Unloading time delay optimization method in mobile edge computing scene

An edge computing and optimization method technology, applied in the field of wireless communication, can solve the problems of large delay consumption and achieve the effect of minimizing the total unloading delay

Active Publication Date: 2019-08-09
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0010] The purpose of the present invention is to provide an offloading delay optimization method in a mobile

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  • Unloading time delay optimization method in mobile edge computing scene
  • Unloading time delay optimization method in mobile edge computing scene
  • Unloading time delay optimization method in mobile edge computing scene

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Embodiment

[0097] In the present invention, the reinforcement learning algorithm DQN is used to learn the NOMA-MEC system to find the best user combination scheme to minimize the total system delay. Basic process such as figure 2 As shown, 2M users can all be used as agents for learning. Taking user k as an example, in time slot t, user k chooses an action, that is, chooses a user as his transmission partner, acts on the environment, makes the environment reach the next state, and returns a reward value R to user k to reward user k The selected actions are evaluated. The goal of RL is to find an appropriate fixed policy π:s→a that probabilistically maps state s to action a in order to optimize the agent's cumulative long-run utility V. User k will change the strategy according to the feedback of the environment, adjust the action to the direction of increasing the reward value, and finally make the long-term utility, that is, the unloading delay, reach the optimum.

[0098] The prese...

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Abstract

The invention aims to provide an unloading delay optimization method in a mobile edge computing scene. The method comprises the following steps: step 1, constructing a system model, wherein the systemmodel comprises 2M users and an MEC server, each user has L tasks and needs to be unloaded to the MEC server for calculation, and it is assumed that only two users are allowed to adopt a mixed NOMA strategy to unload at the same time; step 2, setting each user as an executor, and performing action selection by each executor according to a DQN algorithm, i.e., selecting one user from the rest 2M-1users as the own transmission partner and unloading the transmission partner at the same time; step 3, performing system optimization by using a DQN algorithm: calculating the total unloading time delay of the system, updating a reward value, then training a neural network, and updating a Q function by using the neural network as a function approximator after the selection of all users is completed; and continuously carrying out the iterative optimization on the system until the optimal time delay is found. The problem of high time delay consumption in the existing multi-user MEC scene is solved.

Description

[0001] 【Technical field】 [0002] The invention belongs to the technical field of wireless communication, and in particular relates to an unloading delay optimization method in a mobile edge computing scenario. [0003] 【Background technique】 [0004] At present, the evolution of mobile communication networks to 5G is further accelerated. In the face of rapid traffic growth and user experience requirements, mobile communication networks will be under tremendous pressure. The emergence of Mobile Edge Computing (MEC) has effectively alleviated this pressure. By sinking the service platform with computing, storage, and communication capabilities to the edge of the network, MEC enables mobile users to offload their computing-intensive tasks to MEC devices, emphasizing proximity to mobile users to reduce network operation and service delivery delays. It has developed and evolved into an important technology for 5G mobile communication systems, and is currently widely used in all as...

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Application Information

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IPC IPC(8): H04L12/24H04L29/08G06N3/08G06N3/04
CPCH04L41/083H04L41/145H04L41/142H04L67/10G06N3/08G06N3/044G06N3/045
Inventor 李立欣杨佩彤梁微李旭张会生程岳
Owner NORTHWESTERN POLYTECHNICAL UNIV
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