WO2020076056A1

WO2020076056A1 - Device and method for controlling traffic offloading

Info

Publication number: WO2020076056A1
Application number: PCT/KR2019/013202
Authority: WO
Inventors: 김재현; 천혜림
Original assignee: 아주대학교 산학협력단
Priority date: 2018-10-08
Filing date: 2019-10-08
Publication date: 2020-04-16
Also published as: KR101924628B1

Abstract

Proposed is an offloading method performed by an offloading control device of a base station. The offloading method may comprise the steps of: acquiring network centrality of a user of an electronic device connected to a base station via an application executed in the electronic device, wherein the network centrality indicates the number of other users of the application, who are in an adjacent relationship, which is a relationship of sharing data, with the user of the electronic device; calculating a probability that the application is to be executed in the electronic device, on the basis of the acquired network centrality; and performing offloading of traffic occurring from the application of the electronic device according to an offloading probability of the traffic, which is determined on the basis of the calculated probability.

Description

Apparatus and method for controlling traffic offloading

It relates to an apparatus and method for reducing the load of the core network and increasing the efficiency of the network by controlling offloading of traffic using user's usage information and the like.

The development of mobile communication technology and the proliferation of smart mobile devices have brought about an explosive increase in mobile traffic, which is increasing the load on the core network. On the other hand, the second largest traffic among these mobile traffic is generated due to social networking service (SNS).

Accordingly, there is a need for offloading traffic to increase the quality of user experience (QoE) of a user while reducing the core network load by utilizing the user's social context. However, since a complicated calculation is required to utilize a social context, a considerable delay may occur in an existing cloud computing structure that processes it in a cloud on the Internet via a core network.

In order to solve the above problem, the present disclosure proposes an offloading scheme for improving network performance while reducing the load on the core network by utilizing the user's social context.

The technical problems to be achieved by the present embodiment are not limited to the technical problems as described above, and other technical problems may be inferred from the following embodiments.

According to an aspect, an offloading method performed by an offloading control device of a base station includes another user of an application in an adjacent relationship that is a data sharing data with a user of the electronic device through an application executed in the electronic device connected to the base station Obtaining a network centrality of the user of the electronic device indicating the number of, based on the obtained network centrality, calculating a probability that the application is executed in the electronic device, from the application in the electronic device determined according to the calculated probability And performing offloading of traffic according to the offloading probability of the generated traffic.

The offloading method may be performed for each of the electronic device-application combinations, each combination of a plurality of electronic devices connected to the base station and each of a plurality of applications executed in at least one of the plurality of electronic devices. have.

The step of calculating the probability of the application being executed in the electronic device is based on history information including the number of times the user has selected the application and the obtained network centrality, determining a probability that the application by the user corresponding to the electronic device is to be executed. It can contain.

The probability of offloading of traffic originating from an application in an electronic device may be determined to maximize performance of a local network and a core network associated with a base station.

In the determining of the offloading performance ratio, the offloading performance ratio is determined such that the network performance function value determined according to the data rate prediction value, the transmission delay prediction value, and the packet error loss rate prediction value is the maximum. And determining.

The base station to which the electronic device belongs may be a small cell base station.

An apparatus according to another aspect includes a processor for controlling offloading of a base station by executing a memory and at least one program in which at least one program is stored, wherein the processor is configured to execute an application executed in an electronic device connected to the base station. The network centrality of the user of the electronic device indicating the number of other users of the application in the adjacent relationship, which is a relationship of sharing data with the user of the electronic device, is obtained, and based on the obtained network centrality, the application may be executed in the electronic device. Probability is calculated, and offloading of traffic may be performed according to an offloading probability of traffic generated from an application in an electronic device determined according to the probability.

According to another aspect, the offloading method performed by the offloading control device of the base station includes: between I electronic devices connected to the base station and J applications executed in at least one of the I electronic devices. For each of the P (P is IXJ) electronics-application combinations, through at least some of the J applications, i (i is an index for identifying each electronic device and the corresponding user, 1 <= i <= an integer of i) acquiring the network centrality of the i-th user representing the number of other users in the adjacent relationship, which is a relationship sharing data with the i-th user of the electronic device, in the i-th electronic device Based on the history information including the frequency of execution and the network centrality of the obtained i-th user, the jth j in the i-th electronic device identifies each application As an index to, 1 <= j <= J) calculating the probability that the application will be executed, and the p (p is the respective electromagnetic 긱-) determined based on the probability that the j application is executed in the i-th electronic device As an index for identifying an application combination, it may include performing an offloading of traffic according to an offloading probability of traffic associated with the electronic device-application combination.

The offloading method according to an aspect acquires a user's network centrality and uses it to calculate an application execution probability, and, in particular, offs for each electronic device and each application using a network centrality and an application execution frequency. By calculating the loading rate, it is possible to improve the efficiency of processing traffic from applications such as social networks.

