Auction-based profit maximization offloading in mobile edge computing

Offloading Mobile Devices(MDs)computation tasks to Edge Nodes(ENs)is a promising solution to overcome computation and energy resources limitations of MDs.However,there exists an unreasonable profit allocation problem between MDs and ENs caused by the excessive concern on MD profit.In this paper,we propose an auction-based computation offloading algorithm,inspiring ENs to provide high-quality service by maximizing the profit of ENs.Firstly,a novel cooperation auction framework is designed to avoid overall profit damage of ENs,which is derived from the high computation delay at the overloaded ENs.Thereafter,the bidding willingness of each MD in every round of auction is determined to ensure MD rationality.Furthermore,we put forward a payment rule for the pre-selected winner to effectively guarantee auction truthfulness.Finally,the auction-based profit maximization offloading algorithm is proposed,and the MD is allowed to occupy the computation and spectrum resources of the EN for offloading if it wins the auction.Numerical results verify the performance of the proposed algorithm.Compared with the VA algorithm,the ENs profit is increased by 23.8%,and the task discard ratio is decreased by 7.5%.

User Preference Aware Hierarchical Edge-User Cooperative Caching Strategy

The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been considered as a feasible scheme.However,how to efficiently utilize the limited caching resources to cache diverse contents has been confirmed as a tough problem in the past decade.In this paper,considering the time-varying user requests and the heterogeneous content sizes,a user preference aware hierarchical cooperative caching strategy in edge-user caching architecture is proposed.We divide the caching strategy into three phases,that is,the content placement,the content delivery and the content update.In the content placement phase,a cooperative content placement algorithm for local content popularity is designed to cache contents proactively.In the content delivery phase,a cooperative delivery algorithm is proposed to deliver the cached contents.In the content update phase,a content update algorithm is proposed according to the popularity of the contents.Finally,the proposed caching strategy is validated using the MovieLens dataset,and the results reveal that the proposed strategy improves the delay performance by at least 35.3%compared with the other three benchmark strategies.

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in order to ensure the security of physiological privacy data and the identity privacy of patients,this paper presents a privacy protection strategy for Mobile Edge Computing(MEC)enhanced WBANs,which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency,high reliability within a high-demand data security scenario.On this basis,the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data.Furthermore,a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability,data integrity and reduced delay.The security performance analysis and simulation results show that our proposed strategy not only reduces the delay,but also secures the privacy and transmission of sensitive WBANs data.

Similar physical entity matching strategy for mobile edge search

In recent years,a large number of intelligent sensing devices have been deployed in the physical world,which brings great difficulties to the existing entity search.With the increase of the number of intelligent sensing devices,the accuracy of the search system in querying the entities to match the user’s request is reduced,and the delay of entity search is increased.We use the mobile edge technology to alleviate this problem by processing user requests on the edge side and propose a similar physical entity matching strategy for the mobile edge search.First,the raw data collected by the sensor is lightly weighted and expressed to reduce the storage overhead of the observed data.Furthermore,a physical entity matching degree estimation method is proposed,in which the similarity between the sensor and the given sensor in the network is estimated,and the matching search of the user request is performed according to the similarity.Simulation results show that the proposed method can effectively reduce the data storage overhead and improve the precision of the sensor search system.