CN111901374A - Task unloading method based on alliance game in power Internet of things system - Google Patents

Task unloading method based on alliance game in power Internet of things system Download PDF

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CN111901374A
CN111901374A CN202010568459.7A CN202010568459A CN111901374A CN 111901374 A CN111901374 A CN 111901374A CN 202010568459 A CN202010568459 A CN 202010568459A CN 111901374 A CN111901374 A CN 111901374A
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夏玮玮
高航
成华清
张雅雯
燕锋
沈连丰
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Southeast University
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Abstract

The invention discloses a task unloading method based on alliance game in an electric power Internet of things system, which comprises the following steps: (1) the intelligent ammeter and the access point AP in the same area form a network; a plurality of intelligent electric meters can be connected to the AP by using the same subcarrier; (2) the electric meter has a calculation task, and can be processed locally or unloaded to the AP for processing; forming a union by using the electric meters of the same subcarrier; establishing a cost function; (3) the intelligent electric meter selects an unloading strategy in the strategy set; the intelligent ammeter and the AP establish a alliance game; (4) the intelligent electric meter calculates the unloading income of the intelligent electric meter added into each alliance, and the intelligent electric meter is added into the alliance which enables the total unloading income to be maximum; (5) and the alliance game achieves Nash balance, the intelligent electric meter in the network does not change the strategy any more, and the task is unloaded according to the strategy. The method is based on the alliance game, makes full use of wireless resources and computing resources of the AP, and meets task unloading requirements of the intelligent electric meters while aiming at minimizing unloading cost of the intelligent electric meters.

Description

Task unloading method based on alliance game in power Internet of things system
Technical Field
The invention belongs to the field of power Internet of things, and particularly relates to a task unloading method based on alliance game in a power Internet of things system.
Background
In recent years, the demand for electric power from human beings has increased greatly, but the conventional power distribution network is inefficient. The power internet of things is a modern power grid infrastructure, can improve efficiency, reliability and safety through automatic control and modern communication technology, and realize stable integration of renewable energy and alternative energy. Renewable energy power generation is an effective technology to reduce fossil fuel consumption and greenhouse gas emissions. More importantly, the power internet of things with the new network management strategy enabled can achieve effective power grid integration in distributed power generation to perform demand-side management and achieve distributed power generation load balancing in energy storage. Many researchers have conducted extensive research on renewable energy sources, and the integration of renewable energy sources, reducing system losses and improving reliability, efficiency and safety of power supply to customers are further enhancements to the power internet of things system. Furthermore, existing power grids lack communication functionality, while the power internet of things infrastructure is full of enhanced sensing and advanced communication and computing capabilities. The different components of the system are linked together with communication paths and sensor nodes to provide interoperability with each other.
In the power internet of things, data collected from the smart meter is generally sent to a neighboring AP first and uploaded to a control center by the AP. The smart meter usually has a calculation task and can be processed locally, but if the calculation task is heavy, the local processing causes large energy consumption and time delay overhead. If the calculation tasks on the intelligent electric meter with insufficient calculation resources are unloaded to the AP server for processing, the calculation resources of the AP server are fully utilized, the utilization rate of the AP resources can be improved, and the performance of the system can also be improved. However, the number of subcarriers of the AP is limited, and when the number of smart meters is large, the offloading requirements of all smart meters cannot be well met, and the problem can be well solved by the non-orthogonal multiple access NOMA technology. The basic idea of NOMA is to superimpose the signals from the various smartmeters at the transmitter side using superposition coding and to decode the desired signal at the receiver side using successive interference cancellation techniques. NOMA is able to accommodate a larger number of smart meters than the number of available subcarriers, i.e., multiple smart meters may be offloaded using the same subcarrier, may improve the performance of wireless communications in a number of ways, including more smart meters, lower latency, higher spectral efficiency, and relaxed channel feedback.
Therefore, we consider the smart meters that use the same sub-carrier for task offloading as a federation. The smart meter can choose to process the task locally or to offload the task to the AP server for processing through the sub-carrier. The strategy of the intelligent electric meter directly influences the formation of the alliance, so that the utility function of the alliance is influenced significantly. Therefore, how to select the offloading policy of the smart electric meters and the subcarriers under the offloading condition to realize effective allocation of resources and meet the service requirements of each smart electric meter is an urgent problem to be solved.