The effects of this embodiment are not limited to the above-described effects, and the effects not mentioned will be clearly understood by those skilled in the art from the present specification and the accompanying drawings.

1 is a view for schematically explaining offloading of traffic according to an embodiment.

2 is a block diagram of an apparatus for controlling offloading according to an embodiment.

3 is a flowchart of a method for controlling an offloading by an apparatus for controlling offloading according to an embodiment.

4 is a flowchart of a method for an offloading control apparatus according to an embodiment to control offloading traffic for a plurality of electronic device-application combinations.

5 is a flowchart of a method for determining an offloading probability combination using an approximate network performance function by an offloading control apparatus according to an embodiment.

Hereinafter, various embodiments of the present application will be described with reference to the accompanying drawings. However, this is not intended to limit the technology described herein to specific embodiments, and it should be understood that it includes various modifications, equivalents, and / or alternatives of the embodiments herein. In connection with the description of the drawings, similar reference numerals may be used for similar components.

As used herein, expressions such as “have,” “can have,” “includes,” or “can include,” indicate the presence of a feature (eg, a component such as a numerical value, function, operation, or part). Indicates, does not exclude the presence of additional features.

As used herein, the expression “A or B,” “at least one of A or / and B,” or “one or more of A or / and B”, etc., can include all possible combinations of the items listed together. For example, “A or B,” “at least one of A and B,” or “at least one of A or B,” (1) includes at least one A, (2) includes at least one B, Or (3) all cases including both at least one A and at least one B.

As used herein, expressions such as “first,” “second,” “first,” or “second,” etc. can modify various components, regardless of order and / or importance, and can change one component to another It is used to distinguish from the components, but does not limit the components. For example, the first user device and the second user device may indicate different user devices regardless of order or importance. For example, the first component may be referred to as a second component without departing from the scope of rights described in this document, and similarly, the second component may also be referred to as a first component.

As used herein, the expression "configured to (or configured)", depending on the situation, for example, "suitable for," "having the capacity to", It can be used interchangeably with "" designed to, "" adapted to, "" made to, "or" capable of ". The term "configured (or set) to" may not necessarily mean only "specifically designed to" in hardware. Instead, in some situations, the expression "a device configured to" may mean that the device "can" with other devices or parts. For example, the phrase “processors configured (or set) to perform A, B, and C” means by executing a dedicated processor (eg, an embedded processor) to perform the operation, or one or more software programs stored in the memory device. , It may mean a general-purpose processor (eg, CPU or application processor) capable of performing the corresponding operations. Here, the controller means one or more processors.

The terms used herein are only used to describe specific embodiments, and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person skilled in the art described in this document. Among the terms used herein, terms defined in a general dictionary may be interpreted as having the same or similar meaning in the context of the related art, and in an ideal or excessively formal meaning, unless explicitly defined in this document. Is not interpreted. In some cases, even the terms defined herein cannot be interpreted to exclude embodiments of the present application.

Hereinafter, an image sensor of a curved semiconductor base according to various embodiments will be described with reference to the accompanying drawings.

Mobile edge computing (mobile edge computing) by bringing the online service and content to the user terminal (101, 102, 103), increase the speed of service delivery and relieve the load on the core network.

By opening the base station, which is the edge of the wireless network, to content and service providers, an application server on the base station can control network traffic. Such an application server is hereinafter referred to as an edge server.

The edge server 100 may control traffic related to

user terminals

101, 102, and 103 located in the base station 110 controlled by the edge server 100. That is, the edge server 100 may control the amount of traffic on the network caused by the use of the online service through the

user terminals

101, 102, and 103.

For example, the base station 110 may be a small cell base station. The small cell base station refers to a base station having an output coverage of several tens / hundreds of m by distinguishing it from a macro cell supporting broadband coverage of several kilometres (km).

The small cell base station 110 is divided into a residential femtocell, an enterprise type picocell, a metrocell and a microcell used in a city or rural area according to the size and use of the cell.

Small cells complement the shortcomings of existing cells with relatively large coverage, for example, macro cells, and have emerged as effective traffic acceptance technologies in public places, densely populated areas, etc. It increases the capacity by interference control and cooperative transmission. For example, the small cell was used as a concept such as Home eCodeB or fetom Cell, but is not limited thereto.

Depending on the location and use, the small cell may be constructed independently, or may be constructed as a Cloud RAN structure in which a radio radio unit and a baseband unit are separated.

Regarding the Cloud (or centralized) RAN structure, Alluel Lucent's (ALU) Light Radio, China Mobile, ZTE, HUAWEI's C-RAN, NSN's LightNet, IBM's Cloud based WiMAX, Ericsson's LTE based Cloud RAN The lights have been verified at the PoC (Proof-of-Concept) level. In the case of the Cloud RAN structure, RRH (Remote Radio Head) and DU (Digital Unit) are currently separated, and radio access virtualization for 4G and 5G mobile communication uses flexible resources, supports various radio accesses, and diversifies spectrum. This progresses.

