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At least 307 records · Page 17

Obfuscation for high-performance computing systems

An example technique includes initializing, by an obfuscation computing system, communications with nodes in a distributed computing platform. The nodes include compute nodes that provide resources in the distributed computing platform and a controller node that performs resource management of the resources. The obfuscation computing system serves as an intermediary between the controller node and the compute nodes. The technique further includes outputting an interactive user interface (UI) providing a selection between a first privilege level and a second privilege level, and performing one of: based on the selection being for the first privilege level, a first obfuscation mechanism for the distributed computing platform to obfuscate digital traffic between a user computing system and the nodes, or based on the selection being for the second privilege level, a second obfuscation mechanism for the distributed computing platform to obfuscate digital traffic between the user computing system and the nodes.

Aloisio, Scott↗

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗

43-0434 Bridge Inspection Report 2021

The documentation includes the following: 1. 2021 NMDOT Bridge Inspection Report including Element Level Data Collection (in digital formats prepared by NMSU)--conforms to the National Bridge Inspection Standards and AASHTO Manual for Bridge Element Inspection; 2. 2021 Supplemental Report (in digital formats prepared by NMSU)--provides detailed information related to current condition of major bridge components; 3. 2021 Inspection Pictures (in digital format prepared by NMSU); 4. 2021 Delamination Map (in digital format prepared by LANL). During the 2021 inspection, three critical findings were reported to our LANL contact, Mr. Jonathan Stein, by text and/or email on June 26, 2021. 1. The south joint of the bridge had a modular section of the joint that could potentially come loose during the passing of vehicles. This was reported as a critical finding for safety. If the modular section becomes dislodged or deformed it could pose a serious hazard that could result in a punctured tire to vehicles, motorcyclists and/or bicyclist causing drivers/riders to lose control; 2. The bracket plate located at the north end of the bridge on the pedestrian walkway was corroded through and provides little protection to pedestrians and bicyclists. This was reported as a critical finding for safety to prevent injuries to people; 3. The north approach rail has three missing posts. These posts help ensure that traffic is redirected and the energy is absorbed by the rail. This was reported as a critical finding for safety. Additionally, the approach rail is on a curve with a nearby drop off. Immediate repair is recommended. Based on the 2021 inspection, the bridge deck is rated in "fair" condition. The chain drag performed on the deck identified several areas with delamination that are concentrated near the expansion joints, in the closure joint of the deck near the bridge centerline, and at the south end of the northbound lanes. The chain drag performed during the 2021 inspection revealed 215,333 sq. in. (1495 sq. ft) of delaminations and patched areas (not including the sidewalk). This is approximately a 600% increase from 2019. It is recommended that the delaminations and spalls with exposed rebar be repaired. The "delaminated area" map for the 2021 inspection is provided in the supplemental report.

42 ENGINEERING↗

Human Supervision of Autonomous Vehicle Fleet Operations and Associated Passenger Communications: Preprint

Advances in automated vehicle (AV) technology and expanded operations are rapidly emerging with Automated Mobility District (AMD) deployments in global cities. NLR's AMD research addresses critical elements of human supervision of AV fleet operations and associated passenger communications for vehicles in which no driver or safety attendant is present. Although sufficiently advanced AVs no longer have direct oversight by a driver, fleet management remains staffed with operations personnel at the operations command and control (OCC) facility. This paper examines the functionality of the OCC, drawing comparisons of how automated train control and automated people mover OCCs operate. Within an AMD, the OCC manages various vehicle types, sizes, and operational modes, including on-demand and fixed route service, to facilitate a 'network of networks' for transport within a metropolitan area. The OCC serves as oversight for multiple AV fleets assisting AVs via remote operation of vehicles, communication, and dispatching personnel to resolve problems. The OCC also coordinates system operation, geographically staging vehicles, and managing weather, police, and emergency events. Informed by traffic management center (TMC) strategies using highly integrated software and communications, OCCs facilitate seamless information flows. OCC personnel remotely assist passengers and oversee multi-party operation to ensure safety and security. Although social norms mitigate large-capacity unattended vehicle operations, social interaction in multi-party automated small vehicles has little precedent. This poses a new frontier for society and requires research to effectively understand and manage. Future research will monitor OCC implementations, passenger interfaces, and deployment scaling of initial AMD systems.

