دانلود رایگان مقاله انگلیسی یک مکانیسم انگیزشی واقعی برای سنجش جمعیت موبایل با وظایف موقعیت مکانی - الزویر 2018

abstract

Mobile crowd sensing has emerged as an appealing paradigm to provide sensing data for its efficient economy. A large number of incentive mechanisms has been proposed for stimulating smartphone users to participate in mobile crowd sensing applications. Different from existing work, in addition to sensing tasks with diverse weights, we uniquely take into consideration the crucial dimension of location information when performing sensing tasks allocation. However, the location-sensitive weighted tasks are more vulnerable to the real life where each sensing task has the evident distinction. Meanwhile, the location sensitiveness leads to the increase of theoretical and computational complexity. In this paper, we investigate a truthful incentive mechanism which consists of two main components, winning bids determination algorithm and critical payment scheme. Since optimally determining the winning bids is NP hard, a near-optimal algorithm with polynomial-time computation complexity is proposed, which further approximates the optimal solution within a factor of 1 + ln(n), where n is the maximum number of sensing tasks that a smartphone can accommodate. To guarantee the truthfulness, a critical payment scheme is proposed to induce smartphones to disclose their real costs. Through both rigid theoretical analysis and extensive simulations, we demonstrate that the proposed mechanism achieves truthfulness, individual rationality and high computation efficiency.

7. Conclusion

In this paper, we have investigated a truthful incentive mechanism for stimulating smartphone users to participate in mobile crowd sensing applications with smartphones. In addition to sensing tasks with diverse weights, the crucial dimension of location information is uniquely taken into consideration in our design of incentive mechanism, which is more consistent with the real condition. Based on the reverse auction framework, we have designed a truthful incentive mechanism which consists of winning bids determination algorithm and a critical payment scheme. With polynomial-time computation complexity, the near-optimal algorithm for determining the cost-efficient winning bids can approximate the optimal solution within a factor of 1 + ln(n), where n is the maximum number of sensing tasks that a smartphone can accommodate. Meanwhile, despite the suboptimal approximation algorithm, the proposed critical payment scheme can guarantee truthfulness. As an additional part, after the rigorous analysis, we prove that the number of winning bids from the approximation solution has an upper bound α compared to that of the optimal solution when all smartphone users have the same claimed bid price. After rigorous theoretical proof and extensive simulations, the results demonstrate that our mechanism achieves truthfulness, individual rationality and high computational efficiency.