关键词： Low-energy base station group   Game algorithm   Computation offloading   Energy control   Mobile edge computing  

摘要： The research on mobile edge computing generally ignores task energy control and optimization between base station groups. To solve this problem, this paper proposes a low-latency and efficient task offloading algorithm for low-energy base station groups. Firstly, the low-load base station group model and energy consumption model for edge devices are proposed, which focuses on how base stations handle tasks cooperatively in the group. Secondly, based on the division of base station group, a total energy model for computation and communication loss is established respectively. Then, we analyze energy consumption constraints and optimization goal, clarify the goal and evaluation indicators of offloading tasks. Based on the game theory, a game model of the base station unloading task is established to meet the delay, load and interference constraints, and the updating process of the unloading algorithm is completed by iteration. Finally, experiments verify the convergence ability of the proposed algorithm compared with joint optimization and distributed offloading strategies. The effectiveness of the proposed algorithm is verified from the perspectives of long-term energy constraints, unit data transmission energy consumption, computing data size, number of edge devices and average system delay. Experiments show that the control algorithm proposed in this paper not only effectively reduces the energy consumption of base station group, but also has good execution performance and convergence.

关键词： Non-orthogonal multiple access   Mobile edge computing   Outage probability  

摘要： To satisfy the fast growth of Internet of Things (IoT) or development of applications in the fifth generation (5G) wireless networks, the expected systems need two main functions such as massive connectivity of IoT devices and the low latency. Fortunately, non-orthogonal multiple access (NOMA) has been recommended as a promising approach for 5G networks to satisfy concerned requirements and to significantly improve the network capacity. Together with advances of NOMA scheme, mobile edge computing (MEC) is recognized as one of the key emerging approaches to improve the quality of service and reduce the latency for 5G networks. In order to capture the potential gains of NOMA-aided MEC systems, this paper proposes design of multiple antennas and full-duplex for an edge computing aware NOMA architecture. As expected, such NOMA-aided MEC systems can enjoy the benefits of uplink NOMA in reducing MEC users' uplink outage probability. To this end, we derive expression of outage probability for signals corresponding two-user model at uplink. Especially, degraded performance might happens in practice under impact of hardware impairment.

关键词： Reliability   Interference   Fading channels   Reliability theory   Signal to noise ratio   Computational modeling   Nakagami distribution   Mobile edge computing   computation offloading   Nakagami fading   wireless interference   admission control  

摘要： The coupled stochastic channel interferences can lead to intermittent connectivity and invalid fragment transmissions, which pose a significant challenge to guarantee the reliability of computation offloading. A wide variety of conventional approaches to making offloading decisions are based on the fundamental condition that channels are sufficiently reliable for completing each transmission session. However, the reliability that a user can successfully offload a computation task before a restricted deadline remains unexplored under the interference channels. In this letter, we focus on the Nakagami-m fading channel and propose an analytical framework to characterize the reliability of computation offloading with the restrictions of application deadline and offloading data size in the presence of coupled stochastic interferences. A lower-bound offloading reliability capturing coupled randomness is theoretically derived. Based on the analytical framework, we further propose an admission control method for users to make computation offloading decisions. Simulation results verify our theoretical framework and show the superior performance of the proposed method over other benchmark schemes in terms of guaranteeing reliability.

关键词： Wireless communication   Task analysis   Downlink   Resource management   Edge computing   Uplink   Array signal processing   Mobile edge computing   wireless energy transfer   intelligent reflecting surface   resource management  

摘要： The combination of wireless energy transfer (WET) and mobile edge computing (MEC) has been proposed to satisfy the energy supply and computation requirements of resource-constrained Internet of Things (IoT) devices. However, the energy transfer efficiency and task offloading rate cannot be guaranteed when wireless links between the hybrid access point (HAP) and IoT devices are hostile. To address this problem, this paper aims at utilizing the intelligent reflecting surfaces (IRS) technique to improve the efficiency of WET and task offloading. In particular, we investigate the total computation bits maximization problem for IRS-enhanced wireless powered MEC networks, by jointly optimizing the downlink/uplink phase beamforming of IRS, transmission power and time slot assignment used for WET and task offloading, and local computing frequencies of IoT devices. Furthermore, an iterative algorithm is presented to solve the non-convex non-linear optimization problem, while the optimal transmission power and time allocation, uplink phase beamforming matrixes and local computing frequencies are derived in closed-form expressions. Finally, extensive simulation results validate that our proposed IRS-enhanced wireless powered MEC strategy can achieve higher total computation rate as compared to existing baseline schemes.

关键词： QoS   Mobile edge computing   Recommendation   Time-aware   Location  

摘要： With the rapid development of Internet of Things, mobile edge computing which provides physical resources closer to end users has gained considerable popularity in academic and industrial field. As the number of edge server increases, accessing effective edge services fast is an urgent problem to be solved. In this paper, we mainly focus on the cold-start problem for service recommendation based on location of users and services. Address this conundrum, we propose a service recommendation method based on collaborative filtering (CF) and location, by comprehensively considering the characteristic of services at the edge, mobility and demands of users at different time periods. In detail, we synthesize the service characteristics of each dimension in different time slices through multidimensional weighting method at first. Then We further introduce the idea of Inverse CF Rec to the traditional CF and predict the lost quality of service (QoS) to solve the problem of sparse data. Finally, a recommendation algorithm based on predicted QoS and user geographic location is proposed to recommend appropriate services to users. The experimental results show that our multidimensional inverse similarity recommendation algorithm based on time-aware collaborative filtering (MDITCF) outperforms Inverse CF Rec in terms of the accuracy of recommendation.