33 ADVANCED PROPULSION SYSTEMS↗

HELIOCOMM: Wireless Controls State-of-the-Art Report

This report introduces the concept of wireless controls in heliostat-based concentrating solar thermal power (CSP) systems. Specifically, the need for wireless communications to be implemented within the heliostat-based CSP systems is identified versus the existing approaches that follow wireline connections which suffer from high installation, operation, and maintenance cost. Furthermore, this report analyzes the most recent advances in the field of developing wireless controls in heliostat-based CSP systems, which are highlighted to be in their infancy given the primitive wireless networking solutions that they currently utilize and test. The main contribution of this report is the introduction of a novel HELIOCOMM system that supports the wireless controls in heliostat-based CSP systems by exploiting the next generation networking technology of integrated access and backhaul. Furthermore, the proposed HELIOCOMM system performs an artificial intelligent clustering approach of the heliostats and clusterhead selection and develops an entropy-based routing model to enable the heliostats to communicate with the central station by considering their energy availability and network traffic. Also, towards efficiently exploiting the limited resources in the developed wireless communication system, a resource allocation module is introduced that performs the maximization of the energy efficiency of each heliostat by minimizing its corresponding experienced end-to-end latency to communicate with the central station, while performing an intelligent bandwidth splitting in the access and backhaul wireless links. The overall architecture is presented, and its individual building components are discussed in detail.

14 SOLAR ENERGY↗

Directing Traffic in the Rhizosphere: How Phage and Fauna Shape the Flow and Fate of Root Carbon through Microbial Pathways

The rhizosphere, the portion of soil directly influenced by plant roots, is an area of great biological activity and intense carbon (C) cycling. Interactions among the residents of the rhizosphere, such as bacteria, fungi, viruses, and fauna, result in transformation and transfer C from root exudates and root debris to biomass and developing soil organic matter. The primary object of this research project was to explore the complex interactions controlling C flow in the rhizosphere and the response of these interactions to soil water conditions. We used stable isotope techniques combined with molecular analyses to observe the flow of C as it is fixed by plants from the atmosphere, deposited into the soil through plant roots, and exchanged through multiple pathways of the soil food web. This technical report summarizes the achievements of this project from field, greenhouse, and lab experiments.

54 ENVIRONMENTAL SCIENCES↗

The Role of the Digital Thread for Security, Resilience, and Adaptability in Manufacturing

The manufacturing sector is dramatically evolving with recent technical and digital advances. Among these, the digital thread is revolutionizing manufacturing operations well beyond the historic downloading of programs to computer numerically controlled (CNC) machine tools and the uploading of edited programs from CNC controllers. The digital thread is “the communication framework that enables a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives” (Leiva 2016). It is pervasive around the world and has changed the way society operates; for example, map apps are used to provide time-optimal directions to destinations using real-time traffic feedback. The digital thread makes it possible to digitally verify products, ensure that the latest technologies are deployed across the entire manufacturing ecosystem, and strengthen the workforce by making each individual more efficient and effective. These three foundational advanced manufacturing concepts will ensure a next-generation secure, resilient, and adaptable manufacturing ecosystem and sustainably support current and future needs of society (Lynn et al. 2020).