One of the wireless access network structures to be considered along with the compact deployment of small cells is HetNet. In 5G mobile communication, a small cell is likely to be used in a shaded area, or in an area where traffic is concentrated in a dense urban area, and it will form a HetNet structure with a macro base station. Techniques such as interference control and cooperative transmission in the HetNet environment are studied.

In 5G mobile communication, the wireless access network structure considering a small cell is a wireless access virtualization that assumes a HetNet structure, a virtualization structure that considers distribution and centralized control in each protocol layer, and is flexible in various wireless transmission methods. Research on virtualization structures and structures capable of integrated radio resource control may be conducted.

Meanwhile, as the use of applications related to novel networking, content sharing, etc. increases, the amount of data movement through the network exploded. As the amount of mobile data traffic increases, overloading may occur due to network capacity limitations. As a method for solving this, an offloading technique is proposed.

Referring to FIG. 1, when offloading is not performed, the edge server 100 passes through the core network 170 from the backhaul network of the base station 110 to which the user terminal belongs, for example, the small cell base station 110. The core network traffic 160 connecting the backhaul network of the content provider server is formed.

On the other hand, when the edge server 100 determines the offloading traffic, the edge server 100 does not go through the core network, but the backhaul network or the Internet 140 of the small cell base station 110 and the server 1401 of the direct content provider. ) To form offloading traffic 150.

The edge server 100 considers the importance of each of the

social network subscribers

131, 132, and 133 corresponding to the

user terminals

101, 102, and 103 in applications such as social networking or use frequency of the application selected in the user terminal. Thus, it may be determined whether or not the

user terminals

101, 102, and 103 are offloaded.

Referring to FIG. 1, when a user 132 among a plurality of users belonging to the small cell base station 110 has a high connection with

other users

131 and 133, the edge server 100 is a user 132 May determine to perform offloading for the mobile device 102 associated with.

Hereinafter, an offloading control method performed by an offloading control device including the edge server 100 will be described with reference to the drawings.

2 is a block diagram of an apparatus 200 for controlling offloading according to an embodiment.

The device 200 may include a control unit 210, a communication unit 220, and a memory 230.

The device 200 may store program codes in the memory 230. The controller 210 may process an operation of compressing an artificial neural network by executing program code loaded from the memory 230 through a system bus.

For example, the communication unit 220 includes a wireless communication device such as Wi-Fi, short-range wireless communication, and the device 200 may transmit and receive data to and from external devices through the communication unit 220. Alternatively, the communication unit 220 may include a device that supports wired communication with other devices using a data communication cable, but is not limited thereto.

The memory 230 may include one or more physical memory devices, such as local memory or one or more bulk storage devices. At this time, the local memory may include random access memory (RAM) or other volatile memory devices commonly used while actually executing program code. The mass storage device may be implemented as a hard disk drive (HDD), a solid state drive (SSD), or other nonvolatile memory device. In addition, the device 200 may use one or more cache memories (not shown) that provide temporary storage space of at least some program code to reduce the number of times the program code is retrieved from the mass storage devices during the compression operation. It can contain.

As the executable program code stored in the memory 230 is executed by the device 200, various operations described in the present disclosure may be performed by the controller 210. For example, the memory 230 may store program code for causing the controller 210 to perform one or more operations described in FIGS. 3 to 5.

Depending on the particular type of device being implemented, the device 200 may include fewer components than those shown, or additional components not shown in FIG. 2. Also, one or more components may be included in other components, or may form part of other components.

In step 310, the control unit 210 is a network center of the user of the electronic device indicating the number of other users of the application in the adjacent relationship, which is a relationship that shares data with the user of the electronic device through an application executed in the electronic device connected to the base station. You can acquire a degree.

An adjacency relationship may indicate a relationship in which users share content with each other through an application. For example, a social network may indicate a “friend” relationship, a “first village” relationship, or a “following / follower” relationship.

According to an embodiment, the control unit 210 may obtain information on the neighbor relationship from each of a plurality of terminals connected to the base station. For example, the control unit 210 may obtain information about a neighbor relationship from a log stored in a plurality of electronic devices whenever an application is executed in each of the plurality of terminals.

Alternatively, the control unit 210 may obtain information about an adjacent relationship related to the application through communication with a server managing an application to which the electronic terminal accesses.

For example, information about the neighbor relationship may be defined separately for each application.

Alternatively, the controller 210 may determine a user's adjacent relationship in consideration of whether there is an adjacent relationship in at least some of the plurality of different applications.

For example, a plurality of electronic devices may belong to the coverage of the base station. At this time, a plurality of electronic devices may be connected to the base station to form a communication network with the Internet or an external server. Also, the controller 210 may determine a plurality of applications that are executed on at least some of the plurality of electronic devices connected to the base station to generate traffic. At this time, the control unit 210 may manage traffic of the determined plurality of applications. Alternatively, the controller 210 may manage traffic of a plurality of predetermined numbers of applications.

