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Aqueous sodium-ion batteries (ASIBs) represent a promising battery technology for stationary energy storage, due to their attractive merits of low cost, high abundance, and inherent safety. Recently, a variety of advanced cathode, anode, and electrolyte materials have been developed for ASIBs, which not only enhance our fundamental understanding of the Na insertion mechanism, but also facilitate the research and development of practical ASIB systems. Among these electrode materials, iron-based materials are of particular importance because of the high abundance, low price, and low toxicity of Fe elements. However, to our knowledge, there are no review papers that specifically discuss the properties of Fe-based materials for ASIBs yet. In this review, we present the recent research progress on Fe-based cathode/anode materials, which include polyanionic compounds, Prussian blue, oxides, carbides, and selenides. We also discuss the research efforts to build Fe-based ASIB full cells. Lastly, we share our perspectives on the key challenges that need to be addressed and suggest alternative directions for aqueous Na-ion batteries. We hope this review paper can promote more research efforts on the development of low-cost and low-toxicity materials for aqueous battery applications. 

This paper describes a cloud infrastructure and virtual laboratories on P4 programmable data plane switches. P4 programmable data planes emerged as a technology that enables innovation in networking. P4 is a programming language used to describe how network packets are processed. This paper explains an entry-level training library on P4. The virtual laboratories introduce the learner to P4 and data plane concepts by providing step-by-step guides and exercises. The virtual laboratories are hosted in the Academic Cloud, a distributed platform that manages and orchestrates computing resources. Additionally, the paper describes a work in progress of P4 virtual laboratories that uses Intel Tofino switches. Lastly, the paper discusses the use of the Academic Cloud as a network testbed. 

The alpha version of Bottleneck Bandwidth and Round-trip Time version 2 (BBRv2) has been recently presented, which aims to mitigate the shortcomings of its predecessor, BBR version 1 (BBRv1). Previous studies show that BBRv1 provides a high link utilization and low queuing delay by estimating the available bottleneck bandwidth. However, its aggressiveness induces unfairness when flows i) use different congestion control algorithms, such as CUBIC, and ii) have distinct round-trip times (RTTs). This paper presents an experimental evaluation of BBRv2, using Mininet. Results show that the coexistence between BBRv2-CUBIC is enhanced with respect to that of BBRv1-CUBIC, as measured by the fairness index. They also show that BBRv2 mitigates the RTT unfairness problem observed in BBRv1. Additionally, BBRv2 achieves a better fair share of the bandwidth than its predecessor when network conditions such as bandwidth and latency dynamically change. Results also indicate that the average flow completion time of concurrent flows is reduced when BBRv2 is used. 

This paper describes the deployment of a private cloud and the development of virtual laboratories and companion material to teach and train engineering students and Information Technology (IT) professionals in high-throughput networks and cybersecurity. The material and platform, deployed at the University of South Carolina, are also used by other institutions to support regular academic courses, self-pace training of professional IT staff, and workshops across the country. The private cloud is used to deploy scenarios consisting of high-speed networks (up to 50 Gbps), multi-domain environments emulating internetworks, and infrastructures under cyber-attacks using live traffic. For regular academic courses, the virtual laboratories have been adopted by institutions in different states to supplement theoretical material with hands-on activities in IT, electrical engineering, and computer science programs. Topics include Local Area Networks (LANs), congestion-control algorithms, performance tools used to emulate wide area networks (WANs) and their attributes (packet loss, reordering, corruption, latency, jitter, etc.), data transfer applications for high-speed networks, queueing delay and buffer size in routers and switches, active monitoring of multi-domain systems, high-performance cybersecurity tools such as Zeek’s intrusion detection systems, and others. The training platform has been also used by IT professionals from more than 30 states, for self-pace training. The material provides training on topics beyond general-purpose network, which are usually overlooked by practitioners and researchers. The virtual laboratories and companion material have also been used in workshops organized across the country. Workshops are co-organized with organizations that operate large backbone networks connecting research centers and national laboratories, and colleges and universities conducting teaching and research activities. 

Blockchain technology is the cornerstone of digital trust and systems’ decentralization. The necessity of eliminating trust in computing systems has triggered researchers to investigate the applicability of Blockchain to decentralize the conventional security models. Specifically, researchers continuously aim at minimizing trust in the well-known Public Key Infrastructure (PKI) model which currently requires a trusted Certificate Authority (CA) to sign digital certificates. Recently, the Automated Certificate Management Environment (ACME) was standardized as a certificate issuance automation protocol. It minimizes the human interaction by enabling certificates to be automatically requested, verified, and installed on servers. ACME only solved the automation issue, but the trust concerns remain as a trusted CA is required. In this paper we propose decentralizing the ACME protocol by using the Blockchain technology to enhance the current trust issues of the existing PKI model and to eliminate the need for a trusted CA. The system was implemented and tested on Ethereum Blockchain, and the results showed that the system is feasible in terms of cost, speed, and applicability on a wide range of devices including Internet of Things (IoT) devices.