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Programming Protocol-independent Packet Processors (P4) is an open-source domain-specific language to aid the data plane devices in programming packet forwarding. It has a variety of constructs optimized for this purpose. With P4, one can program ASICs, PISA chips, FPGAs, and many network devices since the language constructs allow true independence in some aspects that OpenFlow could not support. However, there are some challenges facing this technology. The first challenge is that P4 does not account for malicious traffic detection in the data plane pipeline. 2. The controllers have no secure medium of attack signature exchange. This ongoing work presents a multichain solution for detecting malicious traffic and exchanging attack signatures among controllers. This architecture uses an Artificial Immune System (AIS) based Intrusion Detection System (IDS), which runs on a distributed blockchain network, to introspect the P4 data plane to analyze and detect anomaly traffic flows. This IDS resides on the SideChain smart contracts and constantly monitors the traffic flow at the data planes based on introspection. Once malicious traffic is detected on any SideChain, the signatures are extracted and passed through the signature forwarding node to the MainChain for real-time storage. The malicious signatures are sent to all controllers via the mainchain network. We minimize the congestion the solution can cause to the P4 network by utilizing a load balancer to serve the SideChain. To evaluate the performance, we evaluate the False Positive Rate (FPR), Detection Rate (DR), and Accuracy (ACC) of the IDS. We also compute the execution time, performance overhead, and scalability of the proposed solution. 

P4 (Programming Protocol-Independent Packet Processors) represents a paradigm shift in network programmability by providing a high-level language to define packet processing behavior in network switches/devices. The importance of P4 lies in its ability to overcome the limitations of OpenFlow, the previous de facto standard for software-defined networking (SDN). Unlike OpenFlow, which operates on fixed match-action tables, P4 offers an approach where network operators can define packet processing behaviors at various protocol layers. P4 provides a programmable platform to create and implement custom network switches/devices protocols. However, this opens a new attack surface for threat actors who can access P4-enabled switches/devices and manipulate custom protocols for malicious purposes. Attackers can craft malicious packets to exploit protocol-specific vulnerabilities in these network devices. This ongoing research work proposes a blockchain-based model to secure P4 custom protocols. The model leverages the blockchain’s immutability, tamperproof ability, distributed consensus for protocol governance, and auditing to guarantee the transparency, security, and integrity of custom protocols defined in P4 programmable switches. The protocols are recorded as transactions and stored on the blockchain network. The model's performance will be evaluated using execution time in overhead computation, false positive rate, and network scalability. 

Since its inception in 2008, Blockchain has been proposed in different fields of study, and the research results have shown promising prospects in these areas. Despite these study results, blockchain technology has suffered some setbacks in adoption for real-life implementations. The unwillingness to adopt it stems from industries and organizations not being convinced about the proposed solutions' results. The reason is that many of the presented solution results come from simulation. While simulation results are acceptable for research purposes, industries might be skeptical about adopting a new system based only on simulation results. Researchers must present results from real-life implementations to fully convince stakeholders of the usefulness of adopting blockchain technology. However, presenting blockchain results from reallife performance is challenging because of the following significant problems: 1. Blockchain networks are customized to implement a single approach, i.e., no blockchain network can test multiple proposed implementations concurrently, and 2. There is a lack of testbeds (with enough blockchain nodes) to test proposed solutions. This ongoing work presents a Programmable Blockchain Network (PBN), which can implement multiple approaches simultaneously and a global testbed to evaluate proposed solutions in real-life scenarios. The PBN, implemented on Generic Routing Encapsulation (GRE) global testbed, uses a master-slave model for smart contracts calling to implement concurrent blockchain solutions. The preliminary result shows that the proposed solution enhances research results, convincing more industries to adopt blockchain technology. 