Adjacent relationships can be determined in relation to the user. For example, a separate user may correspond to each of a plurality of electronic devices connected to the base station. For example, an application may be executed through each of a plurality of electronic devices corresponding to each of a plurality of users having an account for one application.

As another example, a user may run the same application or two or more different applications through two or more of the plurality of electronic devices. In this embodiment, it is assumed that two or more electronic devices are independent electronic devices, and one user corresponding to the two or more electronic devices is assumed to be an independent user corresponding to each electronic device, and embodiments of the present disclosure may be applied. have.

In step 320, the controller 210 may calculate a probability that the application is executed in the electronic device based on the obtained network centrality.

For example, the greater the network centrality of the user executing the application through the electronic device, the higher the probability of executing the application through the electronic device. Probably, the greater the user's network centrality, the higher the probability that data sharing that generates traffic through the application may be performed.

For example, the network centrality may be determined by collectively considering a plurality of applications. In this case, the network centrality used to calculate the execution probability of the application may be the same for a plurality of applications.

As another example, the network centrality may be determined independently for each of a plurality of applications. In this case, the network centrality used to calculate the execution probability of the application may be determined independently for each of a plurality of applications.

In addition, the controller 210 may calculate a probability that the application is executed based on the history information regarding the number of times the application has been executed in the electronic device.

Similar to the information about the adjacency relationship, the controller 210 may obtain history information on the number of times the application stored in the electronic device has been executed. As another example, the controller 210 may obtain history information including the number of times executed from the electronic device from a server corresponding to the application.

For example, the control unit 210 may determine the probability that the application is executed is increased as the number of times the corresponding application is executed in the electronic device.

In addition, the controller 210 may determine a probability that an application is executed in consideration of a network centrality of a user corresponding to the electronic device and the number of times the corresponding application is executed in the electronic device.

In operation 330, the controller 210 may perform offloading of traffic according to an offloading probability of traffic generated from an application in an electronic device determined according to the calculated probability.

The controller 210 may determine an offloading probability of traffic generated from an application executed in the electronic device to maximize performance of a local network and a core network associated with the base station.

The controller 210 may determine a range of the offloading probability based on the probability that the application is executed in the electronic device.

For example, when the proportion of the probability that one application is executed among the plurality of applications executed in the electronic device is large, the range of the offloading probability of the corresponding application in the electronic device may be determined as a relatively high probability range. For example, when the proportion of the probability that one application is executed among the plurality of applications executed in the electronic device is large, an upper limit of the range of the offloading probability of the corresponding one application may be determined to be high.

In addition, the controller 210 may determine a range of offloading probability in consideration of the traffic loads of the local network and the core network associated with the base station.

For example, the controller 210 may determine a higher range of the offloading probability range as the traffic load of the core network is greater than the traffic load of the local network associated with the base station. For example, the control unit 210 may determine the lower limit of the range of the offloading probability as the traffic load of the core network is greater than the traffic load of the local network associated with the base station.

For example, the degree of traffic load can be determined based on the utility. The utility may indicate the amount of traffic generated by an application among the supported traffic capacity of the network.

The controller 210 may determine a range of offloading probability in consideration of the utility of the local network and the core network associated with the base station. For example, the controller 210 may determine a range of the offloading probability of the application in consideration of the ratio of the localization of the local network to the sum of the activations of the local network and the core network. For example, the control unit 210 may determine the lower limit of the range of the offloading probability to be higher, as the ratio of the localization of the local network to that of the core network increases.

The controller 210 may determine an offloading probability such that the increased network performance is maximized as the speed of the data rate increases, the transmission delay decreases, and the packet error loss rate decreases.

For example, the control unit 210 may determine the offloading probability such that the network performance function value determined according to the predicted value of the data rate, the predicted value of the transmission delay, and the predicted value of the packet error rate corresponding to the offloading probability is the maximum. .

The method of FIG. 3 may be performed by an offloading management device (200 of FIG. 2).

In step 310, the device acquires a network centrality of the user of the electronic device indicating the number of other users of the application in the adjacent relationship, which is a relationship sharing data with the user of the electronic device through an application executed in the electronic device connected to the base station. can do.

According to an embodiment of the present disclosure, the device may acquire information on neighboring relationships from each of a plurality of terminals connected to a base station. For example, the device may acquire information about a neighbor relationship from a log stored in a plurality of electronic devices whenever an application is executed in each of the plurality of terminals.

Alternatively, the device may acquire information about an adjacency relationship related to the application through communication with a server managing an application connected to the electronic terminal.

Alternatively, the device may determine a user's adjacent relationship in consideration of whether there is an adjacent relationship in at least some of the plurality of different applications.

