Name
Abstract | ||
|---|---|---|
With the growing popularity of mobile devices, a new paradigm called mobile crowdsourcing emerged in the recent years. Mobile users with restricted computational capability and sensing ability are now able to conduct complex tasks with the help of other users in the same mobile crowdsourcing system. In this paper, we consider the mobile crowdsourcing system model 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 operating cost of some crowdsourcing tasks and the other focusing on minimizing the overall completion time of tasks belonging to the same project. Correspondingly, under offline settings, we propose an optimal algorithm and an approximation algorithm for these two problems respectively. The optimality and the approximation ratio are analyzed accordingly. Based on these two algorithms, we further design two online algorithms to deal with the problems under online settings and their competitive ratios are computed. Finally, we verify the effectiveness and efficiency of the proposed methods through extensive numerical experiments on synthetic datasets. |
Year | Venue | Field |
|---|---|---|
2018 | ICSOC | Online algorithm,Approximation algorithm,Social network,Mobile social network,Scheduling (computing),Crowdsourcing,Computer science,Real-time computing,Mobile device,System model,Distributed computing |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
16 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiahao Fan | 1 | 0 | 1.01 |
| Xinbo Zhou | 2 | 2 | 0.75 |
| Xiaofeng Gao | 3 | 713 | 98.58 |
| guihai chen | 4 | 3537 | 317.28 |