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Peihang Lin

dblp:308/4452 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 100%
Theoretical computer science
1 paper
Computational geometry · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › wireless sensor network › data collection
mobile data gathering
0.612022
Objective-Variable Tour Planning for Mobile Data Collection in Partitioned Sensor Networks · IEEE Trans. Mob. Comput. 2022
Internet of things and sensor networks
wireless sensor network
0.612022
Objective-Variable Tour Planning for Mobile Data Collection in Partitioned Sensor Networks · IEEE Trans. Mob. Comput. 2022
Computational geometry › motion planning
path planning
0.212022
Objective-Variable Tour Planning for Mobile Data Collection in Partitioned Sensor Networks · IEEE Trans. Mob. Comput. 2022

Methods — techniques the papers use, named apart from their topics

rendezvous point selection · 1.1genetic algorithm · 1.1convex hull algorithm · 1.1
YearPublicationVenuePosition
2022 Objective-Variable Tour Planning for Mobile Data Collection in Partitioned Sensor Networks
abstract
Data collection with mobile elements can improve energy efficiency and balance load distribution in wireless sensor networks (WSNs). However, complex network environments bring about inconvenience of path design. This work addresses the network environment issue, by presenting an objective-variable tour planning (OVTP) strategy for mobile data gathering in partitioned WSNs. Unlike existing studies of connected networks, our work focuses on disjoint networks with connectivity requirement and serves delay-hash applications as well as energy-efficient scenarios respectively. We first design a converging-aware location selection mechanism, which macroscopically converges rendezvous points (RPs) to lay a foundation of a short tour. We then develop a delay-aware path formation mechanism, which constructs a short tour connecting all segments by a new convex hull algorithm and a new genetic operation. In addition, we devise an energy-aware path extension mechanism, which selects appropriate extra RPs according to specific metrics in order to reduce the energy depletion of data transmission. Extensive simulations demonstrate the effectiveness and advantages of the new strategy in terms of path length, energy depletion, and data collection ratio.
Xuxun Liu 0001, Peihang Lin, Tang Liu 0001, Tian Wang 0001, Anfeng Liu, Wenzheng Xu
IEEE Trans. Mob. Comput.2