For example, a plurality of electronic devices may belong to the coverage of the base station. At this time, a plurality of electronic devices may be connected to the base station to form a communication network with the Internet or an external server. Also, the apparatus may determine a plurality of applications that are executed in at least some of the plurality of electronic devices connected to the base station to generate traffic. At this time, the device may manage traffic of the determined plurality of applications. Alternatively, the device may manage traffic of a predetermined number of applications.

In step 320, the device may calculate the probability that the application is executed in the electronic device based on the obtained network centrality.

In addition, the device may calculate the probability that the application is executed based on history information regarding the number of times the application has been executed in the electronic device.

Similar to the information about the adjacency relationship, the device may obtain historical information about the number of times the application stored in the electronic device has been executed. As another example, the device may obtain history information including the number of times executed from the electronic device from a server corresponding to the application.

For example, the more the number of times the corresponding application is executed in the electronic device, the higher the probability that the application is executed.

In addition, the device may determine the probability that the application is executed in consideration of the network centrality of the user corresponding to the electronic device and the number of times the corresponding application is executed in the electronic device.

In operation 330, the device may perform offloading of traffic according to an offloading probability of traffic generated from an application in an electronic device determined according to the calculated probability.

The device may determine the probability of offloading traffic originating from an application running on the electronic device to maximize the performance of the local and core networks associated with the base station.

The device may determine a range of offloading probability based on the probability that the application will be executed in the electronic device.

In addition, the apparatus may determine a range of offloading probability in consideration of the traffic load of the local network and the core network associated with the base station.

For example, the device may determine a higher range of the offloading probability range as the traffic load of the core network is greater than the traffic load of the local network associated with the base station. For example, the higher the traffic load of the core network to the traffic load of the local network associated with the base station, the higher the lower limit of the range of offloading probability can be.

The apparatus may determine a range of offloading probabilities in consideration of the utility of the local network and the core network associated with the base station. For example, the device may determine a range of offloading probabilities of an application by considering the ratio of the localization of the local network to that of the local network and the core network. For example, the device may determine a lower limit of the range of the offloading probability to be higher as the ratio of the localization of the local network to that of the core network increases.

The apparatus may determine the offloading probability such that the increased network performance is maximized as the speed of the data rate increases, the transmission delay decreases, and the packet error loss rate decreases.

For example, the apparatus may determine the offloading probability such that the network performance function value determined according to the predicted value of the data rate corresponding to the offloading probability, the predicted value of the transmission delay, and the predicted value of the packet error loss rate is the maximum. A detailed description will be given with reference to FIGS. 4 and 5 below in relation to a network performance function.

The method of FIG. 4 may be performed by the offloading management device (200 of FIG. 2).

In FIG. 4, it is assumed that I electronic devices are connected in the base station. At this time, the lowercase letter i is an index for each of the electronic devices, and i is an integer with 1 <= i <= I.

In addition, it is assumed that the number of applications executed through at least one of the I electronic devices and generating traffic through the local network and / or the core network associated with the base station is J. At this time, lowercase j is an index of each application, and j is an integer with 1 <= j <= J.

At this time, the number of electronic device-application combinations of each of the M electronic devices and M applications that can be executed in each of the I electronic devices is P = MxN, and the lowercase p is an integer of each electronic device-application combination. Represents an index. p is an integer with 1 <= p <= P.

When offloading is performed, a backhaul of the base station, that is, traffic directly connected to the Internet through a local network occurs.

When the offloading is performed, the backhaul of the base station, that is, traffic from the local network to the Internet via the core network occurs.

In step 410, the offloading control apparatus may calculate a probability that the j application is executed in the i device in each of the electronic device-application combinations.

According to an embodiment of the present disclosure, for each of the I users corresponding to the connected I electronic devices in the network, the device may determine the number of other users sharing data with the i-th user through at least some of the J applications. Can be obtained.

For example, when the offloading control device has I users as vertices, and when any two of the I users are adjacent, the offloading control device acquires a graph G forming an edge between two vertexts corresponding to the two corresponding users. You can.

In addition, the offloading control apparatus may acquire the network center C _i of the i-th user indicating the number of other users who are adjacent to the i-th user for each of the I users through the graph G.

According to an embodiment of the present disclosure, according to an execution frequency of each of the J applications in the i-th electronic device, for each of the connected I-electronic devices in the network, the device performs a ranking r _ij of the execution frequency in the order of the highest execution frequency. Can be obtained. At this time, r _ij is an integer with 1 <= r _ij <= J.

For example, when the number of electronic devices connected to the base station is two and the number of related applications is three as the first application, the second application, and the third application, in the first electronic device, in the order in which the execution frequency is high, the When the first application, the third application, and the second application are determined, r ₁₁ = 1 representing the execution frequency ranking for the first application in the first electronic device, r representing the execution frequency ranking for the second application in the first electronic device. ₁₂ = 3, r ₁₃ = 2 indicating the execution frequency ranking for the third application in the first electronic device.

