Xiangrong Tong
Biographic Data
| ID | 10055797 |
|---|---|
| NAME | Xiangrong Tong |
| GIVEN NAMES | Xiangrong |
| FAMILY NAME | Tong |
| SIGNATURE | TONG X |
| AFFILIATIONS | Yantai University |
| ORCID | 0000-0003-4855-3723 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
A Real-Time Route Prediction-Based Multiobjective Task Allocation for Opportunistic Mobile Crowdsensing
With the widespread use of mobile networks and smart devices, opportunistic mobile crowdsensing (MCS) has emerged as one of the most promising sensing paradigms for intelligent data. In Opportunistic MCS, the real-time mobility of participants and requesters is a crucial feature, as it significantly impacts the quality of MCS services. However, most existing task allocation approaches focus on optimizing the overall system performance while disre…
Mobile Crowdsourcing Quality Control Method Based on Four-Party Evolutionary Game in Edge Cloud Environment
Mobile crowdsourcing (MCS) is a new paradigm that uses various mobile devices to collect sensed data. Mobile edge computing (MEC) can effectively utilize the device resources of mobile edge, greatly relieve the pressure of network bandwidth and improve the response speed. In this article, we construct a four-party evolutionary game model consisting of the platform, crowd workers, task requesters, and edge servers. The computing tasks are conducte…
Three-Party Evolutionary Game Model of Stakeholders in Mobile Crowdsourcing
As a new paradigm to solve problems by gathering the intelligence of crowds, mobile crowdsourcing has become one of the hot spots in academic and industrial fields. Task requester, platform, and crowd workers are stakeholders in mobile crowdsourcing, which inevitably leads to conflicts of interest. In order to solve this problem, this article constructs a three-party evolutionary game model among task requester, platform, and crowd workers. This …
Walrasian Equilibrium-Based Multiobjective Optimization for Task Allocation in Mobile Crowdsourcing
With the rapid development of Industry 5.0 and mobile devices, the research of mobile crowdsensing networks has become an important research focus. Task allocation is an important research content that can inspire crowd workers to participate in crowd tasks and provide truthful sensed data in mobile crowdsourcing systems. However, how to inspire crowd workers to participate in crowd tasks and provide truthful sensed data still has many challenges…
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Walrasian Equilibrium-Based Multiobjective Optimization for Task Allocation in Mobile Crowdsourcing
With the rapid development of Industry 5.0 and mobile devices, the research of mobile crowdsensing networks has become an important research focus. Task allocation is an important research content that can inspire crowd workers to participate in crowd tasks and provide truthful sensed data in mobile crowdsourcing systems. However, how to inspire crowd workers to participate in crowd tasks and provide truthful sensed data still has many challenges…
Three-Party Evolutionary Game Model of Stakeholders in Mobile Crowdsourcing
As a new paradigm to solve problems by gathering the intelligence of crowds, mobile crowdsourcing has become one of the hot spots in academic and industrial fields. Task requester, platform, and crowd workers are stakeholders in mobile crowdsourcing, which inevitably leads to conflicts of interest. In order to solve this problem, this article constructs a three-party evolutionary game model among task requester, platform, and crowd workers. This …
Mobile Crowdsourcing Quality Control Method Based on Four-Party Evolutionary Game in Edge Cloud Environment
Mobile crowdsourcing (MCS) is a new paradigm that uses various mobile devices to collect sensed data. Mobile edge computing (MEC) can effectively utilize the device resources of mobile edge, greatly relieve the pressure of network bandwidth and improve the response speed. In this article, we construct a four-party evolutionary game model consisting of the platform, crowd workers, task requesters, and edge servers. The computing tasks are conducte…
A Real-Time Route Prediction-Based Multiobjective Task Allocation for Opportunistic Mobile Crowdsensing
With the widespread use of mobile networks and smart devices, opportunistic mobile crowdsensing (MCS) has emerged as one of the most promising sensing paradigms for intelligent data. In Opportunistic MCS, the real-time mobility of participants and requesters is a crucial feature, as it significantly impacts the quality of MCS services. However, most existing task allocation approaches focus on optimizing the overall system performance while disre…
Computer Science (4 works) · Computer security (4 works) · Mobile Crowdsensing and Crowdsourcing (4 works) · Crowdsourcing (3 works) · Engineering (3 works) · Computer network (2 works) · Crowds (2 works) · Crowdsensing (2 works) · Game theory (2 works) · Human Mobility and Location-Based Analysis (2 works)