关键词： Mobile edge computing   Cloudlet   MHP2P   Load balance  

摘要： To overcome long propagation delays for data exchange between the remote cloud data center and end devices in Mobile Cloud Computing (MCC), Mobile Edge Computing (MEC) is emerging to push mobile computing, network control and storage to the network edges. A cloudlet in MEC is a mobility enhanced small-scale cloud, which contains several MEC servers located in close proximity to mobile devices. The main purpose of a cloudlet is to stably provide services to mobile devices with low latency. When a cloudlet offers hundreds kinds of services to millions of mobile devices, it is critical to balance the loads so as to improve performance. In this paper, we propose a three-layer mobile hybrid hierarchical P2P (MHP2P) model as a cloudlet. MHP2P performs satisfactory service lookup efficiency and system scalability as well as high stability. More importantly, a load balance scheme is provided so that the loads of MHP2P can be well balanced with the increasing of MEC servers and query load. A large number of simulation experiments indicate that the proposed scheme is efficient for enhancing the load balancing performance in MHP2P based MEC systems. (C) 2021 Elsevier Inc. All rights reserved.

关键词： mobile edge computing   UAV communication   resource allocation   3D deployment   air-ground cooperation  

摘要： Equipping an unmanned aerial vehicle (UAV) with a mobile edge computing (MEC) server is an interesting technique for assisting terminal devices (TDs) to complete their delay sensitive computing tasks. In this paper, we investigate a UAV-assisted MEC network with air-ground cooperation, where both UAV and ground access point (GAP) have a direct link with TDs and undertake computing tasks cooperatively. We set out to minimize the maximum delay among TDs by optimizing the resource allocation of the system and by three-dimensional (3D) deployment of UAVs. Specifically, we propose an iterative algorithm by jointly optimizing UAV-TD association, UAV horizontal location, UAV vertical location, bandwidth allocation, and task split ratio. However, the overall optimization problem will be a mixed-integer nonlinear programming (MINLP) problem, which is hard to deal with. Thus, we adopt successive convex approximation (SCA) and block coordinate descent (BCD) methods to obtain a solution. The simulation results have shown that our proposed algorithm is efficient and has a great performance compared to other benchmark schemes.

关键词： task offloading   machine learning   location prediction   mobile edge computing  

摘要： In mobile edge computing (MEC), mobile devices limited to computation and memory resources offload compute-intensive tasks to nearby edge servers. User movement causes frequent handovers in 5G urban networks. The resultant delays in task execution due to unknown user position and base station lead to increased energy consumption and resource wastage. The current MEC offloading solutions separate computation offloading from user mobility. For task offloading, techniques that predict the user's future location do not consider user direction. We propose a framework termed COME-UP Computation Offloading in mobile edge computing with Long-short term memory (LSTM) based user direction prediction. The nature of the mobility data is nonlinear and leads to a time series prediction problem. The LSTM considers the previous mobility features, such as location, velocity, and direction, as input to a feed-forward mechanism to train the learning model and predict the next location. The proposed architecture also uses a fitness function to calculate priority weights for selecting an optimum edge server for task offloading based on latency, energy, and server load. The simulation results show that the latency and energy consumption of COME-UP are lower than the baseline techniques, while the edge server utilization is enhanced.

关键词： device-to-device communication   content delivery networks   mobile edge computing   incentive based resource sharing   peer to peer resource sharing   wireless communication   mobile devices  

摘要： Recent developments in telecommunication world have allowed customers to share the storage and processing capabilities of their devices by providing services through fast and reliable connections. This evolution, however, requires building an incentive system to encourage information exchange in future telecommunication networks. In this study, we propose a mechanism to share bandwidth and processing resources among subscribers using smart contracts and a blockchain-based incentive mechanism, which is used to encourage subscribers to share their resources. We demonstrate the applicability of the proposed method through two use cases: (i) exchanging multimedia data and (ii) CPU sharing. We propose a universal user-to-user and user-to-operator payment system, named TelCash, which provides a solution for current roaming problems and establishes trust in X2X communications. TelCash has a great potential in solving the charges of roaming and reputation management (reliance) problems in telecommunications sector. We also show, by using a simulation study, that encouraging D2D communication leads to a significant increase in content quality, and there is a threshold after which downloading from base station is dramatically cut down and can be kept as low as 10%.

关键词： mobile edge computing   smart grid   UAV   power line inspection   energy consumption minimization  

摘要： Unmanned aerial vehicles (UAVs) have the advantages of flexibility, low cost, and good communication channel gain. In recent years, the inspection of power grid systems supported by UAVs has been widely used. However, due to the constraint of wireless channels and UAVs, it is impossible to transmit video content to the surveillance center. To solve this problem, in this study, a new mobile edge computing (MEC) technology-enabled power line inspection scheme for smart grid networks was designed. Within this scheme, a double-layer MEC architecture is proposed. In the upper-level layer, several UAVs installed with MEC equipment can locally process inspection videos with higher propriety. At the same time, the remaining tasks with lower priority are performed by the terrestrial base stations. In addition, a cost minimization problem is proposed and solved by the alternating optimization algorithm. The simulation results show that the proposed algorithm can significantly reduce the energy consumption of the system.