In addition, in the second electronic device, when the third application, the second application, and the first application are determined in the order in which the execution frequency is high, r ₂₁ = 3 indicating the execution frequency ranking for the first application in the second electronic device, Article ₂₃ may be r = 1 in the r ₂₂ = 2, a second electronic device in the second electronic apparatus showing the execution frequency ranking for a second application showing the execution frequency ranking of the third application.

The apparatus may obtain an execution probability of each of the device-application combinations based on the network centrality of the i-th user and the execution frequency ranking of the j-th application in the i-th device.

For example, in the offloading determination reference time t, the device has at least one user of the i electronic devices in proximity to the i user, and the j application is executed on the i electronic device It is possible to determine whether or not it satisfies the utilization condition, which is whether or not it has been performed.

As the device determines that it satisfies the utilization condition, the execution probability P _ij (t) of the j application in the i-th electronic device may be determined according to Equation (1).

In Equation 1, α is a Poisson distribution parameter, and m ⁱ ₀ (t), when t, represents the number of applications executed in the i-th electronic device.

In addition, as it is determined that the device does not meet the utilization condition, the execution probability P _ij (t) of the j application in the i-th electronic device may be determined according to Equation 2 below.

In Equation 2, m ^{i '} _j (t), when t, indicates the number of times other users in the adjacent relationship with the i-th user have executed the j-th application.

In step 420, the apparatus may determine, for each of the electronic device-application combinations, a range of the offloading probability of the j application executed in the i device.

At the offloading determination reference time t, the offloading probability corresponding to the combination of the i-th electronic device and the jth application is referred to as ω _ij (t), and the immediately preceding offloading determination reference time is represented as t-1.

The apparatus can determine the offloading probability ω _ij (t) in the range of Equation 3 below.

In Equation 3, U _LN represents the utility of the local network, which is traffic generated by M applications among supportable traffic capacity of the local network associated with the base station, and may be calculated according to Equation 4 below.

In Equation 3, U _CN represents the utility of the core network, which is traffic generated by M applications among the supportable traffic capacities of the core network associated with the base station, and may be calculated according to Equation 5 below.

In step 430, in the range of offloading probabilities for each of the electronic device-application combinations, a combination of offloading probabilities that maximize the network performance function value is determined.

The apparatus can calculate the network performance function O (t) according to Equation 6 below.

In Equation 6, if R _ij (t) represents a predicted value of the data rate, the apparatus may calculate R _ij (t) according to Equation 7 below.

In Equation 4, R _LN represents the data rate in the local network of the base station, R _CN represents the data rate in the core network associated with the base station.

The data rate may indicate the transmission rate of data on the network.

The apparatus may acquire a data rate from each of the local network and the core network, or monitor the local network and the core network, respectively, at a time t-1 immediately before the offload probability determination time.

In Equation 6, D _ij (t) represents a predicted value of the transmission delay rate, and the apparatus may determine D _ij (t) according to Equation 8 below.

In Equation 8, D ^j _LN represents the average transmission delay of the j-th application in the local network of the base station and may be calculated according to Equation 9 below.

In Equation 8, D ^j _CN may be calculated according to Equation 10 below if the average transmission delay of the j th application in the core network associated with the base station is indicated.

In Equations 9 and 10, L _j may represent an average packet size of the j-th application. The average packet size L _j of the j th application may be acquired by the device through monitoring, or may be obtained from an application server or other devices.

In Equation 6, Pe _ij (t) represents a predicted value of the packet error loss rate, and the apparatus can calculate the predicted value Pe _ij (t) of the packet error loss rate according to Equation 11 below.

In Equation 11, Pe _LN represents a packet error loss rate in the local network of the base station, Pe _CN represents a packet error loss rate in the core network associated with the base station.

In Equations 7, 8 and 11, the predicted value of the data rate, the predicted value of the transmission delay rate, and the predicted value of the packet error loss rate are network performance information at the immediately preceding offloading determination time t-1, which is the obtained information, for example, immediately before the offloading decision. It is calculated based on the data rate and packet error loss rate of each of the local network and the core network at time t-1, as well as the weight offloading probability ω _ij (t) determined at the current offloading determination time t.

The apparatus has P = IxJ electronic device-application combinations, that is, the offloading probability ω _ij (t) corresponding to the i-th device and the j-th application by a predetermined difference value Δω _ij in the range of Equation 3 described above Substituting equations 7, 8 and 11 with varying values, the corresponding R _ij (t), D _ij (t) and Pe _ij (t) are calculated, from which the network performance function value O (t) according to equation (6) ). Through this heuristic method, the apparatus determines an offloading probability combination having a maximum network performance function value O (t) among the combinations of offloading probabilities corresponding to each of P = IxJ device-application combinations. .

For example, if the range of offloading probability corresponding to each of all combinations of device-applications is [0.2, 0.5] and the offloading probability is changed at intervals of 0.1, when searching is performed, it is estimated for each device-application There are four offloading probabilities of 0.2, 0.3, 0.4, and 0.5, so there can be all 4 ^ (IxJ) offloading probability combinations, and the device compares the network performance function values for all offloading probability combinations. To do this, the network performance function value of 4 ^ (IxJ) must be calculated.