Disclosure of Invention
In order to solve the problems, the invention discloses a task unloading method based on alliance game in an electric power Internet of things system, which fully utilizes the computing resources of AP and meets the task unloading requirements of each intelligent electric meter while aiming at minimizing the energy consumption and the time delay of the network.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a task unloading method based on alliance game in an electric power Internet of things system comprises the following steps:
(1) all the intelligent electric meters in the same area are accessed to the AP through wireless connection; based on the NOMA technology, a plurality of intelligent electric meters can be connected to the AP by using the same subcarrier, and the intelligent electric meters using the same subcarrier form an alliance;
(2) the intelligent electric meter has a calculation task and can be processed locally or unloaded to the AP through a subcarrier for processing; establishing a cost function of the intelligent ammeter, wherein the cost function is divided into a cost function in local calculation and a cost function in task unloading and consists of energy consumption and time delay; all the intelligent electric meters have the same computing resources required for processing computing tasks; the calculation resources distributed to each intelligent electric meter by the AP are the same; the computing resources of each intelligent electric meter are different;
(3) sequentially selecting strategies, namely adding alliances, for all the intelligent electric meters in the network, and calculating unloading profits, wherein the unloading profits are related to cost functions, and the sum of the unloading profits of all the intelligent electric meters in the alliances is the effectiveness of the alliances; all intelligent electric meters and APs in the network establish a alliance game;
(4) each intelligent electric meter selectively joins in a alliance with the maximum utility through comparison; after all the intelligent electric meters select the strategies, calculating the total utility of the network;
(5) all the intelligent electric meters sequentially execute a strategy which is one iteration; the computing resources required by all the intelligent electric meters for task unloading are the same, and the AP distributes the computing resources for the intelligent electric meters selected for task unloading; after the system carries out one iteration, the strategy of some intelligent electric meters in the network is changed, the number of the intelligent electric meters in each alliance is increased or reduced, and therefore the connection state of each intelligent electric meter in the network needs to be updated;
(6) and the game reaches Nash equilibrium, all the intelligent electric meters in the network do not change the strategy any more, and each intelligent electric meter selects to process the task locally or unload the task to the AP for execution according to the strategy and obtains the computing resource distributed by the AP according to the subcarrier used under the unloading condition.
The invention has the beneficial effects that:
the method and the system enable each intelligent electric meter in the network to sequentially realize strategy selection based on the alliance game to form alliances, so that computing resources and subcarrier resources in the AP are fully utilized, and task unloading requirements of each intelligent electric meter are met while a cost function of the intelligent electric meter is minimized. The method comprehensively considers the unloading selection of the intelligent electric meters, the subcarrier selection and the position influence of the intelligent electric meters, and minimizes the total cost function of all the intelligent electric meters in the network under the condition of ensuring the task effectiveness.
Drawings
FIG. 1 is a flow chart of a task offloading method based on league gaming of the present invention;
FIG. 2 is a NOMA-based power Internet of things infrastructure diagram of the present invention;
fig. 3 is a flow chart of the league game nash equilibrium solving process of the present invention.
Detailed Description
The present invention will be further illustrated with reference to the accompanying drawings and specific embodiments, which are to be understood as merely illustrative of the invention and not as limiting the scope of the invention.
The method is based on the alliance game, the real-time performance of each intelligent electric meter task is guaranteed while the total cost function of all the intelligent electric meters is minimized, and meanwhile the influence of the intelligent electric meter position on alliance formation is considered. The following describes the method of the present invention with reference to the accompanying drawings.
