A Review of P4 Programmable Data Planes for Network Security

Network attacks show a trend of increased attack intensity, enhanced diversity, and more concealed attack methods, which put forward higher requirements for the performance of network security equipment. Unlike the SDN (software defined network) switch with a fixed-function data plane, switches with programmable data planes can help users realize more network protocols. Programming Protocol-independent Packet Processors (P4) is proposed to define the operations of the data plane and to implement user’s applications, e.g., data center networks, security, or 5G. This paper provides a review of research papers on solving network security problems with P4-based programmable data plane. The work can be organized into two parts. In the first part, the programming language P4, P4 program, architectures, P4 compilers, P4 Runtime, and P4 target are introduced according to the workflow model. The advantages of P4-based programmable switching in solving network security are analyzed. In the second part, the existing network security research papers are divided into four parts according to the perspectives of passive defense, active defense, and combination of multiple technologies. The schemes in each category are compared, and the core ideas and limitations are clarified. In addition, a detailed comparison is made for the research on the performance of P4 targets. Finally, trends and challenges related to the P4-based programmable data plane are discussed.

Practical Remote Workflow Solutions for Complex Digital Projects: Opportunities in a Pandemic

The spread of COVID-19 has created numerous challenges in the field of archive management. Limited in-house office space, furloughs of personnel, and inconsistency, has highlighted the potential for the Carl Albert Congressional Research and Studies Center Archives (Center) to develop and implement improved accessibility measures to thousands of linear feet of material. Addition ally, the Center has found unique opportunities to collaborate with multiple academic institutions to propose large-scale digitization program exhibitions using the Center’s remote workflow model. One of the largest, most complex collections the Center has worked with during this time is the Political Commercial Collection (the Collection), which holds 119,000 film, audio, and videotape recordings of commercials aired between 1936 and present. It is the largest collection of political commercials in the world. The Center has developed a working pilot digitization project that has currently resulted in access to 16,000 digital videos for public researchers and over 10,000 available for on-line streaming during the pilot phase between April 16, 2020, and December 1, 2020. This paper presents the practical application of the Center’s simplified “Linear Reciprocity Workflow Model” to provide a systematic solution for digital and long-term preservation of complex collections. The Center has proven that limited personnel and reduced resources need not interrupt continued access to archival repositories.

Cognition of Graphical Notation for Processing Data in ERDAS IMAGINE

This article presents an evaluation of the ERDAS IMAGINE Spatial Model Editor from the perspective of effective cognition. Workflow models designed in Spatial Model Editor are used for the automatic processing of remote sensing data. The process steps are designed as a chain of operations in the workflow model. The functionalities of the Spatial Model Editor and the visual vocabulary are both important for users. The cognitive quality of the visual vocabulary increases the comprehension of workflows during creation and utilization. The visual vocabulary influences the user’s exploitation of workflow models. The complex Physics of Notations theory was applied to the visual vocabulary on ERDAS IMAGINE Spatial Model Editor. The results were supplemented and verified using the eye-tracking method. The evaluation of user gaze and the movement of the eyes above workflow models brought real insight into the user’s cognition of the model. The main findings are that ERDAS Spatial Model Editor mostly fulfils the requirements for effective cognition of visual vocabulary. Namely, the semantic transparency and dual coding of symbols are very high, according to the Physics of Notations theory. The semantic transparency and perceptual discriminability of the symbols are verified through eye-tracking. The eye-tracking results show that the curved connector lines adversely affect the velocity of reading and produce errors. The application of the Physics of Notations theory and the eye-tracking method provides a useful evaluation of graphical notation as well as recommendations for the user design of workflow models in their practice.

Impact of a “Pharmacist First” innovative workflow plan in patients with hypertension and/or diabetes

Usual community pharmacy workflow, whereby patients might see a pharmacist at the end of the dispensing process, is not conducive to proactive patient-centred care. The objective of this study was to evaluate the impact of the “Pharmacist First” (P1st) workflow model on blood pressure and glycemic control in patients with hypertension and/or diabetes. This retrospective review was set in 2 community pharmacies that use the P1st model in the Greater Edmonton Region. The population entailed patients with hypertension and/or type 1 or 2 diabetes who received care via the P1st workflow model. The P1st workflow model places the patient in immediate contact with the pharmacist. The pharmacist first assesses prescription appropriateness, reviews relevant laboratory tests, discusses chronic disease control and addresses any questions or concerns the patient has before passing the prescription to be filled by a technician. This allows issues or concerns to be identified and addressed up front, rather than waiting until the prescription is filled and the patient is ready to leave the pharmacy. The primary outcome assessed in this study was change in blood pressure and/or A1C from baseline to the last follow-up visit. We reviewed 215 patient records. The mean age was 69.4 years (standard deviation 12.5), 51.2% of patients were male, 57.7% had hypertension, 5.6% had diabetes, and 36.7% had both. Median follow-up time was 4.2 months (interquartile range 2.5 -9.3). In 203 patients with hypertension, systolic blood pressure was reduced from 139.83 mmHg to 131.26 mmHg ( p < 0.001) and diastolic blood pressure from 80.26 mmHg to 76.86 mmHg ( p < 0.001). In 87 patients with diabetes, A1C changed from 7.4% to 7.2% ( p = ns). The P1st workflow model demonstrated significant improvements in blood pressure. Further investigation is needed to evaluate the effectiveness of this model with a control group, longer follow-up and evaluation of the patient experience.