关键词： Base stations   Uplink   Downlink   Edge computing   Servers   Computational modeling   Interference   Mobile edge computing   decoupled access   offloading   latency   HetNets   backhaul  

摘要： Achieving an end-to-end low-latency for computations offloading, in Mobile Edge Computing (MEC) systems, is still a critical design problem. This is because the offloading of computational tasks via the MEC servers entails the use of uplink (UL) and downlink (DL) radio links that are usually assumed to be coupled to a single base station (BS). However, for heterogeneous networks, a new architectural paradigm whereby UL and DL are not associated with the same BS is proposed and seen to provide gains in network throughput due to the improved UL performance. Motivated by such gains, and by using typical results from stochastic geometry, we formulate the offloading latency for the MEC-based scheme with decoupled UL/DL association, or decoupled access, and compare its performance to the conventional coupled access scheme. Despite the backhaul delay necessary for the communication between the two serving BSs in UL and DL, the offloading scheme with decoupled access is still capable of providing a fairly lower offloading latency compared to the conventional offloading scheme with coupled access.

关键词： Mobile edge computing  

摘要： Rural cooperative financial organization is a new type of cooperative financial organization in recent years. It is a community financial institution created by farmers and small rural enterprises to voluntarily invest in shares in order to meet the growing demand for rural financing. However, this financial organization has many flaws in the design of the system;it has not promoted the better development of rural mutual fund assistance. In addition, mobile edge computing (MEC) can be used as an effective supplement to mobile cloud computing and has been proposed. However, most of the current literature studies on cloud computing provide computing offload just to propose a network architecture, without modeling and solving to achieve. In this context, this paper focuses on the practical application of MEC in the risk control of new rural cooperative financial organizations. This paper proposes a collaborative LECC mechanism based on machine learning under the MEC architecture. The experimental simulation shows that the HR under the LECC mechanism is about 17%-23%, 46%-69%, and 93%-177% higher than that of LENC, LRU, and RR, respectively. It is unrealistic to want to rely on meager loan interest for long-term development. The most practical way is to increase the income level of the organization itself.

关键词： Mobile edge computing  

摘要： —This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, multiple base stations, and a malicious eavesdropper. Specifically, the users adopt the partial offloading strategy by partitioning the computation task into several parts. One is executed locally and the others are securely offloaded to multiple MEC servers integrated into the base stations by leveraging the physical layer security to combat the eavesdropping. We jointly optimize power allocation, task partition, subcarrier allocation, and computation resource to maximize the secrecy offloading rate of the users, subject to communication and computation resource constraints. Numerical results demonstrate that our proposed scheme can respectively improve the secrecy offloading rate 1.11%–1.39% and 15.05%–17.35% (versus the increase of tasks’ latency requirements), and 1.30%–1.75% and 6.08%–9.22% (versus the increase of the maximum transmit power) compared with the two benchmarks. Moreover, it further emphasizes the necessity of conducting computation offloading over multiple MEC servers. Copyright © 2021, The Authors. All rights reserved.

关键词： Mobile edge computing   Trust management   Service level agreement   Processing performance Fuzzy logic  

摘要： Mobile edge computing (MEC) is introduced as part of edge computing paradigm, that exploit cloud computing resources, at a nearer premises to service users. Cloud service users often search for cloud service providers to meet their computational demands. Due to the lack of previous experience between cloud service providers and users, users hold several doubts related to their data security and privacy, job completion and processing performance efficiency of service providers. This paper presents an integrated three-tier trust management framework that evaluates cloud service providers in three main domains: Tier I, which evaluates service provider compliance to the agreed upon service level agreement;Tier II, which computes the processing performance of a service provider based on its number of successful processes;and Tier III, which measures the violations committed by a service provider, per computational interval, during its processing in the MEC network. The three-tier evaluation is performed during Phase I computation. In Phase II, a service provider total trust value and status are gained through the integration of the three tiers using the developed overall trust fuzzy inference system (FIS). The simulation results of Phase I show the service provider trust value in terms of service level agreement compliance, processing performance and measurement of violations independently. This disseminates service provider's points of failure, which enables a service provider to enhance its future performance for the evaluated domains. The Phase II results show the overall trust value and status per service provider after integrating the three tiers using overall trust FIS. The proposed model is distinguished among other models by evaluating different parameters for a service provider.

关键词： Mobile edge computing  

摘要： Mobile edge computing (MEC) is proposed to boost high-efficient and time-sensitive 5G applications. However, the "microburst" may occur even in lightly-loaded scenarios, which leads to the indeterministic service latency (i.e., unpredictable delay or delay variation), hence hindering the deployment of MEC. Deterministic IP networking (DIP) has been proposed that can provide bounds on latency, and high reliability in the large-scale networks. Nevertheless, the direct migration of DIP into the MEC network is non-trivial owing to its original design for the Ethernet with homogeneous devices. Meanwhile, DIP also faces the challenges on the network throughput and scheduling flexibility. In this paper, we delve into the adoption of DIP for the MEC networks and some of the relevant aspects. A deterministic MEC (D-MEC) network is proposed to deliver the deterministic service (i.e., providing the MEC service with bounded service latency). In the D-MEC network, two mechanisms, including the cycle mapping and cycle shifting, are designed to enable: (i) seamless and deterministic transmission with heterogeneous underlaid resources;and (ii) traffic shaping on the edges to improve the resource utilization. We also formulate a joint configuration to maximize the network throughput with deterministic QoS guarantees. Extensive simulations verify that the proposed D-MEC network can achieve a deterministic MEC service, even in the highly-loaded scenarios. Copyright © 2021, The Authors. All rights reserved.