CN115328650B - Edge node distribution method for maximizing system profit based on intelligent contracts - Google Patents

Edge node distribution method for maximizing system profit based on intelligent contracts Download PDF

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CN115328650B
CN115328650B CN202210963665.7A CN202210963665A CN115328650B CN 115328650 B CN115328650 B CN 115328650B CN 202210963665 A CN202210963665 A CN 202210963665A CN 115328650 B CN115328650 B CN 115328650B
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ecn
dso
edge node
bid
service provider
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CN115328650A (en
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殷昱煜
吴昆澄
李玉
李尤惠子
梁婷婷
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Hangzhou Dianzi University
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Hangzhou Dianzi University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5066—Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5072—Grid computing

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Abstract

The invention discloses an edge node distribution method for maximizing system profit based on intelligent contracts. The invention designs a matching mechanism based on intelligent contracts, and matches ECNs with DSOs according to the calculation frequency of each ECN and the corresponding preference values of different DSOs for ECN calculation capacity and trust degree. Secondly, the invention provides an improved bidirectional auction mechanism based on intelligent contracts, after the bid matrix of the UT is uploaded in the system, the existing bid matrix and elements in the bid matrix are subjected to serialization processing, and under the trusted bidirectional auction mechanism, the benefit maximum value in the sequence is continuously and iteratively updated to complete bidirectional matching of the DSO and the UT. The invention can realize automatic and efficient transaction between network entities according to intelligent contracts and maximize system profit.

Description

Edge node distribution method for maximizing system profit based on intelligent contracts
Technical Field
The invention relates to the field of edge computing, in particular to an edge node distribution method for maximizing system profit based on intelligent contracts.
Background
In the future, the advent of hundreds of billions of intelligent devices will create a range of very delay sensitive services. In order to meet the service requirements, the User Terminals (UTs) need to handle a large number of computationally intensive tasks, which tends to accelerate energy consumption and shorten their service life. Edge computing networks solve these problems by allowing UTs to offload computing tasks to edge nodes (ECNs) deployed nearby.
Currently, most edge devices require a central authority for resource allocation, however, the central authority may not be trusted and is susceptible to single point failure. To solve the above problems, blockchains are introduced to build tamper-resistant ledgers to manage distributed edge computing network transactions automatically performed by smart contracts. In practical applications, the present invention refers to a data service provider (DSO) as a proxy device, coordinating transactions between UTs and ECNs, since the resources of a distributed ECN are typically invisible to UTs. In order to offload tasks to the ECN for execution, the UT needs to pay the proper lease, how to design the intelligent contracts for edge node allocation so that the DSO, ECN and UT together with the benefit maximization is a problem that should be considered by the distributed edge computing network.
The core problems to be solved have two points: (1) Each DSO has different preferences for ECN depending on the trustworthiness and computational power of the ECN. How to deal with competition between multiple DSO proxy devices for ECN leases per unit time is the first core problem to be solved; (2) The reliability and computing power of different users for ECNs will give different price orientations, and selecting the appropriate ECN to perform UT task offloading in what manner per unit time is another core problem to be solved to maximize the overall profit of the edge network.
Disclosure of Invention
Aiming at the problem of selecting an edge node for task offloading of a user terminal in a blockchain scene, a two-stage transaction association mechanism (namely ECN-DSO association based on a matching mechanism and DSO-UT association based on a two-way auction) is provided, namely an edge node allocation method based on intelligent contract maximization system profit. First, the present invention designs a matching mechanism based on intelligent contracts, which establishes one-to-many lease associations between DSOs and ECNs. Second, the present invention proposes an improved two-way auction mechanism based on intelligent contracts, establishing lease associations between DSOs and UTs, and determining the pricing of the winner.
The edge node distribution method based on intelligent contract maximization system profit is mainly divided into two parts:
(1) ECN-DSO associated intelligent contract based on matching mechanism
The smart contract includes the steps of:
step 1: based on the k transaction information of ECN, a transaction reputation Rep (e i ) As standardized quality of service in the ith transaction, calculating its long-term confidenceWherein e i Indicating the ith transaction information.
Step 2.1: each ECN uploads the calculated frequency f and calculates the ECN profit function γ=R- ζκ (f) by invoking the ECN-DSO associated smart contract upload function 2 Wherein R is lease provided by DSO, and is related to f and theta in step 1; ζ is the reference cost per CPU cycle, κ (f) 2 Is the energy consumed by one CPU cycle.
