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Multi-task cross-server resource allocation method based on bidirectional auction in MEC
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A technology of server resources and allocation methods, applied in the field of mobile edge computing resource allocation, can solve problems such as inapplicability and low system efficiency
Active Publication Date: 2019-12-06
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology
However, the current method is only suitable for single-server task resource allocation, not for cross-server resource allocation, and the system efficiency is low; there may be a large number of people in the current base station coverage area (such as concentrated commercial buildings), and there are many MEC service requests. The task load of adjacent base stations may be very small. If the edge servers of multiple base stations can cooperate to form a system, more MEC service requests can be effectively served, and system efficiency can be improved.
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Embodiment 1
[0156] DAMB incentive mechanism:
[0157] (1) Sort the elements in A in ascending order:
[0158] A'=(a q1 =a 3 = 2, a q2 =a 1 = 3, a q3 =a 2 = 4, a q4 =a 5 = 5, a q5 =a 4 =6).
[0159] (2) Sort the elements in B in descending order:
[0165] (5) Delete greater than or equal to in A' Elements:
[0166] A c =(a 3 = 2, a 1 =3).
[0167] (6) find B c The first element in is b 2，3 = 10, because a 3 ∈A c , the task of buyer 2 can be offloaded to seller 3. From Table 2, we know that the App deployment status of Seller 3 is R 3 =(1, 0, 1, 0), the task that buyer 2 needs to handle is R 2 =(1, 1, ...
Embodiment 2
[0178] ASDA Incentive Mechanism
[0179] (1) Sort the elements in A in ascending order:
[0180] A'=(a q1 =a 3 = 2, a q2 =a 1 = 3, a q3 =a 2 = 4, a q4 =a 5 = 5, a q5 =a 4 = 6);
[0181] (2) Start traversing from the first element of A', for a 3 =2 It is known from Table 2 that seller 3 has deployed App1 and App3. Suppose we randomly choose App1 to start the auction. All bids for seller 3App1 are extracted from B. Q from Table 2 1 and Q 2 It can be seen that only Buyer 1 and Buyer 2 need services, and we will form the extracted bids into a new vector Then buyer 2 is the winner, b 1，3 =9 is the highest bid for losing the bid. N ω ={2},M ω = {3}, φ(2) = 3, g 2，3 = 1, r 3，1 =0,q 2，1 =0. by Q 1 , Q 2 and Q 3 It can be seen that Buyer 1, Buyer 2, and Buyer 3 need App3, and we extract all bids for seller 3App3 from B Then buyer 2 is the winner, b 1，3 =9 is the highest bid for losing the bid. N ω ={2},M ω ={3},g 2，3 = 2, r 3，3 =0,q 2，3 =0.
[01...
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Abstract
The invention discloses a multi-task cross-serverresource allocation method based on bidirectional auction in MEC. The multi-task cross-serverresource allocation method comprises the following steps: acquiring the type and quantity information of an application program deployed by each edge server of a seller, and determining the price information of each edge server of the seller for processinga single task; acquiring the type, the number and the maximum tolerance delay information of the to-be-processed task of each mobile device of the buyer; determining bidding information of each to-be-processed task in each mobile device of the buyer; and only publishing the offer information and the bid information to the auction party, determining the price and the winner of the two parties according to the price strategy by the auction party, and completing resource allocation according to the winner information of the two parties, wherein the price strategy is a bidirectional auction mechanism based on a profit and loss balance point or a bidirectional auction mechanism applying separation. The multi-task cross-server resource allocation method provided by the invention has relativelyhigh system efficiency.
Description
technical field [0001] The invention belongs to the technical field of mobile edge computing resource allocation, in particular to a two-way auction-based multi-task cross-server resource allocation method in MEC. Background technique [0002] Mobile Edge Computing (Mobile Edge Computing, MEC) is an emerging computing architecture, which can provide mobile devices (Mobile device, MD) with low latency and high reliability through mobile-enhanced and small-scale data centers, namely edge servers. Sexual computing services. Due to resource constraints, only a limited number of apps can be deployed on an edge server. An MD may have multiple different application requirements at the same time, and the nearest edge server may not be able to meet its requirements. If multiple tasks are offloaded to other edge servers, it not only solves the problem that a single edge server cannot meet the requirements of MD, but also can make reasonable use of the resources of edge servers and i...
Claims
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Application Information
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