Automated Quantum Hardware Selection for Quantum Workflows

The execution of a quantum algorithm typically requires various classical pre- and post-processing tasks. Hence, workflows are a promising means to orchestrate these tasks, benefiting from their reliability, robustness, and features, such as transactional processing. However, the implementations of the tasks may be very heterogeneous and they depend on the quantum hardware used to execute the quantum circuits of the algorithm. Additionally, today’s quantum computers are still restricted, which limits the size of the quantum circuits that can be executed. As the circuit size often depends on the input data of the algorithm, the selection of quantum hardware to execute a quantum circuit must be done at workflow runtime. However, modeling all possible alternative tasks would clutter the workflow model and require its adaptation whenever a new quantum computer or software tool is released. To overcome this problem, we introduce an approach to automatically select suitable quantum hardware for the execution of quantum circuits in workflows. Furthermore, it enables the dynamic adaptation of the workflows, depending on the selection at runtime based on reusable workflow fragments. We validate our approach with a prototypical implementation and a case study demonstrating the hardware selection for Simon’s algorithm.

Geohazard characterization using remote sensing to model flash floods of the Southeast Sinai, Egypt

Flash floods have led to disruptions of human activities and the destruction of properties particularly in the Nuweiba region of Southeast Sinai. Despite the arid nature of Sinai, flash floods still pose a great hazard to the region. Using remote sensing characterization, geohazard models were developed to identify flash flood areas, delineate and discriminate morphological features, active channels areas and soil physiography with a view to categorize risk areas exposed to flash floods hazards in a hazard map and proffer measures for mitigation. The characterization was achieved using a workflow model developed from spatial datasets of Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) and the red-green-blue (RGB) composites from Landsat bands 7 ETM+. The data was used to investigate and assess flash flood areas for morphological attributes, watershed basin characterization, generation of false color composite from Landsat 7 ETM+ 7, 4 and 2 RGB bands and Principal Component Analysis (PCA) band from composite of 742 RGB. Multivariate analysis of generated raster layer attributes provided enhancements and attribute discrimination for delineating areas of active flood channels, upslope zones and soil physiography discrimination from their spectral reflectance. The results are presented in an integrated approach of remote sensing with geographic information systems (GIS) and indicates that the soil types and geological units contribute greatly towards activation of these flash floods which is triggered by intense rainstorms. Components of generated map attributes of SRTM DEM, gradient of DEM and Landsat 7 ETM+ composite of 742 bands in GIS were used to generate a hazard map using spatial analysis to depict the nature and scale of issues identified. Due to flash floods vulnerabilities, the study area was classified into stable/low, moderate and high-risk areas. Mitigation measures to control flash floods were proposed to enable adequate preparations to mitigate impending flash flood disasters.

Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

Abstract P849: Effects of Standardized Stroke Protocols on Nursing Confidence and Knowledge in Low Volume Telestroke Emergency Departments

Introduction: Nurses and staff in Emergency Departments (ED) with low monthly case volumes have few opportunities to build confidence and solidify skills in acute stroke management. The Nursing-driven Acute Stroke Care (NAS-Care) study tested a workflow model with empowerment of ED bedside nurses, clear role assignments for team members, and standardized protocols including a predefined run sheet. Methods: Seven Texas hospitals participated in this prospective, multisite, baseline-controlled study as part of the Lone Star Stroke Research Consortium. After three months of blinded baseline data collection, the following interventions were implemented: NIHSS certification, nursing education including mock stroke codes, and a standardized flowsheet for code organization and documentation (run sheet). Participating nurses were surveyed before and after implementation of this process. Results: The study was completed at 6 hospitals, with 180 patients in the pre-intervention group and 267 in the post-intervention group. The study intervention was found to improve Door-to-ED provider and Door-to-CT metrics but not physician-dependent metrics, Door-to-Needle or Door-to-Provider times (Provencher et al, ISC 2020). Completed surveys were returned by 97 nurses (pre-intervention) and 57 nurses (post-intervention). There were significant increases in the following questions (10 point scale, p<.001): “I understand goals and processes of stroke code activation”, “stroke codes at my institution are completed efficiently”, and “stroke codes are nursing-driven.” In the post-intervention surveys, nurses reported that the NAS-Care protocol improved understanding (mean score 8.0 +/- 2.4 SD/10) and efficiency (8.2 +/- 2.4/10), and reported that they would recommend NAS-Care to be adopted at other institutions (8.8 +/- 2.1/10). Conclusion: Standardized nurse-driven stroke protocols improved self-assessed knowledge and confidence for nurses in EDs utilizing telestroke, in addition to gains in staff-dependent stroke metrics.