Step 2.2: the ECN-DSO associated smart contract verifies the ECN calculation frequency f and the trustworthiness θ.
Step 3: each DSO uploads the lease R in step 2.1 and calculates the DSO profit function ψ=Λ (θ) -R by calling the ECN-DSO associated smart contract upload function, where Λ (·) is an estimated revenue function positively correlated with the ECN calculation frequency f and the trustworthiness θ.
Step 4: a matching function is called to establish an association between the ECN and the DSO.
Step 4.1: in round t, the ECN-DSO associated smart contract estimates the profit offered by the DSO for the unmatched ECN according to the calculated profit function of step 2.1, provides the highest profit DSO for each ECN signature, counts the number of ECNs that have the same DSO, and is denoted as l.
Step 4.2: when the number of ECNs/associated with a DSO exceeds the maximum number of ECNs O that it can match in step 4.1, the ECN-DSO associated smart contract calculates the profit ψ provided by each ECN for that DSO according to step 3 and sorts the DSO in order of big to small profit, then matches the DSO with the previous O-bit ECNs while setting the number of ECNs that the next round of DSOs can match to 0.
Step 4.3: when the number l of ECNs associated with the DSO in the step 4.1 does not exceed the maximum number O of ECNs which can be matched, the ECN-DSO associated intelligent contract matches the DSO with the ECNs, and sets the number of ECNs which can be matched by the DSO in the next round as O-l.
Step 4.4: and stopping running the ECN-DSO associated intelligent contract when the number of ECNs which can be matched by the DSO is 0, otherwise repeating the steps 4.1, 4.2 and 4.3.
(2) DSO-UT associated intelligent contract based on bidirectional auction
The smart contract includes the steps of:
step 5: uploading DSO's key price matrix to different UTs regarding their rented ECN by invoking a DSO-UT-associated smart contract upload function based on a two-way auctionAnd bid matrix +.for different UTs with respect to different ECNs>
Step 6: matrix is formedAll the ask prices contained in the list are sorted according to ascending order, so that an ascending order sequence related to the ask prices is obtained. The sequence value was marked +.>Deletion is higher than +.>Returns a new sequence +.>Become a candidate seller. Will->All bids in (a) are ordered in descending order, deletion is less than +.>Is not less than the median ask +.>The minimum bid is the threshold bid +.>Return to the new sequence->Become a candidate buyer.
Step 7.1: for sequencesFrom the sequence +.>The received bids are sorted in descending order (when the bids are identical, a random arrangement is performed) to construct a bid sequence beta for the ECN. Adding the highest bid in the sequence to the highest bid set BETA (1) And consider the corresponding UT as the potential winning buyer for the ECN.
Step 7.2: from beta (1) One buyer UT is randomly selected as the aggregate BETA (1) Creates a new set v for the bids provided by the UTs and calculates the set v for the UTs (1) The ith UT in (b) calculates the UT profit functionWherein (1)>Is the bid for the ith UT and P is the true lease, i.e., true bid, delivered by that UT to the successfully matched ECN.
Step 7.3: copying the bid sequence BETA of each ECN in step 7.1 to beTo determine the real lease of the UT and to maintain it unchanged throughout the auction process.
Step 8.1: each ECN device is operated as follows in each iteration: eliminating UTs successfully associated with other ECNs in the last iteration in the bid sequence BETA, and recording BETA 0 Is the highest bid in the new sequence BETA and is arranged in the sequenceR-th bit of (b). When r is the sequence->At the last digit of (1), the real lease P is set to the threshold bid B in step 6 t Otherwise, the real rent P is set to +.>Bid price of bit r+1.
Step 8.2: in step 8.1, the UT selected in step 7.2 has given a true bid for a portion of the ECN, and after having given a partial true bid, the DSO-UT associated smart contract invokes the calculate profit function of step 7.2 to calculate the possible profit ω of the UT, from which the ECN that can provide the maximum profit value for the UT is selected to be associated with, while being added to the DSO-UT associated smart contract.
Step 9: after the ECN is successfully matched with the UT, the UT pays the true rent P leasing the ECN in the step 8.1 to the DSO-UT association intelligent contract, and the DSO-UT association intelligent contract provides the reward value in the step 6 to the DSO having the ECN after receiving the rentThe DSO pays the lease R to the leased ECN upon receiving the prize value.
