Stackelberg Game Based Dynamic Admission and Scheduling in Mobile Crowdsensing

Zhifei Wang,Haohao Zhou,Yahui Wu,Hongbin Huang,Yongpeng Zhao,Su Deng

doi:10.1109/access.2019.2929774

Zhifei Wang, Haohao Zhou + Show 4 more

Open Access

https://doi.org/10.1109/access.2019.2929774

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Abstract

Mobile crowdsensing is a crowdsourcing-based paradigm, where the platform executes the sensing requests with the help of many common peoples' handheld devices (typically smartphones). In this paper, we mainly address the dynamic sensing request admission and smartphone scheduling problem to maximize the long-term profit, taking into account the competitive interaction procedure between the platform and smartphones, the queue backlog, and the location of sensing requests and smartphones. First, formulate this problem as a discrete time model and the interaction procedure between the platform and smartphones as a Stackelberg game. Then, we introduce the Lyapunov optimization technique and design a Stackelberg game based dynamic Admission and Scheduling algorithm(SAS). In SAS, all control decisions are made only based on the currently available information and none of the stakeholders, including the platform and smartphones, can improve his utility by unilaterally changing its current strategy. Next, we design an online Cooperative dynamic Admission and Scheduling algorithm(CAS) for the situation where the platform and smartphones work in a cooperative way. Theoretical analysis shows that under any control parameter V > 0, both SAS and CAS algorithm can achieve O(1/V)-optimal average profit while the sensing request backlog is bounded by O(V). The extensive numerical results based on both synthetic and real trace demonstrate the Stackelberg equilibrium of the SAS. The CAS always outperforms SAS, and in some certain situations, the profit of SAS is very close to that of the CAS.

Highlights

Mobile crowdsensing is a novel paradigm where an immense number of mobile devices collectively provide sensing and computing services related to a certain phenomenon of interest [1], [2]
ONLINE DYNAMIC ADMISSION AND SCHEDULING ALGORITHM we present the SAS and CAS algorithms in detail
We can see that all queues of the mobile crowdsensing system are stable and the system is stable

Summary

INTRODUCTION

Mobile crowdsensing is a novel paradigm where an immense number of mobile devices (typically smartphones) collectively provide sensing and computing services related to a certain phenomenon of interest [1], [2]. Compared to the researches mentioned above, the SAS mechanism designed in this paper considers the competitive interaction procedure between the platform and smartphones, and emphasizes the dynamic arrival of location aware sensing tasks. In Stage I, the platform determines the amount of admitted requests of each grid and unit price pj(t) of sensing tasks for each smartphone j to maximize the long-term average profit. 2) STAGE I: ADMISSION CONTROL AND PRICE DETERMINATION At time t, the profit of the platform equals to the proceeds by serving the sensing requests minus the payment to smartphones, which is given by, UP(t) = γ oi(t) − αj(t)pj(t) sij(t) (9). The platform calculates its optimal strategy for the amount of admitted sensing requests of each grid and unit price for each smartphone to achieve long-term profit maximization,. The last constraint indicates the optimal service rate determined by each smartphone through solving the optimization problem in Stage I and affected by unit price offered by the platform

COOPERATIVE APPROACH FORMULATION

ONLINE DYNAMIC ADMISSION AND SCHEDULING ALGORITHM

PERFORMANCE ANALYSIS

Conclusion

SIMULATION SETTINGS

CONCLUSION