Complex task collaboration solving method based on reverse auction strategy in wireless sensor network

Abstract

The invention relates to a complex task collaboration solving method based on a reverse auction strategy in a wireless sensor network, which comprises four stages of: (1) laying tasks: a center cluster layers and divides the tasks according to the DAG graph of the tasks; (2) determining a collaborative cluster: the center cluster will send a message to a surrounding hop cluster for requesting assistance if the energy consumption degree of the center cluster exceeds a setting threshold; if the energy consume degree of the surrounding hop cluster does not exceed the setting threshold, the surrounding hop cluster will be the collaborative cluster of the center cluster; (3) distributing the tasks to a cluster head: the tasks in each layer is firstly disposed by the center cluster which distributes the tasks not distributed to the collaborative cluster; (4) distributing the tasks to nodes in the cluster by the cluster head: a second low-price sealing auction method is applied to the distribution of the tasks in the cluster, the cluster head is as an auction, the nodes in the cluster are as bidders, the auction selects the bidder bidding the lowest price to win the bidding, and the winning side trades at the second low price. The method achieves the energy balance of network nodes and prolongs network lifetime.

Description

Technical field [0001] The invention belongs to the field of wireless multimedia sensor networks, in particular, the invention relates to a method for solving complex tasks cooperatively in a wireless sensor network based on a reverse auction strategy, clustering and processing complex tasks in the network can improve task processing efficiency and balance network loads , to extend the life of the network. Background technique [0002] The relevant literature is as follows: [0003] 1. In 2007, Zhu Jinghua and others proposed a task allocation algorithm based on genetic algorithm-based nested optimization technology in multi-hop sensor networks in "Energy Efficient Task Allocation Algorithms in Wireless Sensor Networks". Task mapping, routing path allocation, task scheduling and dynamic voltage modulation to obtain the optimal allocation scheme, while achieving real-time application and high efficiency of energy utilization. [0004] 2. In 2010, Sherine Abdelhak et al. pro...

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Problems solved by technology

[0004] 2. In 2010, Sherine Abdelhak et al. proposed a task grouping method in "Energy-balancing Task Allocation on Wireless Sensor Networks for Extending the Lifetime", which can ensure the parallel processing of tasks, but when the same child task has several parent task, and the subtask is required to join the task teams of different parent tasks at the same time, no corresponding solution is provided.

This method can achieve the purpose of shortening the task processing time, but in the wireless sensor network, the node energy is limited and difficult to replenish, and the remaining energy of the node will decrease with the increase in the number of processing tasks, and its task processing performance is directly affected by effect, cannot remain constant

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