Step 10: successfully associated UTs and ECNs will be added to the winning UT set and the winning ECN set, respectively. And corresponding bids and ask prices from the seller sequence in step 6And buyer sequence->To avoid double association.
Step 11: by iteratively operating steps 8.1 and 8.2 until beta in step 7.1 (1) For null, DSO-UT association smart contracts are proxied by establishing UTs and DSOsTo establish one-to-one or many-to-one associations of UTs and DSOs.
The invention has the beneficial effects that: the present invention aims to maximize the system profit and develop a two-stage transaction mechanism. Firstly, providing a matching mechanism based on intelligent contracts to establish lease association between DSO and ECN; second, an improved two-way auction mechanism is presented to establish a lease association between the DSO and UT and determine the winner's pricing. Automatic and efficient transactions between network entities may be accomplished in accordance with smart contracts, as well as maximization of system profits.
Drawings
FIG. 1 is a block diagram of the components of the present method;
FIG. 2 is a logic diagram of an ECN-DSO matching mechanism;
FIG. 3 is a schematic flow diagram of a two-way auction based DSO-UT association smart contract;
FIG. 4 is a logical schematic diagram of a two-way auction mechanism;
fig. 5 is a matching relationship between DSO, ECN and UT.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention provides an edge node distribution method for maximizing system profit based on intelligent contract satisfaction. According to the intelligent contract, automatic and efficient transaction between network entities can be realized, and a two-stage transaction mechanism is developed with the aim of maximizing system profit. Firstly, establishing lease association between DSO and ECN according to the calculation frequency of each ECN and the corresponding preference values of different DSO for ECN calculation capability and trust degree; second, an improved two-way auction mechanism is presented to establish a lease association between the DSO and UT and determine the winner's pricing. The method mainly comprises two parts: 1) ECN-DSO associated intelligent contracts based on matching mechanisms; 2) DSO-UT-associated smart contracts based on two-way auctions.
FIG. 1 is a block diagram of the components of the present method. Wherein the DSO acts as a proxy device, on the one hand renting ECN devices by ECN-DSO associated smart contracts that are automatically executable in the blockchain; on the other hand, task offloading of the terminal equipment on the ECN equipment rented by the terminal equipment is completed through the DSO-UT associated intelligent contract. This process is stored in the overall blockchain structure as a block of transaction information with the aid of a consensus mechanism in a public ledger that is maintained together by each device in the system, thereby ensuring security and non-tamperability of decentralised distributed edge computing network transactions.
The method comprises the following specific steps:
(1) ECN-DSO associated intelligent contract based on matching mechanism
The part aims at maximizing the profit of ECN and DSO by establishing intelligent contracts, and realizes the matching between the ECN and the DSO. And pre-matching the ECNs with the DSO with the highest bid in each time slice according to the calculation frequency of each ECN and the corresponding preference value of different DSOs on the calculation capacity and the trust degree of the ECNs, and selecting the ECNs with the highest profit for the DSO to match when the number of the ECNs exceeds the matchable range of the DSO. Such a process is repeated until all ECN matches are completed. After this process is implemented, the DSO stores the ask matrix of its proxy ECN for its computing resources to complete subsequent further associations.
Step 1: based on the k transaction information of ECN, a transaction reputation Rep (e i ) As standardized quality of service in the ith transaction, calculating its long-term confidenceWherein e i Indicating the ith transaction information.
Step 2.1: each ECN uploads the calculated frequency f and calculates the ECN profit function γ=R- ζκ (f) by invoking the ECN-DSO associated smart contract upload function based on the matching mechanism 2 Wherein R is lease provided by DSO, and is related to f and theta in step 1; ζ is the reference cost per CPU cycle, κ (f) 2 Is the energy consumed by one CPU cycle.
Step 2.2: the ECN-DSO associated smart contract verifies the ECN calculation frequency f and the trustworthiness θ.
Step 3: each DSO uploads the lease R in step 2.1 and calculates the DSO profit function ψ=Λ (θ) -R by calling the ECN-DSO associated smart contract upload function, where Λ (·) is an estimated revenue function positively correlated with the ECN calculation frequency f and the trustworthiness θ.
Step 4: a matching function is called to establish an association between the ECN and the DSO.
Step 4.1: in round t, the ECN-DSO associated smart contract estimates the profit offered by the DSO for the unmatched ECN according to the calculated profit function of step 2.1, provides the highest profit DSO for each ECN signature, counts the number of ECNs that have the same DSO, and is denoted as l.
