A long-term allocation method of computing resources based on mobile device cloud
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A technology for computing resources and mobile devices, applied in digital transmission systems, data exchange networks, electrical components, etc., to solve problems such as large network delays, network congestion, and impact on user experience.
Active Publication Date: 2020-12-08
GUANGDONG UNIV OF TECH
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Embodiment 1
[0028] A long-term allocation method of computing resources based on mobile device cloud, please refer to figure 2 , including the following steps:
[0029] S1: The mobile device cloud consists of a group of mobile devices that can provide idle computing resources, first define a m is the provider, that is, mobile devices that provide computing resources, m=1, 2, 3,..., M, M is the total number of mobile devices that provide computing resources; define u i is the user, that is, the mobile device that applies for computing resources, i=1, 2, 3,..., N, N is the total number of users, and the base station is the arbitrator of resource allocation. Then, each a m Submit the number of idle computing resources to the base station, each u i The number of resources submitted to the base station and for each resource provider a m bid Users will bid according to the computing power of the computing resource provider, the number of computing resources they own, and their own compu...
Embodiment 2
[0046] suppose u 1 with a budget of 20, u 2 with a budget of 10, u 3 The budget is 20. The following table shows the user's bid for the resource provider, and the number of computing resources requested by the user and the number of idle resources of the resource provider are respectively in brackets.
[0047] u 1 (3)
u 2 (4)
u 3 (3)
a 1 (5)
2 3 4 a 2 (4)
3 5 2
[0048] 1) The initial value is 0,
[0049] User's final bid = (submitted bid) * (1-bid coefficient);
[0050] 2) Calculate the bid density (user final bid / user resource application volume);
[0051] u 1 (3)
u 2 (4)
u 3 (3)
a 1 (5)
2 / 3 3 / 4 4 / 3 a 2 (4)
1 5 / 4 2 / 3
[0052] 3) The user with the fewest resource applications and the highest bid wins (u 2 , u 3 );
[0053] 4) Calculate payment price and allocate resources. (The VCG mechanism is a classic auction mechanism. For simplicity, this example does not use VCG to calculate th...
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Abstract
The invention discloses a method for long-term distribution of computing resources based on mobile device cloud, which comprises the following steps: (1) each user submits the number of computing resource requirements and the bidding information for each resource provider, and each resource provider submits the number of idle resources; (2) the base station calculates the final bid of the user according to the collected information and the bid coefficient of the user; (3) the base station published the resource allocation scheme and calculates the payment amount of the winning user; (4) the bidding coefficients of the winning users are adjusted; (5) the above steps are repeated until the end of the entire system cycle. The invention considers the time correlation of the computing resourcesand the budget constraint, adjusts the bidding coefficient according to the residual budget of the user in each round of the computing resource allocation, so that the cloud computingresource allocation of the mobile equipment is more fair and reasonable, the energy consumption of the user is reduced, and the service life of the mobile equipment is prolonged.
Description
technical field [0001] The present invention relates to the field of mobile device cloud resource allocation, and more particularly, relates to a long-term allocation method of computing resources based on mobile device cloud. Background technique [0002] In recent years, mobile devices including smartphones are ubiquitous in people's daily life. Although the performance of mobile devices has been greatly improved, they are still limited by battery power and computing power. For example, face recognition, natural languageprocessing, large-scale mobile games, etc., need to offload tasks to remote servers for execution and then return the results. This will not only bring a large network delay, but also cause network congestion and affect user experience. In order to solve this problem, we can offload the task to other surrounding devices for execution and pay certain compensation for it. When the surrounding devices have no available resources, they can be offloaded to the...
Claims
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