Finding
Comprehensive evaluation shows that considering the two design requirements of time delay and energy penalty, the performance of this method is better than traditional data distribution methods.
Paper
A Method of Multi Protocol Data Distribution in Heterogeneous Network
Citations: 1
Full textAbstract
The rapid development of cross technology communication promotes the transformation from single network to heterogeneous wireless network, which greatly improves the efficient coexistence and collaboration of heterogeneous wireless devices, but also brings challenges to data distribution in heterogeneous wireless networks. Traditional data distribution schemes are limited by the communication range of a single node and conflict between different network devices, resulting in continuous decline in the efficiency of data distribution. At the same time, they are not suitable for the unique network model of heterogeneous networks. In order to solve these problems, a data distribution method based on multi protocol parallel data transmission in heterogeneous wireless networks is proposed. The key idea is to use the Parallel Multi-protocol Communication (PMC) node as the transmitting node of the ZigBee network, and define a new system COST function to measure the delay and energy penalty of the system. Through adaptive adjustment of the trade-off coefficient in the function, it can depict the data transmission of various requirements. Based on the system COST function, the paper propose a distribution strategy of delayed receiving packets using beacon control that allows ZigBee to choose the appropriate timing to receive data in a heterogeneous network. Furthermore, the paper proved the rationality of the COST function, and then derived the optimal values of the overall energy penalty and time delay of the system based on the idea of dynamic programming. Comprehensive evaluation shows that considering the two design requirements of time delay and energy penalty, the performance of this method is better than traditional data distribution methods.
Authors
Jianhang Liu, Wan-Chen Wu, Shuqing Wang
Journal
Journal name not available for this finding