As shown in fig. 2, consider a NOMA-based power internet of things scenario, in which there are N smart meters and an AP equipped with a server, located in the center of the scenario. The intelligent electric meter is connected with the AP through a wireless link, and the AP is connected to the power grid control center through a wired link. The channel is assumed to be quasi-static rayleigh fading, i.e. the channel of the smart meter remains unchanged during each unloading period and the state in any two periods is independent. In addition, it is assumed that both the smart meter and the AP are equipped with one antenna. By using
Figure BDA0002548663200000031
Denotes a set of smart meters, and S ═ {1, 2. With NOMA, multiple smartmeters can share the same subcarrier, and therefore, the received signal of a smartmeter at the AP contains not only its desired signal, but also interfering signals from other smartmeters on the same subcarrier. By using
Figure BDA0002548663200000032
To represent the set of smart meters sharing the subcarrier s and assume that each smart meter can offload its computational tasks to the AP server with at most one subcarrier.
By using
Figure BDA0002548663200000033
Representing an unloading decision of the smart meter, ans1 represents that the smart meter n unloads the calculation task by using the subcarrier s, and ansThe opposite is true if 0. Since each smart meter can use at most one subcarrier for task offloading, the offloading decision needs to satisfy the following constraints:
Figure BDA0002548663200000034
the uplink channel gain between the smart meter n and the AP on subcarrier s is denoted as hns. The channel gains in set s are ordered in ascending order, using bs(. represents the sequence in which bs(j) And indicating the sequencing position of the smart meter j in the subcarrier s. In addition, the decoding order in uplink NOMA follows a decreasing order of channel gains, unlike downlink NOMA, where the decoding order is reversed. It decodes the highest ranked user data first and treats the signals from all other users as noise. Once the receiver has decoded the data for the highest ranked user, the receiver can reconstruct the signal for that user and subtract it from the total received signal, then decode the next highest ranked user data in the same way, and so on until all data decoding is complete.
The signal-to-interference-and-noise ratio of the smart meter n on the subcarrier s is represented as follows:
Figure BDA0002548663200000035
wherein p isnsRepresenting the transmission power of a smart meter n on a subcarrier s, n0Which is indicative of the power of the noise,
Figure BDA0002548663200000036
represents the path loss, dnIs the linear distance between the smart meter n and the AP, and mu > 2 is a path loss factor. Arrival rate R of smart meter n on subcarrier sns＝B log2(1+ns) Where B is the bandwidth of the subcarrier. Therefore, the arrival rate of the smart meter n can be expressed as:
Figure BDA0002548663200000041
the computing task of the intelligent electric meter n is represented as In＝{αn,βn}，αnRepresenting task InSize of (1), betanIndicating completion of task InThe number of CPU cycles required. By xnRepresenting whether the smart meter n selects local computation or task offloading, xn1 denotes unloading a task, xn0 denotes local processing. In the invention, each smart meter can process the task locally or unload the task to remote processing, and only one subcarrier can be used at most, so that the method comprises the following steps:
Figure BDA0002548663200000042
considering local calculations with
Figure BDA0002548663200000043
Representing the CPU computing power of the smart meter n, task InThe local computation time of (c) is:
Figure BDA0002548663200000044
the corresponding local computing energy consumption is:
Figure BDA0002548663200000045
wherein κnAre hardware dependent constants. Cost function and completion task InTime delay of
Figure BDA0002548663200000046
And energy consumption
Figure BDA0002548663200000047
About, expressed as:
Figure BDA0002548663200000048
wherein
Figure BDA0002548663200000049
And
Figure BDA00025486632000000410
respectively, are weighting factors for latency and energy consumption. For example, if the smart meter n has extremely high latency requirements, it may be set
Figure BDA00025486632000000411
When task InWhen the calculation is unloaded to the AP, the task completion time
Figure BDA00025486632000000412
Mainly comprises two parts: uplink transmission time
Figure BDA00025486632000000413
And calculating time
Figure BDA00025486632000000414
Namely, it is
Figure BDA00025486632000000415
Wherein
Figure BDA00025486632000000416
fnIs the computing resource that the AP allocates to the smart meter n. If the task is executed locally, i.e. xn0, then fn0. In the present invention, assuming that the computational power of the AP server is sufficiently strong, intelligence is offloaded for eachCalculation resource quantity f of electricity meter distributionnIs stationary.
