A group intelligence perceptual network incentive method based on an endowment effect

Abstract

The invention discloses a group intelligence perceptual network incentive method based on an endowment effect, relating to the technical field of computer network communication. As that introduction of endowment compensation change the winning probability of the service node with low preference in the anti-auction mechanism, the profit of the service node is not zero in the initial compensation time, the participation of the service node is prevent from being prematurely abandon, and the endowment compensation is dynamically updated, and the endowment compensation acquisition is combined withthe participation times, so that the service node increase the participation desire under the effect of the endowment effect, and therefore the participation degree of the service node in the technical proposal of the application is higher. The difficulty of obtaining the endowment compensation is inversely related to the compensation times, so the payment cost is not too high, and the system utility of the invention is higher because the increase degree of the participation degree is greater than the increase degree of the payment cost.

Description

technical field [0001] The present invention relates to the technical field of computer network communication, in particular to an endowment effect-based crowd sensing network incentive method. Background technique [0002] Crowd Sensing Network (Crowd Sensing Network) is a network model that stimulates participating nodes, uses their mobile capabilities and sensing devices to perceive data, and finally completes large-scale data collection tasks. In the crowd sensing system, the nodes are divided into two types: service requesting nodes and service providing nodes. The main body of each type of node is a person carrying smart phones, portable computers and other intelligent perception devices. The relationship between the service parties in crowd sensing is similar to a buyer-seller relationship. The provider gets paid by completing tasks for the requester, and the requester pays by collecting the provider's services. However, providers often expect to get more rewards, w...

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Problems solved by technology

[0003] However, most of the current incentive mechanisms aim to increase participation, reduce payment costs, and improve the utility of both parties as the ultimate goal. However, they generally have two problems: 1) Neglecting the loss avoidance of nodes, the node loss The utility is equal to the utility when the same amount of profit is made; 2) Assume that the initial property rights allocation is irrelevant to the final resource allocation; thus resulting in a deviation between the node decision-making and the actual situation, and ultimately failing to maximize the incentive target

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