The proliferation of Internet Things (IoT) and the success rich cloud services have pushed horizon a new computing paradigm, edge computing, which calls for processing data at network. Edge has potential to address concerns response time requirement, battery life constraint, bandwidth cost saving, as well safety privacy. In this paper, we introduce definition followed by several case studies, ranging from offloading smart home city, collaborative materialize concept computing. Finally,...

Driven by the visions of Internet Things and 5G communications, edge computing systems integrate computing, storage, network resources at to provide infrastructure, enabling developers quickly develop deploy applications. At present, have received widespread attention in both industry academia. To explore new research opportunities assist users selecting suitable for specific applications, this survey paper provides a comprehensive overview existing introduces representative projects. A...

Vehicular ad hoc networks (VANETs) have been widely used in intelligent transportation systems (ITSs) for purposes such as the control of unmanned aerial vehicles (UAVs) and trajectory prediction. However, an efficient reliable data routing decision scheme is critical VANETs due to feature self-organizing wireless multi-hop communication. Compared with networks, which are unstable limited bandwidth, wired normally provide longer transmission distances, higher network speeds greater...

AI-empowered 5G/6G networks play a substantial role in taking full advantage of the Internet Things (IoT) to perform complex computing by offloading tasks edge services deployed intelligent transport systems. However, behavior has certain regularity, and real-time location users can easily be inferred attackers who have historical user data during transmission process. To address this problem, privacy-oriented task method that resist attacks from privacy with prior knowledge is proposed....

With the development of Industrial Internet Things system, huge amount devices, services, and continuous data, making it difficult to discover a trusted service in complex scenarios. To better leverage knowledge historical behavior, recommendation systems are applied. However, model accuracy closely depends on training data size; there is great risk leaking by collecting from multiple departments. solve these problems, we propose graph-convolutional-neural-network-based federated approach,...

With the development of autonomous driving and Internet Vehicles, vehicle data communication security become more important. Blockchain which has transparency, decentralization immutability nature is treated as a promising approach to support intelligent systems. However, due high update overhead, vulnerable raw storage policy inflexible consensus algorithm, traditional blockchain technologies are not suitable in modern vehicular Hence, we propose, system that supports incremental updating....

Current cloud data centers are fully virtualized for service consolidation and power/energy reduction. Although virtualization could reduce the real-time power consumption overall energy consumption, characteristics of hypervisors hosting different workloads have not been well profiled or understood thus far. In this study, we investigate four mainstream a container engine, namely VMware ESXi, Microsoft Hyper-V, KVM, XenServer, Docker, on six platforms (three 2U rack servers, one emerging...

Power consumption is a primary concern in modern servers and data centers. Due to varying workload types intensities, different may have energy efficiency (EE) proportionality (EP) even while having the same hardware configuration (i.e., central processing unit (CPU) generation memory installation). For example, CPU frequency scaling modules voltage can significantly affect server’s efficiency. In conventional virtualized centers, virtual machine (VM) scheduler packs VMs until they saturate,...

In modern society, recommendation systems (RSs) already become an indispensable component, especially in smart cities. Their performance is greatly affected by the available analyzing data, but centralized massive data can cause privacy issues. Hence, federated learning applied to achieve a higher accuracy without sharing raw data. To improve and reliability of traditional RSs, we propose HFSA, semi-asynchronous hierarchical RS. First, from architecture perspective, edge server layer...

The explosive growth of the Internet Things and modern networking technologies lay foundation for development intelligent transportation systems smart cities. To analyzing massive data under required time issues, edge computing paradigm is applied, which pre-processing large amounts at network to save bandwidth improve response time. However, reliability security are still facing many challenges in environment. In this article, we propose a multi-authority hybrid attribute-based signature...

With the development of virtualization technologies, containers are widely used to provide a light-weight isolated runtime environment. Compared with virtual machines, can achieve high-resource utilization and more convenient way sharing, but there significant security challenges due potential resource contention among services. When regular services that share storage system key over-used, lot resources may be preempted, which breakdowns whole delays other This paper addressed performance...

With the rapid development of Internet Things and ever-increasing demands advanced services applications, edge computing is proposed to move storage resources near data source, which improves response time saves bandwidth. However, due limited available massive privacy-sensitive user in nodes, there are huge challenges security privacy protection environment. Hence, we propose an efficient time-domain multi-authority outsourcing attribute-based encryption (ABE) scheme (TMO) with a dynamic...

With the rapid development of Internet Things (IoT) in recent years, popularization different segments IoT has emerged. The technology is slowly evolving toward intelligence, convenience, low power consumption, large connectivity, and wide coverage. This evolution significantly attributed to emergence Narrowband Thing (NB-IoT). NB-IoT an emerging with wide-coverage, large-connection, low-power low-costs. intelligent system based on NB-IoT, important branch field, various functions widely...

Traffic context plays an important role in supporting automated driving and intelligent transportation systems. Smart vehicles explore surrounding environments by analyzing sensor data periodically communicating with neighbors road infrastructures. The can be well learned this way to support driving, but the vehicle trajectory also easily exposed under eavesdropping attacks. pseudonym is proposed hide real identity of vehicles. However, effectiveness anonymity, safety convenience...

Identifying fishing vessel types with artificial intelligence has become a key technology in marine resource management. However, classical feature modeling lacks the ability to express time series features, and extraction is insufficient. Hence, this work focuses on identification of trawlers, gillnetters, purse seiners based semantic vectors. First, we extract trajectories from massive complex historical Vessel Monitoring System data that contain large amount dirty then features...

There has been a 10,000-fold increase in performance of supercomputers since 1992 but only 300-fold improvement per watt. Dynamic adaptation hardware techniques such as fine-grain clock gating, power gating and dynamic voltage/frequency scaling, are used for many years to improve the computer's energy efficiency. However, recent demands exascale computation, well increasing carbon footprint, require new breakthrough make ICT systems more efficient. Energy efficient software not studied last...

As the rapid growth of connected and autonomous vehicles (CAVs) 5G intensifies, more third-party applications are increasingly being deployed on CAVs. They not only improve user experience but also provide helpful services, for example, enhancing public safety by recognizing criminals in real-time videos. Current CAVs prefer to process collected data vehicle avoid long transmission latency extra network cost. However, due limitations on-board computing unit (VCU) increasing use...

Online Analytical Processing, or OLAP, is an approach to answering multidimensional analytical (MDA) queries in interactive way. However, the traditional OLAP approaches can only deal with structured data, but not unstructured textual data like tweets. To address this problem, we propose a Latent Dirichlet Allocation (LDA)-based model, called Multilayered Semantic LDA (MS-LDA), which detects hidden layered interests from Twitter based on LDA. The dimension of be further used apply techniques...

Banks play an important role in the financial market, and their profit mainly comes from loan service. Traditional risk management approaches, as key part services, still have several issues including low data credibility, unreliable checking alert delay. We propose a novel dynamic credit system which leverages edge-based blockchain technology to improve performance provide fair environment. Besides, we discuss potential challenges that may face, such standards, security on edge scalability.