Fog/edge computing has been proposed to be integrated with Internet of Things (IoT) to enable computing services devices deployed at network edge, aiming to improve the user’s experience and resilience of the services in case of failures. With the advantage of distributed architecture and close to end-users, fog/edge computing can provide faster response and greater quality of service for IoT applications. Thus, fog/edge computing-based IoT becomes future infrastructure on IoT development. To develop fog/edge computing-based IoT infrastructure, the architecture, enabling techniques, and issues related to IoT should be investigated first, and then the integration of fog/edge computing and IoT should be explored. To this end, this paper conducts a comprehensive overview of IoT with respect to system architecture, enabling technologies, security and privacy issues, and present the integration of fog/edge computing and IoT, and applications. Particularly, this paper first explores the relationship between cyber-physical systems and IoT, both of which play important roles in realizing an intelligent cyber-physical world. Then, existing architectures, enabling technologies, and security and privacy issues in IoT are presented to enhance the understanding of the state of the art IoT development. To investigate the fog/edge computing-based IoT, this paper also investigate the relationship between IoT and fog/edge computing, and discuss issues in fog/edge computing-based IoT. Finally, several applications, including the smart grid, smart transportation, and smart cities, are presented to demonstrate how fog/edge computing-based IoT to be implemented in real-world applications.

A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications

/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

The Internet of Things (IoT) now permeates our daily lives, providing important measurement and collection tools to inform our every decision. Millions of sensors and devices are continuously producing data and exchanging important messages via complex networks supporting machine-to-machine communications and monitoring and controlling critical smart-world infrastructures. As a strategy to mitigate the escalation in resource congestion, edge computing has emerged as a new paradigm to solve IoT and localized computing needs. Compared with the well-known cloud computing, edge computing will migrate data computation or storage to the network “edge,” near the end users. Thus, a number of computation nodes distributed across the network can offload the computational stress away from the centralized data center, and can significantly reduce the latency in message exchange. In addition, the distributed structure can balance network traffic and avoid the traffic peaks in IoT networks, reducing the transmission latency between edge/cloudlet servers and end users, as well as reducing response times for real-time IoT applications in comparison with traditional cloud services. Furthermore, by transferring computation and communication overhead from nodes with limited battery supply to nodes with significant power resources, the system can extend the lifetime of the individual nodes. In this paper, we conduct a comprehensive survey, analyzing how edge computing improves the performance of IoT networks. We categorize edge computing into different groups based on architecture, and study their performance by comparing network latency, bandwidth occupation, energy consumption, and overhead. In addition, we consider security issues in edge computing, evaluating the availability, integrity, and the confidentiality of security strategies of each group, and propose a framework for security evaluation of IoT networks with edge computing. Finally, we compare the performance of various IoT applications (smart city, smart grid, smart transportation, and so on) in edge computing and traditional cloud computing architectures.

A Survey on the Edge Computing for the Internet of Things

Recently, wireless technologies have been growing actively all around the world. In the context of wireless technology, fifth-generation (5G) technology has become a most challenging and interesting topic in wireless research. This article provides an overview of the Internet of Things (IoT) in 5G wireless systems. IoT in the 5G system will be a game changer in the future generation. It will open a door for new wireless architecture and smart services. Recent cellular network LTE (4G) will not be sufficient and efficient to meet the demands of multiple device connectivity and high data rate, more bandwidth, low-latency quality of service (QoS), and low interference. To address these challenges, we consider 5G as the most promising technology. We provide a detailed overview of challenges and vision of various communication industries in 5G IoT systems. The different layers in 5G IoT systems are discussed in detail. This article provides a comprehensive review on emerging and enabling technologies related to the 5G system that enables IoT. We consider the technology drivers for 5G wireless technology, such as 5G new radio (NR), multiple-input–multiple-output antenna with the beamformation technology, mm-wave commutation technology, heterogeneous networks (HetNets), the role of augmented reality (AR) in IoT, which are discussed in detail. We also provide a review on low-power wide-area networks (LPWANs), security challenges, and its control measure in the 5G IoT scenario. This article introduces the role of AR in the 5G IoT scenario. This article also discusses the research gaps and future directions. The focus is also on application areas of IoT in 5G systems. We, therefore, outline some of the important research directions in 5G IoT.