Since its inception in 2008, Blockchain has been proposed in different fields of study, and the research results have shown promising prospects in these areas. Despite these study results, blockchain technology has suffered some setbacks in adoption for real-life implementations. The unwillingness to adopt it stems from industries and organizations not being convinced about the proposed solutions' results. The reason is that many of the presented solution results come from simulation. While simulation results are acceptable for research purposes, industries might be skeptical about adopting a new system based only on simulation results. Researchers must present results from real-life implementations to fully convince stakeholders of the usefulness of adopting blockchain technology. However, presenting blockchain results from reallife performance is challenging because of the following significant problems: 1. Blockchain networks are customized to implement a single approach, i.e., no blockchain network can test multiple proposed implementations concurrently, and 2. There is a lack of testbeds (with enough blockchain nodes) to test proposed solutions. This ongoing work presents a Programmable Blockchain Network (PBN), which can implement multiple approaches simultaneously and a global testbed to evaluate proposed solutions in real-life scenarios. The PBN, implemented on Generic Routing Encapsulation (GRE) global testbed, uses a master-slave model for smart contracts calling to implement concurrent blockchain solutions. The preliminary result shows that the proposed solution enhances research results, convincing more industries to adopt blockchain technology. 

While millimeter-wave (mmWave) wireless has recently gained tremendous attention with the transition to 5G, developing a broadly accessible experimental infrastructure will allow the research community to make significant progress in this area. Hence, in this paper, we present the design and implementation of various programmable and open-access 28/60 GHz software-defined radios (SDRs), deployed in the PAWR COSMOS advanced wireless testbed. These programmable mmWave radios are based on the IBM 28 GHz 64-element dual-polarized phased array antenna module (PAAM) subsystem board and the Sivers IMA 60 GHz WiGig transceiver. These front ends are integrated with USRP SDRs or Xilinx RFSoC boards, which provide baseband signal processing capabilities. Moreover, we present measurements of the TX/RX beamforming performance and example experiments (e.g., real-time channel sounding and RFNoC-based 802.11ad preamble detection), using the mmWave radios. Finally, we discuss ongoing enhancement and development efforts focusing on these radios. 

Optical networks satisfy high bandwidth and low latency requirements for telecommunication networks and data center interconnection. To improve network resource utilization, machine learning (ML) is used to accurately model optical amplifiers such as erbium-doped fiber amplifiers (EDFAs), which impact end-to-end system performance such as quality of transmission. However, a comprehensive measurement dataset is required for ML to accurately predict an EDFA’s wavelength-dependent gain. We present an open dataset consisting of 202,752 gain spectrum measurements collected from 16 commercial-grade reconfigurable optical add–drop multiplexer (ROADM) booster and pre-amplifier EDFAs under varying gain settings and diverse channel-loading configurations over 2,785 hours in total, with a total dataset size of 3.1 GB. With this EDFA dataset, we implemented component-level deep-neural-network-based EDFA models and use transfer learning (TL) to transfer the EDFA model among 16 ROADM EDFAs, which achieve less than 0.18/0.24 dB mean absolute error for booster/pre-amplifier gain prediction using only 0.5% of the full target training set. We also showed that TL reduces the EDFA data collection requirements on a new gain setting or a different type of EDFA on the same ROADM.

 

Blockchain is a decentralized, digital, and distributed ledger which allows transparent and secure information sharing among the peer-to-peer network. It eliminates the need for a centralized trusted party and, though it was introduced as the backbone technology for cryptocurrencies but has proved to be a promising and revolutionary technology for almost all global industries. The application of blockchain technology in the energy sector proposes a paradigm of solutions to problems of different levels of complexity in the traditional energy ecosystem. Extensive research has been proposed to exploit the inherent benefits of blockchain technology for the integration of distributed energy sources and facilitate peer-to-peer energy trading. This paper proposes a blockchain-based architecture to facilitate secure and decentralized energy trading generated from renewable energy sources. The solution utilizes the Ethereum blockchain and Smart Contracts for energy trading among the members of a small community without any trusted third entity and adopts features to achieve data integrity and confidentiality, and user identity privacy. 

Coexistence of real-time constant-amplitude distributed acoustic sensing (DAS) and 400GbE signals is verified by field trial over metro fibers, demonstrating no QoT impact during co-propagation and supporting preemptive DAS-informed optical path switching before link failure.