Step 4.2: when the number of ECNs associated with the DSO exceeds the maximum number of ECNs that it can match O in step 4.1, the ECN-DSO associated smart contract calculates the profit ψ provided by each ECN for the DSO according to step 3 and sorts the profit by big to small, then matches the DSO with the previous O bit ECNs while setting the number of ECNs that the next round of DSOs can match to 0.
Step 4.3: when the number l of ECNs associated with the DSO in the step 4.1 does not exceed the maximum number O of ECNs which can be matched, the ECN-DSO associated intelligent contract matches the DSO with the ECNs, and sets the number of ECNs which can be matched by the DSO in the next round as O-l.
Step 4.4: and stopping running the ECN-DSO associated intelligent contract when the number of ECNs which can be matched by the DSO is 0, otherwise repeating the steps 4.1, 4.2 and 4.3.
As shown in fig. 2, which is a logic diagram of an ECN-DSO matching mechanism, by calling the ECN-DSO association intelligent contract to upload the calculation frequency f for each ECN, each DSO uploads the estimated rent R, and the ECN is pre-matched with the DSO with the highest bid in each time slice. If the DSO's matchable range is exceeded, the DSO will choose to match the ECN for which it creates the highest profit. If the ECN devices in the system are not fully matched, then the process is repeated until the ECN devices in the system are fully matched.
(2) DSO-UT associated intelligent contract based on bidirectional auction
This section achieves matching between DSO and UT by establishing a smart contract targeting the DSO and UT together with maximization of win and determining the winner's pricing. After uploading the bid matrix of the UT in the system, the intelligent contract completes the bidirectional matching of the DSO and the UT by carrying out serialization processing on the existing bid matrix and the bid matrix and continuously iterating and updating the benefit maximum value in the sequence under a trusted bidirectional auction mechanism.
Step 5: uploading DSO's key price matrix to different UTs regarding their rented ECNs by invoking DSO-UT association smart contract upload functionsAnd bid matrix +.for different UTs with respect to different ECNs>
Step 6: matrix is formedAll the ask prices contained in the list are sorted according to ascending order, so that an ascending order sequence related to the ask prices is obtained. The median value is marked +.>Deletion is higher than +.>Returns a new sequence +.>Become a candidate seller. Will->All bids in (a) are ordered in descending order, deletion is less than +.>Is not less than the median ask +.>The minimum bid is the threshold bid +.>Return to the new sequence->Become a candidate buyer.
Step 7.1: for sequencesFrom the sequence +.>The received bids are sorted in descending order (when the bids are identical, a random arrangement is performed) to construct a bid sequence beta for the ECN. Adding the highest bid in the sequence to the highest bid set BETA (1) And consider the corresponding UT as the potential winning buyer for the ECN.
Step 7.2: from beta (1) One buyer UT is randomly selected as the aggregate BETA (1) Creates a new set v for the bids provided by the UTs and calculates the set v for the UTs (1) The ith UT in (b) calculates the UT profit functionWherein (1)>Is the bid for the ith UT and P is the true lease, i.e., true bid, delivered by that UT to the successfully matched ECN.
Step 7.3: copying the bid sequence BETA of each ECN in step 7.1 to beTo determine the real lease of the UT and to maintain it unchanged throughout the auction process.
Step 8.1: each ECN device is operated as follows in each iteration: eliminating UTs successfully associated with other ECNs in the last iteration in the bid sequence BETA, and recording BETA 0 Is the highest bid in the new sequence BETA and is arranged in the sequenceR-th bit of (b). When r is the sequence->At the last digit of (1), the real lease P is set to the threshold bid B in step 6 t Otherwise, the real rent P is set to +.>Bid price of bit r+1. Since one UT may be associated with multiple ECNs in this iteration, step 8.2 is set to select the appropriate ECN.
Step 8.2: in step 8.1, the UT selected in step 7.2 has given a true bid for a portion of the ECN, and after having given a partial true bid, the DSO-UT associated smart contract invokes the calculate profit function of step 7.2 to calculate the possible profit ω of the UT, from which the ECN that can provide the maximum profit value for the UT is selected to be associated with, while being added to the DSO-UT associated smart contract.