99 GENERAL AND MISCELLANEOUS↗

Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning

Modern vehicles rely on a myriad of electronic control units (ECUs) interconnected via controller area networks (CANs) for critical operations. Despite their ubiquitous use and reliability, CANs are susceptible to sophisticated cyberattacks, particularly masquerade attacks, which inject false data that mimic legitimate messages at the expected frequency. These attacks pose severe risks such as unintended acceleration, brake deactivation, and rogue steering. Traditional intrusion detection systems (IDS) often struggle to detect these subtle intrusions due to their seamless integration into normal traffic. This paper introduces a novel framework for detecting masquerade attacks in the CAN bus using graph machine learning (ML). We hypothesize that the integration of shallow graph embeddings with time series features derived from CAN frames enhances the detection of masquerade attacks. We show that by representing CAN bus frames as message sequence graphs (MSGs) and enriching each node with contextual statistical attributes from time series, we can enhance detection capabilities across various attack patterns compared to using graph-based features only. Our method ensures a comprehensive and dynamic analysis of CAN frame interactions, improving robustness and efficiency. Extensive experiments on the ROAD dataset validate the effectiveness of our approach, demonstrating statistically significant improvements in the detection rates of masquerade attacks compared to a baseline that uses graph-based features only as confirmed by Mann-Whitney U and Kolmogorov-Smirnov tests (p < 0.05) .

Marfo, William [Univ. of Texas, El Paso, TX (Unite↗

ESnet/JLab FPGA Accelerated Transport

To increase the science rate for high data rates/volumes, Thomas Jefferson National Accelerator Facility (JLab) has partnered with Energy Sciences Network (ESnet) to define an edge to data center traffic shaping / steering transport capability featuring data event aware network shaping and forwarding. The keystone of this ESnet+JLab FPGA Accelerated Transport (EJFAT) is the joint development of an AI/ML directed dynamic compute work Load Balancer (LB) of UDP streamed data. The LB is a suite consisting of a Field Programmable Gate Array (FPGA) executing the dynamically configurable, low fixed latency LB data plane featuring real-time packet redirection and high throughput, and a control plane running on the FPGA host computer that monitors network and compute farm telemetry in order to make dynamic AI/ML guided decisions for destination compute host redirection/load balancing and destination resource provisioning. The LB provides for three-tier horizontal scaling across LB suites, core compute hosts, and CPUs within a host. The LB effectively provides seamless integration of edge/core computing to support direct experimental data processing for immediate use by JLab science programs and others such as the EIC as well as data centers of the future requiring high throughput and low latency for both hot and cooled data for both running experiment data acquisition systems and data center use cases.

97 MATHEMATICS AND COMPUTING↗

Securing Inverter Communication: Proactive Intrusion Detection and Mitigation System to Tap, Analyze, and Act

The electric grid has undergone rapid, revolutionary changes in recent years; from the addition of advanced smart technologies to the growing penetration of distributed energy resources (DERs) to increased interconnectivity and communications. However, these added communications, access interfaces, and third-party software to enable autonomous control schemes and interconnectivity also expand the attack surface of the grid. To address the gap of DER cybersecurity and secure the grid-edge to motivate a holistic, defense-in-depth approach, a proactive intrusion detection and mitigation system (PIDMS) device was developed to secure PV smart inverter communications. The PIDMS was developed as a distributed, flexible bump-in-the-wire (BITW) solution for protecting PV smart inverter communications. Both cyber (network traffic) and physical (power system measurements) are processed using network intrusion monitoring tools and custom machinelearning algorithms for deep packet analysis and cyber-physical event correlation. The PIDMS not only detects abnormal events but also deploys mitigations to limit or eliminate system impact; the PIDMS communicates with peer PIDMSs at different locations using the MQTT protocol for increased situational awareness and alerting. The details of the PIDMS methodology and prototype development are detailed in this report as well as the evaluation results within a cyber-physical emulation environment and subsequent industry feedback.

