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Jun Zhang 0112

dblp:29/4190-112 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0007-7262-2772ORCID · verified

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 · 87% Network measurement and analytics · 13%

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

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › lora networks
lora network deployment
0.712023
Citywide LoRa Network Deployment and Operation: Measurements, Analysis, and Implications · SenSys 2023
Internet of things and sensor networks
LPWAN
0.712023
Citywide LoRa Network Deployment and Operation: Measurements, Analysis, and Implications · SenSys 2023
Network measurement and analytics
network performance measurement
0.212023
Citywide LoRa Network Deployment and Operation: Measurements, Analysis, and Implications · SenSys 2023

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

large-scale deployment measurement · 0.7
YearPublicationVenuePosition
2023 Citywide LoRa Network Deployment and Operation: Measurements, Analysis, and Implications
abstract
LoRa, as a representative Low-Power Wide-Area Network (LPWAN) technology, holds tremendous potential for various city and industrial applications. However, as there are few real large-scale deployments, it is unclear whether and how well LoRa can eventually meet its prospects. In this paper, we demystify the real performance of LoRa by deploying and measuring a citywide LoRa network, named CityWAN, which consists of 100 gateways and 19,821 LoRa end nodes, covering an area of 130 km2 for 12 applications. Our measurement focuses on the following perspectives: (i) Performance of applications running on the citywide LoRa network; (ii) Infrastructure efficiency and deployment optimization; (iii) Physical layer signal features and link performance; (iv) Energy profiling and cost estimation for LoRa applications. The results reveal that LoRa performance in urban settings is bottlenecked by the prevalent blind spots, and there is a gap between the gateway efficiency and network coverage for the infrastructure deployment. Besides, we find that LoRa links at the physical layer are susceptible to environmental variations, and LoRa and other LPWANs show diverse costs for different scenarios. Our measurement provides insights for large-scale LoRa network deployment and also for future academic research to fully unleash the potential of LoRa.
Shuai Tong, Jiliang Wang, Jing Yang 0052, Yunhao Liu 0001, Jun Zhang 0112
SenSys5