Crowdlet: Optimal worker recruitment for self-organized mobile crowdsourcing

Pu, Lingjun; Xu, Cunyi; Xu, Jingdong; Fu, Xiaoming

doi:10.1109/infocom.2016.7524548

Cited by 74 publications

(35 citation statements)

References 22 publications

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“…e purpose is to minimize the task makespan by partitioning the total task into suitable subtasks corresponding to the encountered worker computation power. In [25], Pu et al use an online algorithm to maximize the task service quality based on worker's interest preference. Focusing on device-to-device networks, the authors study the recruitment problem when the crowdsourcing is delay-sensitive [26].…”

Section: Related Workmentioning

confidence: 99%

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Optimal Task Partition with Delay Requirement in Mobile Crowdsourcing

Zhai

Wang

2019

Wireless Communications and Mobile Computing

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Mobile crowdsourcing takes advantage of mobile devices such as smart phones and tablets to process data for a lot of applications (e.g., geotagging for mobile touring guiding monitoring and spectrum sensing). In this paper, we propose a mobile crowdsourcing paradigm to make a task requester exploit encountered mobile workers for high-quality results. Since a task may be too complex for a single worker, it is necessary for a task requester to divide a complex task into several parts so that a mobile worker can nish a part of the task easily. We describe the task crowdsourcing process and propose the worker arrival model and task model. Furthermore, the probability that all parts of the complicated task are executed by mobile workers is introduced to evaluate the result of task crowdsourcing. Based on these models, considering computing capacity and rewards for mobile workers, we formulate a task partition problem to maximize the introduced probability which is used to evaluate the result of task crowdsourcing. en, using a Markov chain, a task partition policy is designed for the task requester to realize high-quality mobile crowdsourcing. With this task partition policy, the task requester is able to divide the complicated task into precise number of parts based on mobile workers' arrival, and the probability that the total parts are executed by mobile workers is maximized. Also, the invalid number of task assignment attempts is analyzed accurately, which is helpful to evaluate the resource consumption of requesters due to probing potential workers. Simulations show that our task partition policy improves the results of task crowdsourcing.

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Section: Related Workmentioning

confidence: 99%

“…Note that our task model fits several mobile crowdsourcing tasks including location-based information finding tasks and content creation tasks. Here, we do the simulation based on the content creation tasks, and all task parameters are the same as in [25]. B, Ta i , D i , and R i are all in the unit of slots.…”

Section: Comparison Metricmentioning

confidence: 99%

Optimal Task Partition with Delay Requirement in Mobile Crowdsourcing

Zhai

Wang

2019

Wireless Communications and Mobile Computing

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“…In the outsourcing platform Amazon Mechanical Turk, the candidate workers are evaluated, compared, and selected for an outsourcing task based on their ability values, e.g., worker reputation and worker skills. In [10], a self-organized outsourcing toolkit, i.e., Crowdlet is proposed to employ a set of workers to execute the crowdsourcing task from the requester. In Crowdlet, a candidate worker is selected or not depends on the worker's service quality levels which are influenced by the skills, arrival time, and rewards of the worker.…”

Section: Ability-based Worker Selection In Crowdsourcingmentioning

confidence: 99%

A privacy-preserving exception handling approach for dynamic mobile crowdsourcing applications

Yan

2019

J Wireless Com Network

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The ever-increasing popularity of mobile devices (e.g., mobile phones and smart watches) has created a variety of crowdsourcing applications by employing the massive and distributed mobile computing resources. Typically, a task requester sends his/her task request and constraint conditions to a crowdsourcing platform, and then the crowdsourcing platform is responsible for finding a set of appropriate workers (e.g., mobile users) from massive candidates to satisfy the task request. However, for a mobile crowdsourcing task being executed by a set of workers, a pre-selected worker may become unavailable due to various exceptions. In this situation, it is significant for the crowdsourcing platform to quickly find another similar worker to replace the unavailable worker so as to smooth the crowdsourcing process. However, the above exception handling process is often challenging as candidate workers are often not willing to release their sensitive information to the platform due to privacy concerns. In view of this challenge, in this paper, a novel privacy-preserving exception handling approach, named ExH Simhash , is put forward based on Simhash technique. Finally, through a set of simulated experiments, we validate the feasibility of ExH Simhash in terms of substitution equivalence and computational time.

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“…That is to say, even though such an approach reduces the number of tasks, the overall cost of the task is not guaranteed to be reduced. The authors of [21] presented a comprehensive system model of Crowdlet that defines the task, worker arrival, and worker ability models. In [22], the authors designed an approximate task allocation algorithm that is near optimal with polynomial-time complexity and used it as a building block to construct the whole randomized auction mechanism.…”

Section: Related Workmentioning

confidence: 99%

Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

Shen

Yan

Peng

et al. 2018

Wireless Communications and Mobile Computing

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Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT), targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN). This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA) is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.

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Crowdlet: Optimal worker recruitment for self-organized mobile crowdsourcing

Cited by 74 publications

References 22 publications

Optimal Task Partition with Delay Requirement in Mobile Crowdsourcing

Optimal Task Partition with Delay Requirement in Mobile Crowdsourcing

A privacy-preserving exception handling approach for dynamic mobile crowdsourcing applications

Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

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