Wireless Multiple Access Network With a Sectional Configured Data Collection System and Codeword Filtering Mechanism

Abstract

Swarm robotics is an approach to collective robotics with which it is easily possible to complete the tasks that are difficult to do with single robot. The wireless multiple access network contributes significantly in wireless mobile swarm robotics for communication and networking, especially in disaster scenarios. Since the unpredictable impacts may fail the sensing robots or nodes, causing the loss of valuable data, a coding scheme called the Growth codes is designed to increase data persistence. In the wireless multiple access network, a key requirement of data collection in disaster scenarios is to maintain a high data intermediate recovery rate. In the later period of the Growth codes, the large amount of redundant data in the network affects the efficiency of data collection. In this paper, we design and analyze techniques to reduce the number of redundant data, and propose a sectional configured data collection strategy based on the Growth codes, called the SCGC protocol. Setting cache nodes around the sink to filter the redundant codewords, the sink can collect data faster, ensuring a high data intermediate recovery rate. We also design an information update strategy and some constraints to control node overhead. Through the simulations, we show that the proportion of redundant codewords can be reduced by 10-15%, while the negative impact of these valid codewords is not considered in the Growth codes. We also show that the SCGC protocol can improve the data recovery efficiency without affecting the stability of the network or shortening the network lifetime.

Keywords

• Codeword filtering
• data recovery efficiency
• multiple access
• nodes scheduling
• swarm robotics
• wireless network