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Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect and upload sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive…

网络与互联网体系结构 · 计算机科学 2014-12-25 Jiajun Sun

Crowd sensing is a new paradigm which leverages the ubiquity of sensor-equipped mobile devices to collect data. To achieve good quality for crowd sensing, incentive mechanisms are indispensable to attract more participants. Most of existing…

计算机科学与博弈论 · 计算机科学 2014-05-01 Jiajun Sun

Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive mechanisms are…

计算机科学与博弈论 · 计算机科学 2014-03-24 Jiajun Sun

Mobile Crowdsensing has shown a great potential to address large-scale problems by allocating sensing tasks to pervasive Mobile Users (MUs). The MUs will participate in a Crowdsensing platform if they can receive satisfactory reward. In…

计算机科学与博弈论 · 计算机科学 2018-08-14 Jiangtian Nie , Zehui Xiong , Dusit Niyato , Ping Wang , Jun Luo

Vehicular mobile crowd sensing is a fast-emerging paradigm to collect data about the environment by mounting sensors on vehicles such as taxis. An important problem in vehicular crowd sensing is to design payment mechanisms to incentivize…

计算机科学与博弈论 · 计算机科学 2018-09-17 Susu Xu , Weiguang Mao , Yue Cao , Hae Young Noh , Nihar B. Shah

Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces…

社会与信息网络 · 计算机科学 2016-11-15 Pin-Yu Chen , Shin-Ming Cheng , Pai-Shun Ting , Chia-Wei Lien , Fu-Jen Chu

Mobile crowdsensing has emerged as an efficient sensing paradigm which combines the crowd intelligence and the sensing power of mobile devices, e.g.,~mobile phones and Internet of Things (IoT) gadgets. This article addresses the…

网络与互联网体系结构 · 计算机科学 2017-02-16 Mohammad Abu Alsheikh , Yutao Jiao , Dusit Niyato , Ping Wang , Derek Leong , Zhu Han

Mobile crowdsensing (MCS) is a promising sensing paradigm that leverages the diverse embedded sensors in massive mobile devices. A key objective in MCS is to efficiently schedule mobile users to perform multiple sensing tasks. Prior work…

计算机科学与博弈论 · 计算机科学 2017-05-18 Changkun Jiang , Lin Gao , Lingjie Duan , Jianwei Huang

Mobile crowd sensing (MCS) is a new paradigm which leverages the ubiquity of sensor-equipped mobile devices such as smartphones, music players, and in-vehicle sensors at the edge of the Internet, to collect data. The new paradigm will fuel…

网络与互联网体系结构 · 计算机科学 2014-10-01 Jiajun Sun

Crowd sensing is a new paradigm which leverages a large number of sensor-equipped mobile phones to collect sensing data. To attract more participants to provide good quality, bidding mechanisms that solicit the Vickrey-Clarke-Groves (VCG)…

计算机科学与博弈论 · 计算机科学 2014-08-20 Jiajun Sun

Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond the scale of what was previously possible. In a mobile crowdsensing system, it is paramount to incentivize smartphone users to provide…

网络与互联网体系结构 · 计算机科学 2018-05-01 Francesco Restuccia , Pierluca Ferraro , Simone Silvestri , Sajal K. Das , Giuseppe Lo Re

Mobile crowdsensing leverages mobile devices (e.g., smart phones) and human mobility for pervasive information exploration and collection; it has been deemed as a promising paradigm that will revolutionize various research and application…

网络与互联网体系结构 · 计算机科学 2013-08-22 Kai Han , Chi Zhang , Jun Luo

Mobile crowdsourced sensing (MCS) is a new paradigm which takes advantage of the pervasive smartphones to efficiently collect data, enabling numerous novel applications. To achieve good service quality for a MCS application, incentive…

计算机科学与博弈论 · 计算机科学 2013-06-25 Dong Zhao , Xiang-Yang Li , Huadong Ma

Mobile crowdsensing (MCS) has been intensively explored recently due to its flexible and pervasive sensing ability. Although many incentive mechanisms have been built to attract extensive user participation, Most of these mechanisms focus…

计算机科学与博弈论 · 计算机科学 2015-05-15 Jiajun Sun

Mobile Crowd Sensing (MCS) is a new paradigm which takes advantage of pervasive smartphones to efficiently collect data, enabling numerous novel applications. To achieve good service quality for a MCS application, incentive mechanisms are…

计算机科学与博弈论 · 计算机科学 2014-04-10 Dong Zhao , Huadong Ma , Liang Liu

The prosperity of smart mobile devices has made mobile crowdsensing (MCS) a promising paradigm for completing complex sensing and computation tasks. In the past, great efforts have been made on the design of incentive mechanisms and task…

多智能体系统 · 计算机科学 2020-11-26 Yize Chen , Hao Wang

The recent proliferation of increasingly capable mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to a crowd of participating workers that carry various mobile devices. Aware…

计算机科学与博弈论 · 计算机科学 2017-01-09 Haiming Jin , Lu Su , Klara Nahrstedt

In this paper, we study the incentive mechanism design for real-time data aggregation, which holds a large spectrum of crowdsensing applications. Despite extensive studies on static incentive mechanisms, none of these are applicable to…

计算机科学与博弈论 · 计算机科学 2017-12-27 Zhikun Zhang , Shibo He , Mengyuan Zhang , Jiming Chen

To overcome the limited coverage in traditional wireless sensor networks, \emph{mobile crowd sensing} (MCS) has emerged as a new sensing paradigm. To achieve longer battery lives of user devices and incentive human involvement, this paper…

信息论 · 计算机科学 2018-01-01 Xiaoyang Li , Changsheng You , Sergey Andreev , Yi Gong , Kaibin Huang

Mobile crowdsensing has shown a great potential to address large-scale data sensing problems by allocating sensing tasks to pervasive mobile users. The mobile users will participate in a crowdsensing platform if they can receive…

计算机科学与博弈论 · 计算机科学 2018-11-01 Jiangtian Nie , Jun Luo , Zehui Xiong , Dusit Niyato , Ping Wang
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