Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Longhao Yi

dblp:413/8240 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2025
—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.

Theoretical computer science
1 paper
Approximation and online algorithms · 67% Algorithmic game theory and mechanism design · 33%
Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Approximation and online algorithms › online algorithms
competitive analysis
0.912025
Task Scheduling Mechanism for Crowdsourcing in Mobile Social Networks · IEEE Trans. Mob. Comput. 2025
Algorithmic game theory and mechanism design › mechanism design
crowdsourcing
0.912025
Task Scheduling Mechanism for Crowdsourcing in Mobile Social Networks · IEEE Trans. Mob. Comput. 2025
Approximation and online algorithms › online algorithms
online scheduling
0.912025
Task Scheduling Mechanism for Crowdsourcing in Mobile Social Networks · IEEE Trans. Mob. Comput. 2025
Ubiquitous computing and smart environments
mobile crowdsourcing
0.312025
Task Scheduling Mechanism for Crowdsourcing in Mobile Social Networks · IEEE Trans. Mob. Comput. 2025

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

competitive analysis · 1.7approximation algorithms · 0.9approximation algorithm · 0.9
YearPublicationVenuePosition
2025 Task Scheduling Mechanism for Crowdsourcing in Mobile Social Networks
abstract
With the popularization of smart phones, mobile crowdsourcing emerged and gained growing attention in the recent years. Mobile users are now able to conduct complex tasks with the communication between each other. In this paper, we study the task scheduling problem in the mobile crowdsourcing systems based on the spontaneously formed mobile social networks (MSNs). We introduce two crowdsourcing task scheduling problems under this system model, with one problem aiming to minimize the total cost of some crowdsourcing tasks and the other focusing on minimizing the final completion time of the tasks belonging to the same project. We introduce a unified framework to solve the problems and propose two approximation algorithms for these two problems in the offline versions respectively and prove Their approximation ratios accordingly. Based on the two algorithms, we further design two online algorithms to deal with the workers' dynamism and also analyze their competitive ratios. Finally, we verify the effectiveness and efficiency of the proposed methods through numerical experiments on real and synthetic datasets.
Longhao Yi, Xiaofeng Gao 0001, Shahzad Sarwar Bhatti, Guihai Chen
IEEE Trans. Mob. Comput.2