Multi Skill Registration Status
Alix Stocking
Certified Multi-Skilled Healthcare Technician Credential the Nations 1st and only industry-recognized in demand multi-skilled stacked credential designed to impact higher Education by helping students efficiently and cost-effectively gain transparent in-demand skills that lead to employment and to provide numerous benefits to healthcare providers, organizations, and patients for Health care organizations that increasingly face the pressures of meeting the needs of patients while responding to the financial pressures of cost containment and quality optimization.
With the boom in 5G technology, mobile spatial crowdsourcing has shown great dynamism in industrial mobile communications and edge computing node management. But the traditional crowdsourcing system is not advanced enough to adapt to the new environment. Typically, traditional crowdsourcing workflow is hosted by a centralized crowdsourcing platform. However, the centralized crowdsourcing platform faces the following problems: (1) single point of failure, (2) user privacy leakage, (3) subjective arbitration, (4) additional service fee, and (5) non-transparent task assignment process. To improve those problems, we replaced the centralized crowdsourcing platform with a decentralized blockchain infrastructure. And we analyzed the challenge problems of multi-skilled spatial crowdsourcing tasks in the blockchain crowdsourcing system. In addition, a crowdsourcing task allocation algorithm has been proposed, which implements a transparent task distribution process and can adapt to the computing-constrained environment on the blockchain. Compared with the TSWCrowd blockchain-based crowdsourcing model, our system has a higher task allocation rate under the same conditions. And the experimental result shows our work has good economic feasibility, which decentralizes the crowdsourcing process and significantly reduces the additional consumption of the crowdsourcing process.
At the same time, the development of 5g has brought new vitality to mobile crowdsourcing. Stable and high-speed wireless networks enable people to have higher accuracy and better stability in the information they can access through their mobile devices. With 5g technology, people can filter and locate crowdsourcing tasks more accurately and quickly, improving the efficiency of the crowdsourcing process.
To solve the problems in traditional crowdsourcing, many researchers have introduced blockchain technology into the crowdsourcing process and replaced the centralized crowdsourcing platform with blockchain, a decentralized infrastructure.
Single point of failure Blockchain is jointly maintained by distributed nodes around the world, and it is only necessary to ensure that more than 50% of the nodes are working properly to guarantee the availability of the system. So the blockchain-based crowdsourcing system will be completely immune to the problem of single point of failure.
Additional service fee The blockchain crowdsourcing system does not have a centralized intermediary platform to collect service fee, but still, needs to pay a certain blockchain transaction fee and gas fee. Li et al. [2] shows that the consumption generated by blockchain crowdsourcing is competitive with the service fee charged by traditional crowdsourcing platforms.
Yuan et al. [4] is the first to design and implement a private and anonymous blockchain-based crowdsourcing system, and solve the problem of data leakage and identity leakage in a decentralized crowdsourcing system. Li et al. [2] designed a decentralized crowdsourcing system with reliability, fairness, security, and low services fee. Liu et al. [5] proposed a system for blockchain-based software crowdsourcing. Yuan et al. [6] used a blockchain-based crowdsourcing system to outsource computationally intensive tasks in machine learning.
Cheng et al. [7] proposed a new complex crowdsourcing task model: Multi-Skill required spatial crowdsourcing task, which is a model closer to real life. For example, a requester wants to hold a party, and he needs to hire some workers to help him cook, play music, and take photographs. This task is a typical multi-skill crowdsourcing task, which requires the participating workers to have matching skills, such as playing instruments, cooking, and photography. Especially with the development of GPS-equipped smart devices and wireless mobile networks, spatial crowdsourcing tasks are gradually commercialized and becomes a very successful model in recent years. Spatial crowdsourcing tasks are gradually commercialized and becomes a very successful business model in recent years. Platforms such as MTurk [8], Uber [9], TaskRabbit [10] are developing greatly rapidly, and online taxi and take-out food have gradually become an important way of life for people.
