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 rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. Fulfilling these tasks is challenging, as mobile environments are increasingly complex, heterogeneous, and evolving. One potential solution is to resort to advanced machine learning techniques, in order to help manage the rise in data volumes and algorithm-driven applications. The recent success of deep learning underpins new and powerful tools that tackle problems in this space. In this paper, we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas. We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking. We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems. Subsequently, we provide an encyclopedic review of mobile and wireless networking research based on deep learning, which we categorize by different domains. Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.

/pdf/deep-learning-in-mobile-and-wireless-networking-a-survey-ct8cy2kuqi.pdf

Deep Learning in Mobile and Wireless Networking: A Survey

Space-air-ground integrated network (SAGIN), as an integration of satellite systems, aerial networks, and terrestrial communications, has been becoming an emerging architecture and attracted intensive research interest during the past years. Besides bringing significant benefits for various practical services and applications, SAGIN is also facing many unprecedented challenges due to its specific characteristics, such as heterogeneity, self-organization, and time-variability. Compared to traditional ground or satellite networks, SAGIN is affected by the limited and unbalanced network resources in all three network segments, so that it is difficult to obtain the best performances for traffic delivery. Therefore, the system integration, protocol optimization, resource management, and allocation in SAGIN is of great significance. To the best of our knowledge, we are the first to present the state-of-the-art of the SAGIN since existing survey papers focused on either only one single network segment in space or air, or the integration of space-ground, neglecting the integration of all the three network segments. In light of this, we present in this paper a comprehensive review of recent research works concerning SAGIN from network design and resource allocation to performance analysis and optimization. After discussing several existing network architectures, we also point out some technology challenges and future directions.

Space-Air-Ground Integrated Network: A Survey

A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT

As a powerful tool, the vehicular network has been built to connect human communication and transportation around the world for many years to come. However, with the rapid growth of vehicles, the vehicular network becomes heterogeneous, dynamic, and large scaled, which makes it difficult to meet the strict requirements, such as ultralow latency, high reliability, high security, and massive connections of the next-generation (6G) network. Recently, machine learning (ML) has emerged as a powerful artificial intelligence (AI) technique to make both the vehicle and wireless communication highly efficient and adaptable. Naturally, employing ML into vehicular communication and network becomes a hot topic and is being widely studied in both academia and industry, paving the way for the future intelligentization in 6G vehicular networks. In this article, we provide a survey on various ML techniques applied to communication, networking, and security parts in vehicular networks and envision the ways of enabling AI toward a future 6G vehicular network, including the evolution of intelligent radio (IR), network intelligentization, and self-learning with proactive exploration.

Future Intelligent and Secure Vehicular Network Toward 6G: Machine-Learning Approaches

Security has become one of major concern especially in critical applications like e-healthcare. To cater to the security needs in e-healthcare, this paper proposes a novel scheme which prevents data from unauthorized fabrication and preserves the integrity of data. The proposed scheme also removes overhead of integrity validation from user's end as this work is assigned to a trusted third party, i.e., a proxy server. For this purpose, the patient's data given by user is sent to proxy server along with user's signature where it is broken down in the form of blocks. A ‘tag’ is then generated for each block using lightweight elliptic curve cryptography (ECC). This block-tag pair is then uploaded on the data server which is used for integrity checking. Whenever a patient's data access request is raised, the block of data is retrieved using tag value and integrity is then verified. In addition to it, a lightweight lattice-based authentication scheme is proposed in the paper to authenticate the users. The request is served only when the user is deemed authentic and there is no modification in the original data sent by the user. The effectiveness of the proposed authentication scheme has been proven by performing its analysis in terms of computation time and communication cost. Moreover, the superiority of the proposed data integrity scheme has been validated by comparing it with the traditional discrete logarithmic scheme.

LEASE: Lattice and ECC-Based Authentication and Integrity Verification Scheme in E-Healthcare

Data security is an integral part of web based business applications like insurance, banking etc. These applications require a secure infrastructure to meet the security requirements of confidentiality, endpoint authentication, message integrity and no repudiation. Document encryption/decryption and signatures/validation are the data security standards that define XML vocabularies and processing rules to meet these security requirements. In this paper, we present a how a file securely passes from sender (server) to the receiver (client) through a central gateway with web services applications which mean a secure architecture for the exchange of confidential documents. Designing a secured electronic system architecture i.e. connected to the central gateway through which the whole work is established and takes place accordingly to pass only the files over the internet and have security features like digital signatures. Various algorithms, implementations and coding have been developed for encryption/decryption, signatures/validations and web services.