14 SOLAR ENERGY↗

Understanding the Effects of Vehicle Platoons on Crash Type and Severity

Crash type is an informative indicator to infer driving behaviors and conditions that cause a crash. For example, rear-end and side-swipe crashes are typically caused by improper vehicle interaction such as sudden lane-changing or speed control while hit-object crashes are likely the result of a single driver’s mistake. This study investigated the impact of vehicles travelling as a group (platoon) and its configuration (i.e., types of vehicles consisting of the platoon) on crash type and severity since the vehicles could affect each other when travelling in close proximity. This study applied Generalized Structure Equation Modeling (GSEM) to capture the complex relationships among the various crash factors such as traffic condition, driver characteristics, environmental conditions, and vehicle interaction to the crash attributes including type and severity. This study collected over 3 million individual vehicle data from 39 traffic count sites in California to estimate the vehicle interactions and driving behaviors. The microscopic traffic data are matched to 1417 crash reports. Results showed that vehicles traveling in platoons are associated with more rear-end and side-swipe crashes. Speed difference in the platoon had a positive effect on hit-object crashes if the platoon comprises vehicles of homogeneous type – either trucks or non-trucks. In addition, human factors such as age and gender were identified as significant influential factors in all type of crashes, however truck involvement particularly played an important role amongst side-swipe crashes. Crash severity was negatively affected by total flow, and rear-end crashes were more likely to be severe compared with hit-object crashes. Based on findings, this study suggests practical operational strategies to reduce traffic instability associated with platooned vehicle patterns. Understanding the high-risk factors for different crash types and severities would provide valuable insights for decision-makers and transportation engineers to develop targeted intervention strategies in consideration of road users and traffic conditions such as fleet mix and speed.

ADVANCED PROPULSION SYSTEMS↗

Closed-form solutions towards real-time energy-optimal and collision-free speed planning with limited information

Under real-world driving conditions, available information is limited due to communication range, and connected and automated vehicles (CAVs) must plan and follow energy-optimal and collision-free speed trajectory with a high updating rate. To this end, this paper presents a holistic design of a speed planning algorithm using analytical closed-form optimal solutions. Using the simplest vehicle model, we derive closed-form solutions as a function of boundary conditions, and summarize them without and with state constraints imposed by speed limits and vehicle in front. Then, we introduce multiple modes (e.g., eco-approach to traffic signal) to properly respond dynamically changing situations, and present how to set boundary conditions for each mode, while guaranteeing nature of globally optimal solutions. Finally, we perform a large-scale simulation study to identify and quantify the energy impacts of CAVs for real-world driving routes. A simple but effective algorithm based on closed-form solutions shows a significant energy saving potential in comparison with human-driven vehicle and adaptive cruise controlled vehicle with connectivity.

Han, Jihun↗

Leveraging Multiple Connected Traffic Light Signals in an Energy-Efficient Speed Planner

Connecting automated vehicles to traffic lights can lead to significant energy savings by enabling them to pass through intersections in an energy-efficient way without unnecessary stops. A cellular-based communication system connecting multiple traffic lights can help realize the full potential of energy-efficient driving at intersections. Thus, we propose a hierarchical speed planner that can leverage information from multiple connected traffic lights. The proposed speed planner consists of two modules: a green window selector and a reference trajectory generator. The green window selector, based on Dijkstra’s algorithm, finds a series of "green windows" for connected traffic lights that builds an energy-optimal path for vehicles to follow. The reference trajectory generator finds optimal entering times, based on the selected green window at each intersection, and then computes reference trajectories. Deriving and using analytical optimal entering speeds as a function of entering times allows us to guarantee the computational simplicity suitable for real-time implementation. We also demonstrate how to balance energy and traffic flow perspectives in the reference trajectory generator. Lastly, a high-fidelity simulation framework is used to evaluate the proposed speed planner and quantify the extent to which it can save energy in various real-world urban route scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Genome-wide profiling of histone (H3) lysine 4 (K4) tri-methylation (me3) under drought, heat, and combined stresses in switchgrass