The total energy consumption under the condition of task unloading consists of three parts, namely task unloading energy consumption, remote calculation energy consumption and result downloading energy consumption. Since the invention is focused on smart meter perspective and the AP server is usually powered by the grid, only considering the energy consumption of the calculation task offloading process are:
Figure BDA00025486632000000417
wherein
Figure BDA00025486632000000418
Is the efficiency of the power amplifier of the smart meter. Therefore, the cost function of n task unloading of the intelligent electric meter is as follows:
Figure BDA00025486632000000419
total cost function and offload decision xnSubcarrier allocation ansAnd the location of the smart meter. The method optimizes the unloading decision, and simultaneously considers the influence of the position of the intelligent electric meter on the formation of the alliance so as to reduce the total cost function to the maximum extent. The sum of the cost functions for all SMs is:
Figure BDA0002548663200000051
as shown in fig. 1, the task offloading method based on the alliance game in the power internet of things system specifically includes:
(1) all the intelligent electric meters in the same region are accessed to the AP through wireless connection, and the intelligent electric meters are represented as a set
Figure BDA0002548663200000052
Based on the nonorthogonal multiple access NOMA technology, a plurality of smart meters can be connected to the AP by using the same subcarrier, and the smart meters sharing the same subcarrier form a alliance, wherein the subcarrier set is expressed as S ═ 1,2,...,S}；
(2) The intelligent electric meter has a calculation task In＝{αn,βnThe data can be processed locally or unloaded to the AP through a subcarrier; establishing a cost function of the intelligent ammeter, and dividing the cost function into a cost function in local calculation
Figure BDA0002548663200000053
And cost function when task is unloaded
Figure BDA0002548663200000054
The method comprises energy consumption and time delay; all the intelligent electric meters have the same computing resources required for processing computing tasks; the calculation resources distributed to each intelligent electric meter by the AP are the same; the computing resources of each intelligent electric meter are different;
(3) all the intelligent electric meters in the network sequentially select a strategy, namely the joined alliance, and calculate the unloading profit, wherein the unloading profit is related to a cost function and is expressed as
Figure BDA0002548663200000055
Is that the intelligent electric meter n is in alliance
Figure BDA0002548663200000056
The unloading profit. Federation
Figure BDA0002548663200000057
The sum of the uninstalled profits of all the intelligent electric meters in the alliance is the utility
Figure BDA0002548663200000058
All intelligent electric meters and APs in the network establish a alliance game;
(4) each intelligent electric meter selectively joins in a alliance with the maximum utility through comparison; after all the intelligent electric meters select the strategies, calculating the total utility R of the network;
(5) all the intelligent electric meters sequentially execute a strategy which is one iteration; the computing resources required by all the intelligent electric meters for task unloading are the same, and the AP distributes the computing resources for the intelligent electric meters selected for task unloading; after the system carries out one iteration, the strategy of some intelligent electric meters in the network is changed, the number of the intelligent electric meters in each alliance is increased or reduced, and therefore the connection state of each intelligent electric meter in the network needs to be updated;
(6) and the game reaches Nash equilibrium, all the intelligent electric meters in the network do not change the strategy any more, and each intelligent electric meter selects to process the task locally or unload the task to the AP for execution according to the strategy and obtains the computing resource distributed by the AP according to the subcarrier used under the unloading condition.
Wherein, the step (1) is performed
Figure BDA0002548663200000059
Represents a set of federations, where for any i ≠ j, there is
Figure BDA00025486632000000510
And is
Figure BDA00025486632000000511
When k is more than or equal to 1 and less than or equal to S, the alliance
Figure BDA00025486632000000512
A set of SMs representing task offloading with subcarrier k; when k is more than or equal to S +1 and less than or equal to S + N, alliance
Figure BDA00025486632000000513
Represents a collection of electricity meters that perform computing tasks locally.
Utility function of alliance in step (3)
Figure BDA00025486632000000514
The calculation formula of (2) is as follows:
Figure BDA00025486632000000515
federation
Figure BDA0002548663200000061
The utility of (a) is that the smart meter can obtain the total calculation unloading profit by using the subcarrier k, and at the moment, the smart meter can obtain the total calculation unloading profitTables perform the computational tasks locally without any benefit, and their appropriate selection of offload decisions and subcarrier allocation can reduce the cost function. When k is more than or equal to S +1 and less than or equal to S + N,
Figure BDA0002548663200000062
namely, the smart meter performs the task locally.
