Location-Based Data Aggregation in 6LoWPAN

Abstract

Location-based information has recently been exploited to assist the aggregated process of data, thereby reducing the spatial redundancy efficiently. The constraints nature in 6LoWPAN becomes one of the major concerns in data aggregation methods. However, traditional CSMA/CA in MAC layer may cause significant transmission and control overhead as well as delay on listening and competing for channels. It is a low efficient way to transfer IPv6 packet due to the big packet header. To overcome these shortages, in this paper, we propose LDAA, a location-based novel data aggregation model that aggregates data from the network layer according to the MAC layer queuing delay. When the queuing delay becomes larger, more packets will be dynamically aggregated into one packet to increase the proportion of application data. Otherwise, the amount of packets involved in aggregation will decrease to improve channels utilization. Simulation results show that our approach could provide better real-time guarantees and reduce data spatial redundancy and energy consumption efficiently.