Home > Academic & Technology > Improved Distributed Algorithm to Optimize Coverage Control in Mobile Sensor Networks

Improved Distributed Algorithm to Optimize Coverage Control in Mobile Sensor Networks

This paper is originally the short version of my thesis or final project for my bachelor degree. The contents consist of what I’ve written in ICIUS 2010 and adapted idea of paper I wrote in 8th IEEE ICNSC 2011. Adapted idea means that I adopted some algorithms from paper published in 8th IEEE ICNSC 2011 and modified it to what I need in my thesis, in this case for limited range anisotropic sensor. This paper was planned to be published in a journal but I still don’t have any sponsor to publish it. Moreover, the way I wrote this paper is also not well-organized. Currently, I’m reorganizing the paper flow.

This paper is also one of the three researches I did during my spare time in last semester of my bachelor study.

As my thesis, this paper definitely has been presented in my final seminary on December, 8th, 2010. The following is the abstract of this research:

In the deployment of mobile sensor networks, some agents may be initialized far away from region of interest and due to the sensor’s limited sensing of range, some sensors detect no information. Without any information, agents have no capability to move. As a result, some sensors may not able to participate in the coverage task. This paper describes how to solve this problem by implementing leader-following algorithm in a distributed control algorithm. An anisotropic mobile sensor model is considered. Then, an improved distributed coverage control algorithm is presented. In addition, energy and dynamic sensing of each mobile sensor is also considered. A power-aware distributed coverage control algorithm is also proposed to reduce energy consumption and optimize coverage ability. Moreover, it is assumed that each agent is equipped with omni-directional communication capability. A distributed control algorithm based on gradient descent is implemented to drive robots to the region of interest. Simulations illustrate the results.

The next actions for this research will be:

  1. Considering the dynamic communication graph (still an idea)
  2. 3 dimensions including odd environment (still an idea)
  3. Non-convex environment (still an idea)

To see/download the paper click here.

Happy to discuss,

Best regards,

Risvan Dirza

Categories: Academic & Technology
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