coverage area, current associated users in real timeiThe current load, and at the same time, uploads this information to the controller.
Step 6: the controller constructs an information database between the AP and the user in the whole overlay network through the received network information, such as the overlay relationship Ass _ can between the AP and the user, and the association relationship between the AP and the userAss _ now, data traffic per UserjLoad AP of steam and APi_load。
And 7: load information AP of each APiLoad and AP load upper and lower limit threshold lmaxAnd lminAnd comparing to determine the working state of the AP preliminarily. If APi_load≤lminEntering step 8; if APi_load＞lmaxThen, the process proceeds to step 12.
And 8: if APi_load≤lminThen AP will beiThe columns are the FreeAPs to be dormant, such as AP3 and AP4 in FIG. 1, and the association relation Ass _ now between the AP and the user is obtainediThe associated user column is the user FreeUser to be unloaded.
And step 9: judging whether the FreeUser of the User to be unloaded can be switched to other APs and the User flow requirement is met according to Ass _ can, namely, the Userj_steam+APi_load≤lmax. If the user does not satisfy the condition, returning to the step 8 to remove the user associated AP from the FreeAP; if all users of the FreeAP meet this condition, all APs in the FreeAP meet the sleep condition.
Step 10: in order to ensure effective unloading of users as much as possible, all users in the FreeUser are subjected to unloading sequencing based on greedy thought.
Preferably, during the process of unloading users to other APs, users with fewer AP options should be satisfied first, so users in FreeUser are sorted in descending order of switchable AP number according to the data recorded in Ass _ can.
Preferably, the same switchable AP number may occur in the FreeUser, and at this time, the switching selection of the user with a large flow demand is less than that of the user with a small flow demand, so that the users with the same switchable AP number in the FreeUser are sorted in the order of the flow from large to small.
Step 11: and pre-unloading the users in the FreeUser in sequence, and selecting the AP with the maximum system profit from the plurality of switchable APs for access based on an auction mechanism in the unloading process. If the same problem occurs in the step 9 in the unloading process, returning to the step 8 to remove the user associated AP from the FreeAP; if all users are successfully unloaded, go to step 15.
Preferably, the invention provides a user switching selection method based on an auction mechanism on the basis of the selection problem of the user re-associated AP and by using an improved second price mechanism as a payment rule, and the method comprises the following specific steps:
(a) AP for providing access network service for user to be switched by using user to be switched as buyeriAs a seller, the seller is willing to leave the remaining capacity CiSome or all of them are taken out for sale.
(b) Utilizing cost function P, vendor APiAccording to the flow d of the user j to be unloadedjAnd the current own load l0Cost estimate v is given faithfullyijAnd use it as the tender price bijParticipating in contests, i.e. bij＝vij。
(c) When a user to be unloaded has a plurality of associatively and selectively accessed auction APs, the generalized second price mechanism is improved to determine the AP with the lowest bid price to win the auction, so that the system AP benefit function
Maximum (n is the total number of APs), where
(UiIs a network interface with APiThe entire set of users associated).
(d) According to the second price mechanism rule, auction payment p needed to be given by the winning APijFor the medium-low bid price of the auction player, p is determined by formula (4)ij。
Step 12: if APi_load＞lmaxI.e. APiOverload, will APiThe associated users are arranged from more to less according to the number of the associable APs to obtain a user sequence FreeUser to be unloaded, and the step 13 is entered.
Step 13: sequentially selecting the re-associated APs for the users in the FreeUser based on an auction mechanism until the load of the current overloaded AP is less than lmaxAnd returning to the step 6. If the AP is still overloaded after traversing all users, go to step 14.
Step 14: awakening the adjacent dormant AP with the loaded AP to share the user on the overloaded AP until the load of the current overloaded AP is less than lmaxAnd returning to the step 6.
Step 15: and according to the final calculation result, obtaining the switch of the AP with the maximum energy saving of the system and the re-association decision of the user, and issuing an instruction to the related AP by the controller to realize energy-saving operation.
The following describes in detail specific steps of an auction mechanism-based energy-saving control method for a wireless access point of a WLAN system with reference to fig. 2:
201: and modeling the relation between the AP load and the energy consumption according to the measured data.
202: and determining an upper limit threshold and a lower limit threshold of the AP load based on the packet loss rate of the wireless receiving end and the marginal cost effect.
203: and the controller acquires and updates the state of the AP node and the association relationship between the AP and the user in real time.
Table 1 the controller stores AP information
Table 2 the controller stores AP associated user information
Table 3 controller stores AP overlay user information
| Target AP number | User terminal MAC address | Signal strength |
| 1 | 11-22-33-44-55-77 | -32 |
204: and comparing the AP real-time load with an AP load upper and lower limit threshold. And if the AP load is between the upper limit threshold and the lower limit threshold, no processing is performed, and the AP load in the system is waited to change.
205: if the AP load is larger than the upper limit threshold, the process is switched to 206, and if the AP load is smaller than the lower limit threshold, the process is switched to 207.
206: and unloading part of users on the overloaded AP to the peripheral open AP through an auction mechanism, and if the open APs can not meet the unloading requirements of the users, opening part of dormant APs for the unloading users to access.
207: and judging whether the user associated with the AP to be dormant meets the unloading condition, if any user does not meet the unloading condition, returning to 205 and keeping the AP open state.
208: and determining an AP to be dormant and a user list to be unloaded, and sequencing the users to be unloaded.
