Incentive Mechanism For Computation Offloading In Local Edge Community

With the rapid development of the mobile internet,mobile commerce has become more and more important in our lives.Aiming at mobile commerce secur ity problem,the emerging blockchain technology can be used as an efficient solution.However,due to the limitation of the computing power of the device,the blockchain cannot run efficiently on mobile devices.Existing works use mobile edge computing technology to solve this problem.But,it is impossible to effectively share computing resources due to the selfishness of the computing devices.Therefore,it is required to design a motivation strategy for computing devices to share their computing resources while maximizing the social utilities of the system.The motivation offloading strategy thus has become the key to solve the above problems.This thesis proposes a computing model that combines the incentive mechanism with the offloading strategies for computing tasks in the local cloud community network with mobile edge computing.At the same time,an incentive algorithm based on double auction is proposed to increase the revenue of computing device by stimulating the sharing of their idle computing resources.Computing devices can be effectively motivated by this algorithm to share their resources.In order to avoid the case when computing tasks are too large to find suitable computing devices to offload tasks.In this thesis,a computing task segmentation mechanism is invented.The above problem is formulated into a mixed integer programming problem.The resource allocation incentive mechan ism allocates independent tasks to surrounding computing devices with idle resources by considering the heterogeneous preferences of task-intensive mobile devices.This thesis theoretically proves the individual rationality,budget balance,authenticity and efficiency properties of the proposed algorithm.The performance of the proposed algorithm is verified through simulation experiments.Since the long-term utility of the system cannot be well guaranteed,this thesis proposes another long-term pricing incentive mechanism.According to the arrival rule of user devices in the system,the algorithm divides the entire time frame,and in each time slot of the time frame,a corresponding computing task offloading strategy will be executed.The long-term nature of the algorithm allows that if users have computing tasks and sufficient budgets,they can always participate in the offloading strategies for computing tasks.This algorithm can improve the completion time for all user tasks in the system,and it can optimize total system utility.The performance of the algorithm is verified through simulation experiments.In order to verify the performance of the proposed algorithm,this thesis builds a mobile blockchain-task offloading prototype experimental platform using laboratory devices,based on the principles of mobile edge computing and mobile blockchain.By deploying the algorithms on the platform,the performance of the algorithms are verified justified.Experimental results demonstrate that the proposed algorithms can effectively improve the total utility of the system.