A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems

Real-time monitoring systems can introduce numerous benefits to the participants in terms of performing data mining and analysis. Nonetheless, due to the correlations in time-series data, it is hard to achieve an effective privacy and utility tradeoff through a normal differential privacy mechanism. To address this issue, we propose novel multi-dimensional decomposition based schemes, which can greatly improve the utility in differential privacy. After extending the developed scheme, we then develop a binary decomposition scheme for time-series aggregation in real-time monitoring systems. Through both extensive theoretical analysis and experiments, our data shows that our proposed schemes can effectively improve usability while achieving the same level of differential privacy than existing schemes.

On binary decomposition based privacy-preserving aggregation schemes in real-time monitoring systems

A novel multitype-users welfare equilibrium based real-time pricing in smart grid

The smart grid poses great concern about the exposure of consumers' privacy as the fine-grained measurements in the smart metering system can expose consumer's privacy through the disclosure of accurate load profiles of home energy usage. To address this issue, in this paper we propose novel scaling perturbation based privacy-preserving schemes that can achieve great utility for fine-grained measurements in a privacy-friendly and cost-effective manner. Our schemes adopt the measurement-based scaling perturbation to hide original measurements with low cost. Through a combination of both extensive theoretical analysis and experiments, our results show that the proposed schemes can preserve consumers' privacy through fine-grained measurements and achieve a better utility-privacy tradeoff in comparison with the existing schemes.

On Scaling Perturbation Based Privacy-Preserving Schemes in Smart Metering Systems

With the explosive growth of mobile devices and subsequent traffic volume, densified deployment of Heterogeneous Network (HetNet) coexisting with a variety of cells with overlay coverage has emerged as a viable solution for future 5G networks. Despite many advantages, this new architecture also introduces numerous new network management issues, such as frequent handovers. Although a number of handover mechanisms have been proposed, these methods generally depend on one or more objective attributes from the perspective of the users and network, and do not consider the subjective demands of personalized users and specific applications that demand differentiated network services. In this paper, we first develop an software defined networking (SDN)-driven handover architecture that is capable of perceiving global network statements and requirements from all perspectives, including the physical layer, users, and applications. Then, a context-aware multi-criteria handover mechanism is developed in the SDN controller to provide differentiated services. Considering the many complicated factors, the handover decision is made based on a hierarchical fuzzy inference system to process diverse attributes and fuzzy information described in natural language. The evaluation results demonstrate that our scheme outperforms the baseline Received Signal Strength Indicator (RSSI)-based handover scheme, more efficiently providing differentiated services with respect to throughput, bandwidth cost, and application satisfaction.

Context-Aware Multi-Criteria Handover with Fuzzy Inference in Software Defined 5G HetNets

With the tremendous growth of the Internet of Things (IoT), big data, and artificial intelligence (AI), the edge computing-based service paradigm has been introduced to meet the increasing demand of applications. To provide efficient computing services at the network edge, the algorithms and applications are generally deployed based on the container-based microservice strategy, which significantly impacts the system efficiency and QoS. Considering the fundamental system uncertainties, including the dynamic workload and service rate, we investigate how to minimize the long-term system cost through the elastic microservice deployment in this paper. To this end, we formulate the container-based microservice deployment as a stochastic optimization problem to minimize the system cost while maintaining the system QoS and stability. We develop a cost-aware elastic microservice deployment algorithm to solve the formulated problem, which balances the tradeoff between system cost and QoS. Our algorithm makes the real-time decisions based on current queue backlogs and system states without predicting the future knowledge. Finally, we conduct the theoretical analysis and extensive simulations based on data traces from the ResNet-50 model-based visual recognition application. The results demonstrate that our algorithm outperforms the baseline strategies with respect to the system cost, queue backlogs, and the number of Pod replicas.

/pdf/towards-cost-efficient-edge-intelligent-computing-with-24bw0sqfom.pdf

Jie Lin

Papers

On binary decomposition based privacy-preserving aggregation schemes in real-time monitoring systems

A novel multitype-users welfare equilibrium based real-time pricing in smart grid

On Scaling Perturbation Based Privacy-Preserving Schemes in Smart Metering Systems

Context-Aware Multi-Criteria Handover with Fuzzy Inference in Software Defined 5G HetNets

Towards Cost-Efficient Edge Intelligent Computing With Elastic Deployment of Container-Based Microservices