The method of FIG. 5 may be performed by the offloading management device (200 of FIG. 2).

Of the network performance function values calculated by substituting L candidate offloading probabilities in each offloading probability interval of each device-application combination, theoretically L ^ to determine a combination of offloading probabilities having the largest network performance function values It is necessary to calculate the network performance function value of (IXJ).

Since it requires a relatively large amount of computation, it is possible to reduce the computation and increase efficiency by using an approximate network performance function to improve processing speed.

The approximate network performance function is calculated after calculating an approximate network performance function value for each of the candidate values of the L offloading probabilities in a corresponding device-application combination, i.e., the offloading probability wij range corresponding to the i-device and the j-th application. , Offloading probability wij corresponding to the maximum value among L approximate network function values is determined as a corresponding device-application combination, i.e., offloading probability wij of the i-th device and the j-th application combination.

At this time, since the approximate network performance function value of L times is calculated for each combination, if the approximate network performance function value of MxNxL times is calculated for the total of MxN combinations, the approximate optimal offloading probability combination can be calculated. have. Therefore, the amount of computation can be greatly reduced and the efficiency of the system can be increased.

In step 505, the apparatus may set the index i that identifies the device to 1. In addition, in step 510, the device may set an index j to 1 to identify the application.

Then, while changing i and j, the offloading probability is determined for each device-application combination.

In step 515, the apparatus acquires an upper limit value upper (wij) and a lower limit value lower (wij) of a range of offloading probabilities corresponding to the i-th device and the j-th device.

For example, the apparatus may obtain a range of offloading probability according to Equation (3). At this time, the upper limit of the range of offloading probability upper (wij) is

And lower (wij) is

It can be determined by.

In operation 520, the device may set the index k representing candidates of the offloading probability to 1 in the range of the offloading probability.

For example, the device may determine L candidate values in the determined range of offloading probabilities. At this time, k is an integer value from 1 to L.

When k is 1, ω _{ij, k} has a lower value lower (ω _ij ), and when k is L, ω _{ij, k} has an upper value upper (ω _ij ).

In step 525, the device may _calculate an approximate network performance function o _{ij, k} (t) using ω _{ij, k} (t).

For example, the device may calculate an approximate network performance function value o _{ij, k} (t) according to Equation (12).

In Equation 12, R _{ij, k} (t), D _{ij, k} (t), and Pe _{ij, k} (t) represent the prediction of the data rate, the prediction of the transmission delay rate, and the prediction of the packet error loss rate, respectively. It can be calculated by substituting the current candidate value ω _{ij, k} (t) in ω _ij (t) in Equations 7 to 11 described above.

In Equation 12, j ° is an index indicating applications other than the j application,

And

Is the offloading probability corresponding to the combination between the i device and the j ° application, which is another application.

It is assumed that k = 1, that is, the minimum value that is the lower limit.

In addition, the apparatus is a list of approximate network performance functions corresponding to the current device-application combination list o _ij (t) and approximate network performance function values calculated using ω _{ij, k} (t) o _{ij, k} (t) Can be added and saved.

In step 535, the device may determine whether k is L.

If k is not L, it is necessary to repeatedly perform step 530 for the additional candidate group in the offloading probability range, so the device proceeds to step 540 to update the k value by adding 1 to k.

If k is L, it indicates that the approximate network performance function value has been calculated for all offloading probability candidate values in the current device i and application j combination, and the apparatus performs step 545.

In step 545, the device sets the offloading probability ω _{ij, max} (t) with the maximum approximated function value o _{ij, k} (t) in the list of approximate network performance function lists o _ij (t), device i and application j. It can be determined by the offloading probability corresponding to the combination.

As described above, the apparatus may determine the offloading probability for each combination of the i-th device and the j-th application while performing steps 515 to 545.

At step 550, the device may determine if j equals the total number of applications J.

If j is different from the total number of applications J, steps 515 to 545 are repeatedly performed for the current i-device and other application combinations. Accordingly, the device updates the index j identifying the application at step 555 to j + 1 and returns to step 515 to proceed to subsequent steps.

If j is equal to the total number of applications J, the offloading probability is determined for all combinations of applications for the current i device, so the apparatus determines whether to change or terminate the target device of the offloading probability. 560.

In step 560, the apparatus determines whether the index i identifying the device is equal to the number I of devices.

If i is different from the total number of devices I, steps 515 to 545 are repeatedly performed for a device different from the current i-th device. Accordingly, in step 565, the apparatus updates index i identifying the device to i + 1 and returns to step 510 in order to determine the offloading probability sequentially from the first application, and then proceeds to the subsequent steps.

If, at step 560, the index i identifying the device is equal to the number I of devices, the device determines the offloading probability for all device and application combinations, and thus ends the process.

