High-performance target tracking scheme with low prediction precision requirement in WSNs

Liu, Anfeng; Zhao, Shaona

doi:10.1504/ijahuc.2018.10016988

Cited by 9 publications

(1 citation statement)

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“…A wireless sensor network is a set of distributed hardware-constrained wireless devices that monitor a targeted area [ 6 , 7 , 8 , 9 , 10 , 11 ]. Wireless sensor networks are widely used in a variety of applications such as the environmental monitoring and urban health monitoring [ 12 , 13 , 14 ], healthcare [ 2 , 15 ], vehicular communication networks [ 16 ], cyber-physical cloud systems [ 17 ], multi-channel cognitive radio networks [ 18 , 19 ], crowdsourcing networks [ 20 , 21 , 22 ], and social networks [ 23 , 24 ]. Because of the growing demand for wireless sensor applications in various aspects, quality of service (QoS) is an important issue in wireless sensor applications [ 25 , 26 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Aggregation Routing to Reduce Delay for Multi-Layer Wireless Sensor Networks

Liu

Xie

et al. 2018

Sensors

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The quality of service (QoS) regarding delay, lifetime and reliability is the key to the application of wireless sensor networks (WSNs). Data aggregation is a method to effectively reduce the data transmission volume and improve the lifetime of a network. In the previous study, a common strategy required that data wait in the queue. When the length of the queue is greater than or equal to the predetermined aggregation threshold (Nt) or the waiting time is equal to the aggregation timer (Tt), data are forwarded at the expense of an increase in the delay. The primary contributions of the proposed Adaptive Aggregation Routing (AAR) scheme are the following: (a) the senders select the forwarding node dynamically according to the length of the data queue, which effectively reduces the delay. In the AAR scheme, the senders send data to the nodes with a long data queue. The advantages are that first, the nodes with a long data queue need a small amount of data to perform aggregation; therefore, the transmitted data can be fully utilized to make these nodes aggregate. Second, this scheme balances the aggregating and data sending load; thus, the lifetime increases. (b) An improved AAR scheme is proposed to improve the QoS. The aggregation deadline (Tt) and the aggregation threshold (Nt) are dynamically changed in the network. In WSNs, nodes far from the sink have residual energy because these nodes transmit less data than the other nodes. In the improved AAR scheme, the nodes far from the sink have a small value of Tt and Nt to reduce delay, and the nodes near the sink are set to a large value of Tt and Nt to reduce energy consumption. Thus, the end to end delay is reduced, a longer lifetime is achieved, and the residual energy is fully used. Simulation results demonstrate that compared with the previous scheme, the performance of the AAR scheme is improved. This scheme reduces the delay by 14.91%, improves the lifetime by 30.91%, and increases energy efficiency by 76.40%.

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