A Security Solution for the Transmission of Confidential Data and Efficient File Authentication Based on DES, AES, DSS and RSA

In recent years, the huge expansion of Datacenters (DC) to execute billions of end-user applications in real-time leads to a large amount of energy consumption across the globe So, the traditional TCP/IP-based networks which are being used for DC inter-connections are facing challenges of managing stringent Quality-of-Service (QoS) requirements of different applications of the end-users and service providers Moreover, the existing solutions rely on distributed architecture and do not scale for large scale data centers The issue of high power consumption at DC arises with the increase in the number of nodes and links in the network Also, it becomes problematic on the DC whenever the underlying network resources (switches and routers) are not efficiently utilized at the time of peak data traffic resulting in high operational cost of energy utilization However, Software-Defined Networking (SDN) emerges as one of the leading technologies to address the aforementioned issues using the programmable switches and controllers Inspired from these facts, in this paper, we have formulated the Energy-Aware Routing (EAR) problem of DCs as a Mixed Integer Non-Linear Programming (MINLP) for which an Energy-Efficient Fast Flow Forwarding (EnFlow) scheme is designed The EnFlow scheme uses the power-saving mode of the network to solve the EAR problem It has three modules namely– priority scheduling , routing , and re-routing  The first module works according to the First-in-First-Out Push Out Priority (FIFO-POP) scheduling using the multiple OpenFlow switches The FIFO-POP is designed to save the energy usage of multiple switches by reducing the average waiting time of incoming packets in the queue buffers The second module is based upon an efficient flow re-routing for a new node and link adaptation to provide the maximum bandwidth to the wired links The third module is based upon the meta-heuristic Ant Colony Routing (ACR) to execute the stochastic decision policy on the network controller for computation of the shortest path of the forwarding nodes The proposed EnFlow scheme is simulated using the data traces of 34 cities of NorthAmerica zone with Omnet++ 51 using various performance evaluation metrics The results obtained demonstrated that the proposed EnFlow scheme is 2455% and 7115% more energy-efficient in comparison to the RE-FPR and ILP-EAR schemes Also, it consumes 972% and 4083% lower energy in comparison to the FFHA and EXR schemes respectively

EnFlow: An Energy-Efficient Fast Flow Forwarding Scheme for Software-Defined Networks

In a multi-cloud environment, consumers can access multiple cloud services using a single heterogeneous computing architecture. In such an environment, multiple instances of the same cloud service and its component may be geographically dispersed. So, cloud service broker (CSB) exploits the heterogeneity of multi-cloud environment to provide high performance at a low price to its consumers. The consumer tasks are allocated to the geo-dispersed cloud service components for execution of various services. For this purpose, an optimal service components identification and task allocation are major concerns keeping in view of the heterogeneity in multi-cloud environment. For this purpose, a scheduling algorithm, which takes care of location, price, and performance is required. Therefore, in this paper, SLOPE: A Self Learning Optimization and Prediction Ensembler for Task Scheduling in Multi-cloud Environment is proposed. SLOPE works in two phases, 1) In first phase, Bayes theorem is used to design a self-learning algorithm, to compute the conditional probability (strength) of each service component in order to select the probable rule string, and 2) a roulette wheel method is used to select an optimal scheduling policy for a given service request. SLOPE helps to identify the best possible service component from the pool of resources on the basis of dynamic factors and then schedule a service request to the selected component. Unlike most of the other existing approaches, SLOPE builds an efficient schedule for service selection. Experimental results demonstrate that SLOPE performs better in comparison to other competing schemes of its category.

SLOPE: A Self Learning Optimization and Prediction Ensembler for Task Scheduling

Metaverse is an evolving paradigm for the next-generation Internet, intends to provide 3D immersive experiences and self–sustaining virtual shared space by utilising a wide range of relevant technologies. Due to rapid advancement in technologies such as augmented reality (AR), mixed reality and virtual reality (VR) in real-time applications, metaverse is proceeding from science fiction to extended reality (XR). In this article, we present the vision of metaverse's future in wireless technologies, including 6G and beyond. We illustrate the framework of metaverse-based wireless systems, describing the requirements and fundamental technologies to be integrated with 6G to realize the metaverse. We consider a case study of an autonomous vehicle's remote assistance system that leverages VR technology, 360° live stream, and a mobile edge-enabled distributed computing paradigm. The simulation findings demonstrate the effectiveness of employing VR technology to create an immersive environment for remotely controlling and supporting autonomous vehicles to enable quicker decision-making. Furthermore, we compare several potential future networks, discuss the deployment challenges, and present cloud-edge-end framework-driven solutions to employ Next-G wireless systems in the metaverse. Finally, we outline several open research directions to realize the true vision of metaverse towards 6G and beyond.

Rajat Chaudhary

Papers

LEASE: Lattice and ECC-Based Authentication and Integrity Verification Scheme in E-Healthcare

A Security Solution for the Transmission of Confidential Data and Efficient File Authentication Based on DES, AES, DSS and RSA

EnFlow: An Energy-Efficient Fast Flow Forwarding Scheme for Software-Defined Networks

SLOPE: A Self Learning Optimization and Prediction Ensembler for Task Scheduling

Metaverse for 6G and Beyond: The Next Revolution and Deployment Challenges