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Fog computing task unloading method for Internet of Things

A fog computing and Internet of Things technology, applied in the field of fog computing task offloading for the Internet of Things, which can solve problems such as unbearable transmission delay, reducing end-user satisfaction with service quality, and communication bandwidth burden.

Active Publication Date: 2019-08-06
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, with the surge in traffic in recent years, the transmission of large-capacity data to cloud servers not only brings a heavy burden on communication bandwidth, but also causes unbearable transmission delays, which reduces end-user satisfaction with service quality Spend

Method used

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  • Fog computing task unloading method for Internet of Things
  • Fog computing task unloading method for Internet of Things
  • Fog computing task unloading method for Internet of Things

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Embodiment Construction

[0075] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0076] figure 1 A two-layer cellular heterogeneous network model consisting of FN and IoT devices is described. Considering that the 5G small cell network is composed of the next generation core network (Next Generation Core network, NGC) and the radio access network (Radio Access Network, RAN). exist figure 1 Among them, the RAN side is mainly composed of R FNs and U IoT devices. It is assumed that each IoT device has tasks that require a large amount of computing resources to be completed, and different IoT devices have different delay sensitivities and energy consumption sensitivities. Each IoT can choose to offload tasks to connected FN computing or local computing. Suppose a group of FNR={1, 2, 3,..., r,..., R}, each FN has a certain number of RBs, use N={1, 2, 3,..., N} express. Assume a group of IoT devices U={1, 2, 3, ..., u, ...

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Abstract

The invention relates to a fog computing task unloading method for the Internet of Things, and belongs to the technical field of mobile communication. According to the method, bidirectional matching joint modeling are carried out task unloading decisions, transmission resource allocation and computing resource allocation, and FN and IoT equipment to minimize the total overhead problem of the system. Firstly, QoS requirements of the IoT equipment are analyzed based on an analytic hierarchy process, and priorities are established according to different QoS requirements of the IoT equipment; secondly, RB allocation is conducted on the IoT devices, and the number of RBs needed by every IoT equipment is determined; then, computing resource allocation is carried out, and the computing time delayis determined. Based thereon, a bi-directional matching game is established, and a stable association between the FN and the IoT device requesting offloading is determined. And finally, every IoT equipment makes an unloading decision according to the task local computing overhead and the task unloading computing overhead. According to the invention, the total time delay and the energy consumptioncost of the system are reduced, and the stability of IoT equipment association and the effectiveness of resource allocation are realized.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to an Internet of Things-oriented fog computing task offloading method. Background technique [0002] A central goal in 5G mobile networks is to provide people with ubiquitous connectivity, enabling access to all applications and services anytime, anywhere. The Internet has moved to a cloud-based structure, and cloud computing provides end users with outsourced computing and storage functions. However, with the surge in traffic in recent years, the transmission of large-capacity data to cloud servers not only brings a heavy burden on communication bandwidth, but also causes unbearable transmission delays, which reduces end-user satisfaction with service quality Spend. In addition to real-time interaction and low-latency issues, support for mobility and geographic distribution is also critical as mobile users and traffic increase. In order to meet the high requirements ...

Claims

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Application Information

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IPC IPC(8): H04L12/24H04W28/24H04W28/18H04W28/20H04W28/22
CPCH04L41/0893H04L41/0896H04L41/5051H04W28/18H04W28/20H04W28/22H04W28/24Y02D30/70
Inventor 黄晓舸崔艺凡张东宇陈前斌
Owner CHONGQING UNIV OF POSTS & TELECOMM
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