关键词： Low delay   Mobile edge computing   Data processing   IC design   Global routing   Wirelength optimization   Internet of Things  

摘要： With the development of Internet of Things (IoT), real-time decision making has gradually become one of the important characteristics in mobile edge computing (MEC) environment of IoT. Therefore, in the Integrated Circuit (IC) design of MEC environment for IoT, low delay is one of the important optimization objectives. In the many routing competitions, wirelength, overflow, and runtime are the main evaluation standards, so how to reduce wirelength, overflow, and runtime has become a major challenge. However, the existing work lacks the excellent optimization ability in wirelength, overflow, and runtime, or only considers some of the optimization objectives. Therefore, we consider the wirelength, overflow, and runtime as the optimization objectives and propose a high-quality global routing algorithm of IC design in MEC environment, including the following effective strategies: (1) A hybrid topology optimization strategy combining Prim algorithm and divide-and-conquer method, (2) a heuristic search algorithm considering the congestion and the wirelength of nets. Due to the use of the Fast Lookup Table (FLUTE) algorithm to construct the topology of each net, there are too many Steiner points. For this reason, we used Prim algorithm and divide-and-conquer method to construct the topology, and thus it can avoid the problem of redundant Steiner points. In addition, we propose a congestion area identification method based on interval division to determine the area and order of nets to rip-up and reroute (R&R). Furthermore, a heuristic search algorithm that considers both the congestion and the wirelength of nets is used to optimize the total wirelength in the R&R stage. In terms of the total overflow, the total wirelength and the runtime, the experimental results show that the proposed strategies have achieved effective optimization, which can better satisfy the demand of low delay of IC design for data processing in MEC environments of IoT.

关键词： slicing resource allocation algorithm   radio access network model   mobile edge computing   network system   service requirements   telecommunication network reliability   6G mobile communication   resource allocation   edge computing   optimisation   energy consumption   telecommunication scheduling   enhanced mobile broadband slicing users   stability-oriented RAN slicing   short time interval resource allocation algorithms   computing power   computation offloading   radio access networks   joint communication   slicing resources   ultra-reliable low latency communication slicing users   mobile computing   5G mobile communication   stable allocation   base stations   URLLC slices   telecommunication computing  

摘要： Network slicing and mobile edge computing are key technologies in 5G/6G networks. Stable allocation of slicing resources is a challenge while communication and computation offloading coexist. To meet the service requirements of communication and computation offloading, a radio access network model which consists of enhanced mobile broadband (eMBB) slicing users, ultra-reliable low latency communication (URLLC) slicing users, base stations integrated with MEC servers, and fog nodes with computing power are proposed. By employing the Lyapunov optimisation technique, a slicing resource allocation algorithm is proposed to maintain the queue stability and minimise the energy consumption of the system. For eMBB and URLLC slices, long time interval and short time interval resource allocation algorithms are proposed respectively. Simulation results show that the proposed algorithm can guarantee the long-term stability of the network system while ensuring the service requirements.

关键词： Servers   Task analysis   Computational modeling   Digital twin   Resource management   Quality of service   Multi-access edge computing   Mobile edge computing   digital twin   IoT  

摘要： In this letter, we study a mobile edge computing (MEC) architecture with the assistance of digital twin (DT) applied for industrial automation where multiple Internet-of-Things (IoT) devices intelligently offload computing tasks to multiple MEC servers to reduce end-to-end latency. To do so, first we propose and formulate a practical end-to-end latency minimization problem in the DT-assisted MEC model subject to the constraints of quality-of-services and computation resource at the IoT devices and MEC servers in industrial IoT networks. Then, we solve the proposed latency minimization problem by iteratively optimizing the transmit power of IoT devices, user association, intelligent task offloading, and estimated CPU processing rate of the devices. Finally, simulation results are conducted to prove the effectiveness of the proposed method in terms of the latency performance compared with some conventional methods.

关键词： Book reviews   Mobile computing   Edge computing   Cloud computing   Servers   Multi-access edge computing   Computer architecture   6G mobile communication  

摘要： This book offers comprehensive, self-contained knowledge on mobile edge computing (MEC), not only covering the basics, essential topics, and future directions, but also detailing the design and implementation of communications, computing, and caching in MEC. The first chapter provides an overview of MEC by outlining its technological characteristics and distinctions from cloud computing. Mobile cloud computing (MCC) integrates cloud computing with mobile devices to enhance mobile device capabilities such as computing and storage. Compared to mobile cloud computing (MCC), MEC provides an IT service environment and cloud computing capabilities at the edge of the network, within the radio access network, and close to mobile subscribers. Thus, the user experience can be further improved by the execution of computation- and storage-sensitive applications through computing in the edge cloud and the delivery of related computing services. This book provides basic concepts of MEC, explores the promising application scenarios of MEC integrated with emerging technologies, and gives insights into possible future directions of MEC. Due to the broad coverage on both the principle and applications of MEC, the book allows for easy cross-referencing and is suitable for researchers seeking a comprehensive but quick view of the current and future research focus about MEC and the related areas.

关键词： Servers   Power demand   Cloud computing   Mobile handsets   Task analysis   Computer architecture   Load management   5G networks   mobile edge computing   hotspot mitigation   energy saving  

摘要： Due to the long latency of accessing services from cloud datacenters, mobile edge computing (MEC) has been proposed to provide the capability of cloud computing in close proximity to mobile users. Mobile devices can offload computation-intensive applications to MEC servers to achieve better performance and reduce power consumption. Owing to user mobility, workloads of MEC servers would vary severely to cause imbalanced loads and incur hotspot servers. Previous studies of power saving and hotspot management apply mechanisms for cloud datacenters to MEC servers, but these studies may not be suitable for MEC servers due to the limited computation and communication capacity. We are motivated to propose a scheme, complementary offloading for hotspot mitigation (COHM), for MEC. COHM consists of mechanisms for MEC servers with different states, namely busy, idle, and available. These mechanisms jointly consider the computation tasks for MEC servers with different states to mitigate hotspots. The simulation results show that COHM can decrease the number of hotspot servers without degrading the quality of service for applications.