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Sparse Event Detection Method for Wireless Sensor Networks Based on Compressed Sensing and Game Theory

A wireless sensor and compressed sensing technology, applied in the field of wireless communication, can solve problems such as detection loopholes, large communication interference, and high cost

Active Publication Date: 2011-12-21
哈尔滨工大正元信息技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The purpose of the present invention is to solve the problem that when the sensor nodes placed randomly in the wireless sensor network are too dense, it will often cause greater communication interference, low detection accuracy, and high cost; on the contrary, if the placed nodes are too rare and other Randomness, there will be a problem of detecting loopholes, and a sparse event detection method for wireless sensor networks based on compressed sensing and game theory is provided.

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  • Sparse Event Detection Method for Wireless Sensor Networks Based on Compressed Sensing and Game Theory
  • Sparse Event Detection Method for Wireless Sensor Networks Based on Compressed Sensing and Game Theory
  • Sparse Event Detection Method for Wireless Sensor Networks Based on Compressed Sensing and Game Theory

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specific Embodiment approach 1

[0066] Specific implementation mode one: the following combination figure 1 Describe this embodiment, the wireless sensor network sparse event detection method based on compressed sensing and game theory described in this embodiment is based on compressed sensing and game theory wireless sensor network sparse event detection method, the method includes the following steps:

[0067] Step 1. Divide the M sensor nodes distributed randomly in the network system into levels using the idea of ​​game theory to form a level, which is a level strategy;

[0068] Step 2. Based on the principle of compressed sensing, determine the activation of one or more levels of sensor nodes according to the number K of ongoing events, and the number P of activated sensor nodes satisfies

[0069] K

[0070] Using the P sensor nodes to detect K events occurring in the N event sources;

[0071] Step 3: The network system data terminal receives the P-dimensional data vectors of the N event source...

specific Embodiment approach 2

[0076] Specific implementation mode 2: This implementation mode further explains the implementation mode 1. In step 1, the M sensor nodes randomly distributed in the network system are divided into levels using game theory to form a level, which is the process of a level strategy for:

[0077] Step 11, each sensor in the network system determines the sensor IDs of all neighbor nodes within the communication radius and the positional relationship of the neighbor nodes relative to itself by sending information;

[0078] The sensor ID is set when leaving the factory. Each sensor ID is different and is set to distinguish its identity, that is, the ID card of the sensor. Each sensor ID has a certain communication radius, and the size of the communication radius varies according to the sensor model. When a sensor sends information to the sensors of its neighbor nodes within the communication radius, it sends its own sensor ID and communication radius and other inherent parameters t...

specific Embodiment approach 3

[0088] Specific implementation mode three: this implementation mode further explains implementation mode one. In step two, the process of determining to activate one or more levels of sensor nodes according to the number K of ongoing events is:

[0089] The number P of activated sensor nodes satisfies K

[0090] P = Σ x = 1 y P x

[0091] The number y of activation levels can be determined,

[0092] In the formula, P x is the number of nodes in a certain level, y=1, 2, . . . a.

[0093] In order to achieve system optimization, when only K events occur, it is not necessary to call all the sensors, only a part of the sensors need to be called, and the other part of the sensors does not work. In this way, the requirements for detecting K events are met, and the minimum number of sensors is us...

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Abstract

The invention discloses a method for detecting wireless sensor network sparse events based on compressed sensing and the game theory, which belongs to the field of wireless communication and aims to solve the problem that excessively intensive sensor nodes randomly released in the wireless sensor network probably cause communication interface but sparse sensor nodes probably cause detection leak.The method disclosed by the invention comprises the following steps: (I) dividing M sensor nodes randomly released in the network system into a layers according to the thought of the game theory; (II) determining to activate one or more layers of sensor nodes according to the number (K) of the current events; (III) receiving a data vector y by a data terminal of the network system, and obtaining a measurement matrix [phi]P*N according to the detection process; and (IV) obtaining the specific distribution vector E of K happening events in N event sources by use of a greedy sparse event detection algorithm.

Description

technical field [0001] The invention relates to a sparse event detection method of a wireless sensor network based on compressed sensing and game theory, belonging to the field of wireless communication. Background technique [0002] With the need for remote monitoring of wireless sensor networks in recent years, the long-distance and large-scale data transmission poses a huge pressure on sensor nodes and even the entire communication line. The sensor network realizes the monitoring of environmental temperature, humidity, forest fire danger, etc., and the purpose is to obtain timely and accurate information about the occurrence of events. According to the sparsity characteristics of these events in time or space, the traditional event detection method is to deploy a corresponding number or even more sensors for the number of independent events. The purpose of doing this is to obtain better detection results and minimize detection errors. However, when the randomly placed s...

Claims

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Application Information

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IPC IPC(8): H04W24/00H04W84/18
Inventor 王强闫文杰沈毅
Owner 哈尔滨工大正元信息技术有限公司
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