209: and pre-switching the users to be unloaded in sequence, and if the users do not meet the unloading condition, returning to 205 and keeping the AP opening state associated with the users.
210: and determining the re-association AP of the user until all the users to be unloaded are traversed.
211: and obtaining a final AP switch and user re-association scheme, and outputting an instruction to the relevant AP by the controller to complete energy-saving operation.
The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (5)
1. A WLAN system wireless access point energy-saving control method based on auction mechanism is characterized by comprising the following steps:
1) determining the upper and lower load limits of the wireless access point AP of the WLAN system;
2) determining the working state of the AP by comparing the real-time load of the AP with the energy-saving upper and lower limit thresholds;
3) adopting a greedy algorithm to unload and sort the users according to the number of the associable APs of the users and the flow demand, and determining the resource allocation of an auction mechanism;
4) and determining a payment rule of the auction mechanism by adopting an improved second price mechanism, wherein the improved second price mechanism is as follows: in the auction process, the winning auction with the lowest bid price needs to pay the next lowest bid price; under the condition of meeting the data transmission rate requirement of a user, selecting an AP (access point) for the user, wherein the system power consumption is increased to the minimum;
the step 1) of determining the upper and lower load limits of the wireless access point AP of the WLAN system specifically comprises the following steps: firstly, analyzing the change of the energy consumption of the AP along with the load and the packet loss rate of the AP through actual measurement data of a WLAN system to determine the upper limit of the load of the AP, performing regression fitting analysis on experimental data to obtain a mathematical model of the energy consumption and the load of the AP, and determining the lower limit of the load of the AP by using a marginal cost model;
the step of performing regression fitting analysis on the experimental data to obtain a mathematical model of the AP energy consumption and the load specifically comprises the following steps: constructing a discrete relation between the AP load and the energy consumption according to actual monitoring data, analyzing by a general fitting mode and a sectional fitting mode to obtain a continuous mathematical model between the AP load and the energy consumption, and determining a load lower limit threshold of the AP by using a marginal cost model;
setting a load value with the packet loss rate of the wireless receiving end being limited to 1% as a load upper limit threshold of the AP;
in the step 3), resource allocation of an auction mechanism is determined by using a greedy auction algorithm, and users are ordered according to a certain rule, wherein the ordering mode is as follows:
(a) the user j to be unloaded is determined according to the associable AP number | AjArranging | from small to large in sequence;
(b)|Aji users with the same are according to the current flow demand djArranging in sequence from big to small;
the payment rule of the auction mechanism in the step 4) is specifically as follows:
(a) AP for providing access network service for user to be switched by using user to be switched as buyeriAs a seller, the seller is willing to leave the remaining capacity CiTake out part or all of them for sale;
(b) utilizing cost function P, vendor APiAccording to the flow d of the user j to be unloadedjAnd the current own load l0Cost estimate v is given faithfullyijAnd use it as the tender price bijParticipating in contests, i.e. bij＝vij；
(c) When a user to be unloaded has a plurality of associatively and selectively accessed auction APs, the generalized second price mechanism is improved to determine the AP with the lowest bid price to win the auction, so that the system AP benefit function
Maximum, n is the total number of APs, wherein
UiIs a network interface with APiA set of all associated users;
(d) according to the second price mechanism rule, auction payment p needed to be given by the winning APijFor the medium to low bid price of an auction player, p is determined by the following formulaij；
2. The auction mechanism-based energy-saving control method for the wireless access point of the WLAN system according to claim 1, wherein the method for determining the operating state of the AP in step 2) specifically comprises:
(a) the method comprises the steps that an integrated controller reads real-time load conditions of all APs in a network system;
(b) if the real-time load value of the AP is between the upper limit threshold and the lower limit threshold, the working state of the AP is not changed;
(c) if the real-time load value of the AP is lower than the lower limit threshold, the AP is listed as an AP to be dormant, and the user associated with the AP to be dormant is listed as a user to be unloaded; the processing method when the real-time load of the AP is higher than the upper limit threshold value comprises the following steps: the controller inquires the working condition of the adjacent AP of the overloaded AP and the coverage relation between the associated user and the adjacent AP; unloading part of users of the overloaded AP to the peripheral associable started APs according to the coverage relation between the started APs and the users until the load of the overloaded AP returns to the range between the upper and lower limit thresholds; if all the unloadable users complete the reassociation and the AP is still overloaded, the controller issues an instruction to awaken the adjacent dormant AP to share the users on the overloaded AP until the load of the overloaded AP returns to the range between the upper and lower limit thresholds.
3. The auction mechanism based WLAN system wireless access point energy saving control method of claim 2, wherein the AP information received and stored by the centralized controller comprises the following fields: BSSID, AP serial number, current load, number of associated users, number of coverage users, and AP running state。
4. The auction mechanism based WLAN system wireless access point energy saving control method of claim 2, wherein the AP associated user information received and stored by the centralized controller contains the following fields: terminal MAC address, user traffic, associated AP number, terminal signal strength.
5. The auction mechanism based WLAN system wireless access point energy saving control method of claim 2, wherein the AP coverage user information received and stored by the centralized controller contains the following fields: target AP number, terminal MAC address, terminal signal strength.
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| CN109660995B (en) * | 2018-12-07 | 2021-11-09 | 上海交通大学 | AP intelligent energy-saving control method and device in WiFi system based on machine learning algorithm |
| CN110856227B (en) * | 2019-11-19 | 2021-08-10 | 三峡大学 | Data unloading method based on greedy algorithm and reverse auction |
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