Step 9: after the ECN is successfully matched with the UT, the UT pays the true rent P leasing the ECN in the step 8.1 to the DSO-UT association intelligent contract, and the DSO-UT association intelligent contract provides the reward value in the step 6 to the DSO having the ECN after receiving the rentLease R calculated by DSO upon paying ECN-DSO association to leased ECN upon receipt of a prize value (see step 2.1 in matching mechanism based ECN-DSO association smart contract)
Step 10: successfully associated UTs and ECNs will be added to the winning UT set and the winning ECN set, respectively. And corresponding bids and ask prices from the seller sequence in step 6And buyer sequence->To avoid double association.
Fig. 3 is a schematic flow diagram of a two-way auction-based intelligent contract in which proxy devices propose reasonable ask prices for their leased edge node server devices while mobile terminal devices propose their own bids by invoking upload functions therein. The DSO-UT associated intelligent contract performs serialization processing on the ask price matrix and the bid price matrix, and a two-way auction mechanism is adopted to find proper pricing for an edge node server in the system. The intelligent contract agent then completes the relevant trade process, i.e. the mobile terminal device UT pays the true rent P of the leased ECN to the DSO-UT associated intelligent contract, and the DSO-UT associated intelligent contract provides the reward value to the DSO owning the ECN after receiving the rentThe DSO pays the lease R to the leased ECN upon receiving the prize value. The mobile terminal device indirectly completes the task offloading transaction in this manner.
Fig. 4 is a logic diagram of a bi-directional auction mechanism, in which after uploading the bid matrix of the DSO with respect to its proxy ECN and the bid matrix of the UT, the smart contract performs a serialization process on elements in the matrix, and under a trusted bi-directional auction mechanism, continuously iterates to update the benefit maximum in the sequence to complete bi-directional matching of the DSO and the UT.
Step 11: by iteratively operating steps 8.1 and 8.2 until beta in step 7.1 (1) To null, the DSO-UT association smart contract is developed by establishing a relationship between the UT and the ECN to which the DSO proxies. Wherein the DSO and ECN are in one-to-one or one-to-many relationship, and the DSO and UT are in one-to-one or one-to-many relationship. There is a one-to-one relationship between ECNs and UTs that is associated by DSOs. As shown in fig. 5.

Claims (3)

1. An edge node allocation method for maximizing system profit based on intelligent contracts, characterized by executing the following two contracts:
(1) ECN-DSO associated intelligent contract based on matching mechanism
The ECN-DSO associated smart contract includes the steps of:
step 1: based on the k transaction information of the edge node ECN, a transaction reputation Rep (e i ) Calculating long-term confidence as normalized quality of service in the ith transactionWherein e i Representing the ith transaction information;
step 2.1: each edge node ECN uploads the calculated frequency f and calculates an edge node ECN profit function γ=r- ζκ (f) by invoking an ECN-DSO associated smart contract upload function 2 Wherein R is lease provided by data service provider DSO, and is related to calculation frequency f and θ in step 1, ζ is reference cost, κ (f) caused by each CPU cycle 2 Is the energy consumed by one CPU cycle;
step 2.2: the ECN-DSO associated intelligent contract verifies the ECN calculation frequency f and the long-term reliability theta of the edge node;
step 3: each data service provider DSO uploads the lease R in step 2.1 and calculates a data service provider DSO profit function ψ=Λ (θ) -R by calling an ECN-DSO associated smart contract upload function, where Λ (·) is a revenue function positively correlated with the edge node ECN calculation frequency f and long term reliability θ;
step 4: invoking a matching function to establish an association between the edge node ECN and the data service provider DSO;
step 4.1: in round t, the ECN-DSO associated smart contract calculates the profit offered by the data service provider DSO for the unmatched edge nodes ECN according to the calculate edge node ECN profit function of step 2.1, marks the data service provider DSO that offers the highest profit for each edge node ECN, counts the number of edge nodes ECN that mark the same data service provider DSO, and marks l;
step 4.2: when the number l of edge nodes ECN associated with the data service provider DSO exceeds the maximum number O of matched edge nodes ECN in step 4.1, the ECN-DSO associated intelligent contract calculates the profit ψ provided by each edge node ECN in the sequence for the data service provider DSO according to step 3, and sorts the data service provider DSO from big to small, then matches the data service provider DSO with the previous O-bit edge node ECN, and sets the number of edge nodes ECN matched by the data service provider DSO in the next round to 0;