However, existing blockchain-based crowdsourcing-related efforts cannot support mobile crowdsourcing tasks with multi-skill requirements. They usually involve simple online crowdsourcing tasks. Furthermore, the current blockchain-based crowdsourcing system usually typically set the design focus on implementing a general decentralized crowdsourcing framework. They usually use an intuitive method for task assignment, which is a first-come, first-serve mechanism. If a qualified worker first claims a task, they assign the task to the first-claim worker.
Thus, the goal of the research is to design a blockchain-based crowdsourcing system that (1) supports mobile crowdsourcing tasks with multiple skill requirements, (2) contains an efficient, fair, and transparent task assignment algorithm to improve the completion rate of crowdsourcing tasks while ensuring the fairness of the task assignment process, and (3) is equipped with a reliable fairness assurance mechanism to avoid false reporting and free-riding.
We can ensure that the execution process of the task assignment algorithm is credible and transparent by using smart contract technologies. However, since each node in the blockchain network stores a complete copy of the transaction, when the number of tasks and workers to be allocated in the system is too large, the gas fee generated by the task assignment algorithm executed on-chain may bring additional costs. The main challenge is how to design a fair and transparent task assignment algorithm for a crowdsourcing system to adapt to the blockchain environment with limited computing resources and to meet the demand of spatial crowdsourcing tasks with multi-skill requirements. The proposed task assignment algorithm should take into account many factors such as spatial coordinates, skill requirements, and budget constraints. To solve the above problems, we have implemented a task assignment algorithm and a decentralized crowdsourcing system. Highlights of our original contributions in this paper are as follows:
We discussed the decentralized workflow of the blockchain crowdsourcing system and analyzed the problems faced by multi-skilled spatial crowdsourcing tasks in the blockchain crowdsourcing system. And we have built a crowdsourcing system based on blockchain technology, using smart contracts to realize the interaction between requesters and workers, ensuring that the crowdsourcing system is decentralized and fair.
We deployed our task assignment algorithm with smart contracts and ensured the transparency and fairness of the algorithm execution process. Finally, we implemented a crowdsourcing-based task quality evaluation mechanism through the oracle contract to ensure the fairness of crowdsourcing participants.
The remainder of the paper is organized as follows: The second part shows the related work and the third part discussed the preliminary and problem statement. The Fourth part describes the proposed system architecture. The fifth part analyzed the feasibility of the system. The final part carries on the experiment and makes the result analysis, and the fifth part summarizes the whole article.
In this section, we will describe the proposed task allocation strategy. There are three related topics in our research: spatial crowdsourcing task matching, smart contract on Ethereum, and the blockchain-based crowdsourcing system.
According to the task allocation mechanism, we can classify spatial crowdsourcing into two categories: (1) WST(worker selects task), with the help of a recommendation algorithm [12, 13], the platform recommends tasks to workers and workers choose their interested tasks, and (2) TSW(task selects worker), the platform allocates tasks to workers with optimization goals such as maximum profit. Our work will use the TSW mechanism to maximize the task allocation rate.
Cheng et al. [7] researched the multi-skilled spatial crowdsourcing problem. They want to find an optimal worker-and-task assignment strategy. And they proposed three effective methods to allocate workers to tasks, including greedy, g-divide-and-conquer, and cost-model-based adaptive algorithms. In this paper, the problem of multi-skilled spatial crowdsourcing is defined, and they proved that the problem is NP-hard. But the algorithm complexity of this work is not suitable for the blockchain environment.
Recommendation systems are often used in crowdsourcing systems for task assignment. Yin et al. [16] proposed a holistic personalized recommendation framework , which are based on joint matrix factorization and cognitive knowledge mining. They study the hidden relationships among users, which are mined from the APIs. This helps to optimize the task recommendation model of the crowdsourcing system.
When smart contract meets blockchain, it will reveal some unique features. First, the program code of the smart contract will be recorded and verified by the blockchain nodes. Therefore, once a smart contract has been deployed, it can no longer be modified. Second, smart contracts are executed between anonymous and trustless independent nodes, without centralized control and coordination with third-party authorities, which can ensure transparent and fair execution. Third, the smart contract can have its digital encryption currency or other digital assets, and complete the transfer of assets when the predefined conditions are triggered [18].
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