In the alliance game of the method provided in the step (3), the participants are all the intelligent electric meters in the electric power Internet of things system. The intelligent electric meter is provided with a calculation task and can select local processing or unload the task to the AP for processing; based on NOMA, multiple smart meters can share the same subcarrier. The cost function of the intelligent electric meter is related to energy consumption and time delay. The league game is described as follows:
participant Player: all the intelligent electric meters in the network are integrated into
Figure BDA0002548663200000063
Federation Coolant: the union is set as
Figure BDA0002548663200000064
Wherein, for any i ≠ j, there are
Figure BDA0002548663200000065
And is
Figure BDA0002548663200000066
Strategy Strategy: the strategy of each participant is to decide whether to offload and the subcarriers used to compute offload in case of offload according to its utility on each federation;
utility function: federation
Figure BDA0002548663200000067
Is expressed as
Figure BDA0002548663200000068
Is the total amount of all smart meters in the alliance that utilize subcarrier kCalculating the income;
the total cost function of step (4) can be expressed as:
Figure BDA0002548663200000069
the nash equilibrium solving process of the league game in the step (6) is as follows:
the initial state of the network is random. And i and t respectively represent the number of iterations and the number of continuous unsuccessful switching operations (comparison times), the initial value is set to be zero, and the switching operation means that the intelligent electric meter leaves from one alliance and then joins in another alliance. Wherein the number t of consecutive unsuccessful handover operations is set to increase the convergence speed and reduce the complexity of the algorithm. If the smart meter performs the switching operation, t is reset to zero, otherwise it is incremented by one. When T reaches a suitable set value T, the algorithm will stop and assume that steady state has been reached.
Selecting one intelligent electric meter according to the preset arrangement, randomly selecting one alliance different from the alliance where the intelligent electric meter is currently located by the intelligent electric meter, and calculating the utility of the two alliances and the unloading profits of all the intelligent electric meters in the two alliances;
comparing the utility of the two alliances, if the income of other electric meters is not influenced, the intelligent electric meter selects to join the alliance with higher utility, and the alliance state is updated;
after the system carries out one iteration, the strategy of some intelligent electric meters in the network is changed, the number of the intelligent electric meters accessed in each alliance is increased or reduced, the network connection state is comprehensively updated, and each intelligent electric meter reselects the alliance to carry out a new iteration;
and fifthly, the alliance game reaches Nash equilibrium, all the intelligent electric meters in the network do not change strategies any more, and each intelligent electric meter selects local processing calculation tasks or unloads the tasks and subcarriers used under the unloading condition to obtain calculation resources distributed by the AP for task unloading.
The technical means disclosed in the invention scheme are not limited to the technical means disclosed in the above embodiments, but also include the technical scheme formed by any combination of the above technical features.

Claims (5)

1. A task unloading method based on alliance game in an electric power Internet of things system is characterized in that: the method comprises the following steps:
(1) all the intelligent electric meters in the same area are accessed to the AP through wireless connection; based on the NOMA, a plurality of intelligent electric meters can be connected to the AP by using the same subcarrier, and the intelligent electric meters using the same subcarrier form a coalition;
(2) the intelligent electric meter has a calculation task and is locally processed or unloaded to the AP through a subcarrier for processing; establishing a cost function of the intelligent ammeter, wherein the cost function is divided into a cost function in local calculation and a cost function in task unloading and consists of energy consumption and time delay; all the intelligent electric meters have the same computing resources required for processing computing tasks; the calculation resources distributed to each intelligent electric meter by the AP are the same; the computing resources of each intelligent electric meter are different;
(3) sequentially selecting strategies, namely adding alliances, for all the intelligent electric meters in the network, and calculating unloading profits, wherein the unloading profits are related to cost functions, and the sum of the unloading profits of all the intelligent electric meters in the alliances is the effectiveness of the alliances; all intelligent electric meters and APs in the network establish a alliance game;
(4) each intelligent electric meter selectively joins in a alliance with the maximum utility through comparison; after all the intelligent electric meters select the strategies, calculating the total utility of the network;
(5) all the intelligent electric meters sequentially execute a strategy which is one iteration; the computing resources required by all the intelligent electric meters for task unloading are the same, and the AP distributes the computing resources for the intelligent electric meters selected for task unloading; after the system carries out one iteration, the strategy of some intelligent electric meters in the network is changed, the number of the intelligent electric meters in each alliance is increased or reduced, and therefore the connection state of each intelligent electric meter in the network needs to be updated;
(6) and the game reaches Nash equilibrium, all the intelligent electric meters in the network do not change the strategy any more, and each intelligent electric meter selects to process the task locally or unload the task to the AP for execution according to the strategy and obtains the computing resource distributed by the AP according to the subcarrier used under the unloading condition.