step 4.3: when the number l of edge nodes ECN associated with the data service provider DSO in the step 4.1 does not exceed the maximum value O of the number of matched edge nodes ECN, the ECN-DSO associated intelligent contract matches the data service provider DSO with the number l of edge nodes ECN, and simultaneously sets the number of edge nodes ECN matched by the data service provider DSO in the next round as O-l;
step 4.4: stopping running the ECN-DSO associated intelligent contract when the number of the edge nodes ECNs matched by the DSO of the data service provider is 0, otherwise repeating the steps 4.1, 4.2 and 4.3;
(2) DSO-UT associated intelligent contract based on bidirectional auction
The DSO-UT association intelligent contract comprises the following steps:
step 5: uploading data service provider DSO's asking price matrix to different user terminals UT with respect to leased edge node ECN by invoking DSO-UT associated intelligent contract uploading function based on bi-directional auctionAnd bid matrices +/for different user terminals UT with respect to different edge nodes ECN>
Step 6: matrix of asking priceAll the asking prices contained in the list are sorted in ascending order to obtain an ascending order sequence of asking prices, and the value in the sequence is marked as +.>Deletion is higher than +.>Returns a new sequence +.>Become a candidate seller;
will bid matrixAll bids in (a) are ordered in descending order, deletion is less than +.>Is not less than the median ask +.>The minimum bid is the threshold bid +.>Return to the new sequence->Become a candidate buyer;
step 7.1: for sequencesFrom the sequence +.>In order to order the bids in descending order, constructing a bid sequence B for the edge node ECN, adding the highest bid in the sequence to the highest bid set B (1) And regarding the corresponding user terminal UT as a potential winning buyer of the edge node ECN;
step 7.2: from the highest bid set B (1) A buyer user terminal UT is randomly selected as the highest bid set B (1) Creates a new set v for the bid offered by the user terminal UT and sets B for the highest bid (1) The i' th user terminal UT in the middle calculates the profit function of the user terminal UTWherein (1)>Is the bid of the ith user terminal UT, and P is the true rent delivered by the user terminal UT to the successfully matched edge node ECN, namely the true bid;
step 7.3: duplicating the bid sequence B of each edge node ECN in step 7.1 asAnd remains unchanged throughout the auction process;
step 8.1: each edge node ECN device operates as follows in each iteration: eliminating user terminals UT in the bid sequence B successfully associated with other edge nodes ECN in last iteration, note B 0 Is the highest bid in bid sequence B, side-by-side in sequenceR-th position in (a);
when r is a sequenceAt the last digit of (1), the real lease P is set to the threshold bid +.>Otherwise, the real rent P is set to +.>The (1) th bit of the bid price;
step 8.2: in step 8.1, the user terminal UT selected in step 7.2 has given a true bid to a part of edge nodes ECN, after the DSO-UT associated smart contract has given a partial true bid, the profit ω of the user terminal UT is calculated by calling the calculation profit function in step 7.2, and the edge node ECN providing the maximum profit value for the user terminal UT is selected therefrom to be associated therewith, while being added to the DSO-UT associated smart contract;
step 9: after the edge node ECN is successfully matched with the user terminal UT, the user terminal UT pays the real lease P leasing the edge node ECN in the DSO-UT association intelligent contract payment step 8.1, and the DSO-UT association intelligent contract provides the reward value in the step 6 to the data service provider DSO having the edge node ECN after the lease is received
The data service provider DSO pays the lease R to the leased edge node ECN upon receiving the bonus value;
step 10: the successfully associated user terminal UT and edge node ECN will be added to the winning set of user terminals UT and winning set of edge nodes ECN, respectively, and the corresponding bids and offers will be ordered from the seller sequence in step 6And buyer sequence->Delete in the middle;
step 11: by iteratively operating steps 8.1 and 8.2 until B in step 7.1 (1) To the air, the DSO-UT association smart contract establishes a one-to-one or many-to-one association of the user terminal UT and the data service provider DSO by establishing a one-to-one association between the user terminal UT and the edge node ECN to which the data service provider DSO is proxied.
2. An intelligent contract-based system according to claim 1An edge node allocation method for maximizing system profit, characterized in that: in step 7.1 for the sequenceFrom the sequence +.>The received bids are selected, ordered in descending order, and randomly arranged when a plurality of bids are the same.
3. An edge node allocation method for maximizing system profit based on intelligent contracts according to claim 1, wherein: there is a one-to-one relationship between the edge nodes ECN and the user terminals UT, which are associated by the data service provider DSO.
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