Evidence map›Paper›PMID 29734718›Full record

ArticleSensors (Basel, Switzerland)2018

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks.

Ahmadreza Vajdi, Gongxuan Zhang, Junlong Zhou, Tongquan Wei, Yongli Wang, Tianshu Wang

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ahmadreza VajdiSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. vajdi@njust.edu.cn.ORCID 0000-0001-7411-851X
Gongxuan ZhangSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. gongxuan@njust.edu.cn.
Junlong ZhouSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. jlzhou@njust.edu.cn.ORCID 0000-0002-7734-4077
Tongquan WeiDepartment of Computer Science and Technology, East China Normal University, Shanghai 200062, China. tqwei@cs.ecnu.edu.cn.ORCID 0000-0002-7421-1711
Yongli WangSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. yongliwang@njust.edu.cn.
Tianshu WangSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China. wangtianshu122@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

Indexed as

energy efficiencyfuzzy decision systemmobile sinkrendezvous point planningwireless sensor network

Identifiers

PMID29734718
PMCPMC5981768

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.