2. The task offloading method based on alliance game in power internet of things system according to claim 1, characterized in that: in the cost function in the step (2), under the condition that the optimal alliance of each intelligent electric meter is selected, the sum of the total cost functions of the whole network is minimum.
3. The task offloading method based on alliance game in power internet of things system according to claim 1, characterized in that: the description of the league game in the step (3) is as follows:
participant Player: all the intelligent electric meters in the network are integrated into
Figure FDA0002548663190000011
Federation Coolant: the union is set as
Figure FDA0002548663190000012
Wherein, for any i ≠ j, there are
Figure FDA0002548663190000013
And is
Figure FDA0002548663190000014
Strategy Strategy: the strategy of each participant is to decide whether to offload and the subcarriers used to compute offload in case of offload according to its utility on each federation;
utility function: federation
Figure FDA0002548663190000015
Is expressed as
Figure FDA0002548663190000016
Is all using sub-carrier k in the federationAnd (4) total calculation income obtained by the intelligent electric meter.
4. The task offloading method based on alliance game in power internet of things system according to claim 1, characterized in that: the specific processes of the steps (4) and (5) are as follows:
federation
Figure FDA0002548663190000021
The utility of (a) is expressed as:
Figure FDA0002548663190000022
in the formula (I), the compound is shown in the specification,
Figure FDA0002548663190000023
representing the cost function of the smart meter when performing local calculations,
Figure FDA0002548663190000024
representing a cost function when the smart meter unloads the tasks to the AP for processing by using the subcarrier k, calculating the unloading benefit of each strategy executed by the smart meter, and selecting the strategy with the highest utility by contrast, wherein the total utility function of the network is as follows:
Figure FDA0002548663190000025
5. the task offloading method based on alliance game in power internet of things system according to claim 1, characterized in that: in the step (6), the league game reaches Nash equilibrium, and the solving process is as follows:
the initial state of the network is random. Respectively representing iteration times and continuous unsuccessful switching operation times by using i and t, setting an initial value to be zero, and switching operation means that the intelligent electric meter leaves from one alliance and then joins in another alliance; wherein the number of successive unsuccessful handover operations t is set to increase the convergence rate and reduce the algorithm complexity; if the intelligent electric meter executes the switching operation, resetting t to zero, otherwise adding one to the t; when T reaches a suitable set value T, the algorithm will stop and assume that a steady state has been reached;
selecting one intelligent electric meter according to the preset arrangement, randomly selecting one alliance different from the alliance where the intelligent electric meter is currently located by the intelligent electric meter, and calculating the utility of the two alliances and the unloading profits of all the intelligent electric meters in the two alliances;
comparing the utility of the two alliances, if the income of other electric meters is not influenced, the intelligent electric meter selects to join the alliance with high utility, and the alliance state is updated;
after the system carries out one iteration, the strategy of some intelligent electric meters in the network is changed, the number of the intelligent electric meters accessed in each alliance is increased or reduced, the network connection state is comprehensively updated, and each intelligent electric meter reselects the alliance to carry out a new iteration;
and fifthly, the alliance game reaches Nash equilibrium, all the intelligent electric meters in the network do not change strategies any more, and each intelligent electric meter selects local processing calculation tasks or unloads the tasks and subcarriers used under the unloading condition to obtain calculation resources distributed by the AP for task unloading.
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