Mobile sensing device computing task safe unloading method based on fuzzy game

Abstract

The invention discloses a mobile sensing device computing task safe unloading method based on a fuzzy game. The method comprises the following steps: (1) obtaining an unloading opportunity diagram ofa sensing device, the size of a cache space of an adjacent sensing device and the link channel confidential capacity of an edge computing node; (2) judging whether a related unloading side link channel is attacked or not and whether adjacent sensing equipment or an edge computing node is attacked or not to obtain an attack strategy adopted by an invisible attacker; (3) iteratively calculating themaximum income when the sensing equipment vs adopts the alternative task safety unloading strategy according to the fuzzy game until a Nash equilibrium condition is met, and selecting an optimal strategy; and (4) optimizing the task unloading rate of the sensing equipment to the edge computing node and the task unloading rate of the adjacent sensing equipment. According to the method, the unloading time delay is shortened, and the task unloading success rate is improved, so that a safe task unloading strategy is realized when the sensing equipment is subjected to invisible attacks in the calculation task unloading process.

Description

technical field [0001] The invention belongs to the technical field of the Internet of Things, and more specifically relates to a method for safely offloading calculation tasks of mobile sensing devices based on fuzzy games. Background technique [0002] As a service computing architecture, sensor edge cloud technology provides reliable computing resource services for resource-constrained sensor devices. Sensor devices can offload time-sensitive computing tasks from sensor devices to edge computing nodes for execution, thereby saving Computing resources for sensing devices and improving the processing performance of computing tasks. However, in the open sensing edge cloud computing environment, there are a large number of sensing devices and various types. The edge computing nodes in the sensing edge cloud receive computing tasks offloaded from massive sensing devices. Bandwidth and cache are vulnerable to attacks from malicious devices, thereby degrading the service qualit...

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Problems solved by technology

However, when both the channel and the cache are under attack, how to optimize the computing task offloading strategy to defend against the channel and cache attack, none of the above methods gives a suitable solution

[0007] (3) Although the existing solution methods propose some resource-optimized defense strategies, they do not consider the uncertainty of the attack strength of the invisible attacker, which makes the sensing edge cloud system unable to provide a matching computing task. uninstall strategy

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