Meanwhile, the above-described embodiments of the present invention can be written in a program executable on a computer, and can be implemented in a general-purpose digital computer that operates a program using a computer-readable recording medium. In addition, the structure of data used in the above-described embodiment of the present invention can be recorded on a computer-readable recording medium through various means. Computer-readable recording media include magnetic storage media (eg, ROM, floppy disks, hard disks, etc.), optical storage media (eg, CD-ROM, DVD, etc.).

So far, the present invention has been focused on the preferred embodiments. Those skilled in the art to which the present invention pertains will understand that the present invention may be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments should be considered in terms of explanation, not limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the equivalent range should be interpreted as being included in the present invention.

Claims

In the offloading method performed by the offloading control device of the base station,

Obtaining a network centrality of the user of the electronic device indicating the number of other users of the application in an adjacent relationship that is a data sharing relationship with the user of the electronic device through an application executed in the electronic device connected to the base station ;

Calculating a probability that the application is executed in the electronic device based on the obtained network centrality;

And performing offloading of traffic according to an offloading probability of traffic generated from the application in the electronic device determined according to the calculated probability.
According to claim 1,

The offloading method,

And each of the plurality of electronic devices connected to the base station and each of the electronic device-application combinations, which is a combination of each of a plurality of applications executed in at least one of the plurality of electronic devices.
According to claim 1,

The step of calculating the probability that the application is executed in the electronic device is

And determining a probability that the application is executed by a user corresponding to the electronic device, based on history information including the number of times the user has selected the application and the acquired network centrality.
According to claim 1,

A method for determining the offloading probability of traffic originating from the application in the electronic device to maximize the performance of the local network and the core network associated with the base station.
According to claim 1,

Determining the offloading performance ratio,

And determining the offloading performance ratio such that a network performance function value determined according to a prediction value of a data rate corresponding to an offload performance ratio, a prediction value of a transmission delay, and a prediction value of a packet error loss rate is the maximum.
According to claim 1,

The base station to which the electronic device belongs is a small cell base station.
In the device,

A memory in which at least one program is stored; And

And a processor for controlling offloading of the base station by executing the at least one program,

The processor,

Acquiring a network centrality of the user of the electronic device indicating the number of other users of the application in an adjacent relationship that is a data sharing relationship with the user of the electronic device through an application executed in the electronic device connected to the base station,

Based on the obtained network centrality, calculate the probability that the application will be executed in the electronic device,

An apparatus for performing offloading of traffic according to the offloading probability of traffic generated from the application in the electronic device determined according to the calculated probability.
An offloading method performed by an offloading control device of a base station,

For each of the P (P is IXJ) electronic device-application combinations between I electronic devices connected to the base station and J applications executed in at least one of the I electronic devices,

Through at least some of the J applications, i (i is an index for identifying each electronic device and a corresponding user, an integer with 1 <= i <= I) of the i user of the electronic device and data Acquiring a network centrality of the i-th user indicating the number of other users in neighboring relationships that are shared relationships;

Based on the history information including the frequency of execution of the j-th application in the i-th electronic device and the network centrality of the obtained i-th user, the j-j in the i-th electronic device identifies each application As an index for, 1 <= j <= J integer) calculating the probability that the application is executed; And

The p (p is an index for identifying each combination of electromagnetic 긱 -applications) determined based on the probability that the j-th application will be executed in the i-th electronic device. And performing offloading of the traffic according to the offloading probability of the traffic related to the combination,

The step of calculating the probability,

At the offloading determination reference time t, among the users of the I electronic devices, a user of at least one electronic device adjacent to the i user exists, and whether the j application is executed in the i electronic device Determining whether or not to meet the conditions of phosphorus utilization,

The network centrality of the obtained i-user is C i , and the ranking of the execution frequency of the j-th application in the order of execution frequency among the J applications in the i-th electronic device is r ij (r ij is positive). Integer),

As it is determined that the utilization condition is satisfied, the execution probability P ij (t) of the j application in the i-th electronic device is determined according to Equation 1 below,

-Equation 1-

In Equation 1, α is a Poisson distribution parameter, and m i 0 (t) represents the number of applications executed in the i-th electronic device at the offload determination reference time t,

As it is determined that the utilization condition is not satisfied, the execution probability P ij (t) of the j-th application in the i-th electronic device is determined according to Equation 2 below,

-Equation 2-

In Equation 2, m i ' j (t), the reference time t of the offloading determination time t, indicates how many times the j application has been executed by other users adjacent to the i user .
The method of claim 8,

The offloading probability of traffic associated with the p-th electronics-application combination is a predicted value of data rate and transmission delay predicted according to offloading probability combinations of traffic associated with each of the P electronics-application combinations. At least one prediction value of a prediction value of (delay) and a packet error loss rate is obtained,

A method for determining offloading probability combinations of the traffic such that a network performance function value associated with the base station determined according to the obtained at least one prediction value is maximized