Evidence map›Paper›PMID 29659535›Full record

ArticleSensors (Basel, Switzerland)2018

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

Xujing Li, Anfeng Liu, Mande Xie, Neal N Xiong, Zhiwen Zeng, Zhiping Cai

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  4. QoS in Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xujing LiSchool of Information Science and Engineering, Central South University, Changsha 410083, China. xujingli@csu.edu.cn.
Anfeng LiuSchool of Information Science and Engineering, Central South University, Changsha 410083, China. afengliu@mail.csu.edu.cn.ORCID 0000-0001-5190-4761
Mande XieSchool of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China. xiemd@zjgsu.edu.cn.
Neal N XiongDepartment of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK 74464, USA. xiongnaixue@gmail.com.ORCID 0000-0002-0394-4635
Zhiwen ZengSchool of Information Science and Engineering, Central South University, Changsha 410083, China. zengzhiwen@mail.csu.edu.cn.
Zhiping CaiDepartment of Network Engineering, School of Computer, National University of Defense Technology, Changsha 410073, China. zpcai@nudt.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 ( N t ) or the waiting time is equal to the aggregation timer ( T t ), 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 ( T t ) and the aggregation threshold ( N t ) 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 T t and N t to reduce delay, and the nodes near the sink are set to a large value of T t and N t 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%.

Indexed as

aggregation delayaggregation ratiodata aggregationenergy efficiencywireless sensor networks

Identifiers

PMID29659535
PMCPMC5948754

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.