Background: Switchgrass (Panicum virgatum L.) is a warm-season perennial (C4) grass identified as an important biofuel crop in the United States. It is well adapted to the marginal environment where heat and moisture stresses predominantly affect crop growth. However, the underlying molecular mechanisms associated with heat and drought stress tolerance still need to be fully understood in switchgrass. The methylation of H3K4 is often associated with transcriptional activation of genes, including stress-responsive. Therefore, this study aimed to analyze genome-wide histone H3K4-tri-methylation in switchgrass under heat, drought, and combined stress. Results: In total, ~ 1.3 million H3K4me3 peaks were identified in this study using SICER. Among them, 7,342; 6,510; and 8,536 peaks responded under drought (DT), drought and heat (DTHT), and heat (HT) stresses, respectively. Most DT and DTHT peaks spanned 0 to + 2000 bases from the transcription start site [TSS]. By comparing differentially marked peaks with RNA-Seq data, we identified peaks associated with genes: 155 DT-responsive peaks with 118 DT-responsive genes, 121 DTHT-responsive peaks with 110 DTHT-responsive genes, and 175 HT-responsive peaks with 136 HT-responsive genes. We have identified various transcription factors involved in DT, DTHT, and HT stresses. Gene Ontology analysis using the AgriGO revealed that most genes belonged to biological processes. Most annotated peaks belonged to metabolite interconversion, RNA metabolism, transporter, protein modifying, defense/immunity, membrane traffic protein, transmembrane signal receptor, and transcriptional regulator protein families. Further, we identified significant peaks associated with TFs, hormones, signaling, fatty acid and carbohydrate metabolism, and secondary metabolites. qRT-PCR analysis revealed the relative expressions of six abiotic stress-responsive genes (transketolase, chromatin remodeling factor-CDH3, fatty-acid desaturase A, transmembrane protein 14C, beta-amylase 1, and integrase-type DNA binding protein genes) that were significantly (P < 0.05) marked during drought, heat, and combined stresses by comparing stress-induced against un-stressed and input controls. Conclusion: Our study provides a comprehensive and reproducible epigenomic analysis of drought, heat, and combined stress responses in switchgrass. Significant enrichment of H3K4me3 peaks downstream of the TSS of protein-coding genes was observed. In addition, the cost-effective experimental design, modified ChIP-Seq approach, and analyses presented here can serve as a prototype for other non-model plant species for conducting stress studies.

59 BASIC BIOLOGICAL SCIENCES↗

Oak Ridge National Laboratory Pilot Demonstration of an Attestation and Anomaly Detection Framework using Distributed Ledger Technology for Power Grid Infrastructure

This report summarizes the design and pilot demonstration of a framework called Grid Guard that was created to provide increased data and device trustworthiness to electric grid devices by leveraging distributed ledger technology (DLT), specifically blockchain. Grid Guard contains a combination of core cryptographic methods such as the secure hash algorithm (SHA), and asymmetric cryptography, private permissioned blockchain, baselining configuration data, consensus algorithm (Raft) and the Hyperledger Fabric (HLF) framework. The system implements a low energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems such as substations, control centers and metering infrastructures. Blockchain is a distributed database structured that provides a practically unalterable (immutable) timeline of stored transactions. By relying on hashing and the Raft consensus algorithm, if an entity tries to illegitimately alter a record at one instance of the database the other ledger nodes are not altered. They work to cross-reference each other and easily locate any incorrectly added data and remove it. The bulk raw data is stored in an off-chain storage (outside of the blockchain ledger) and a hash of this baseline data is stored in the Blockchain ledger via hashing windows of time-series and configuration data, after aggregation and filtering. The bulk off-chain data repository is then considered to be trust-anchored using the hashes stored in the blockchain. To secure the electric grid testbed devices and data, device configuration baselines were compared to those baselines that had been previously stored in the ledger. Statistical baselines for device configurations, network communication patterns, and high-speed sensor data are calculated and then stored off-chain and hashes stored in the ledger. Measurements such as three-phase voltage and current, frequency, breaker status, protection scheme settings, network configuration settings (and other device configuration artifacts) and network traffic features (packet interarrival times) are compared every minute or other selected time windows. During phase 1 of the Grid Guard DLT project different DLT technologies were studies, and an assessment was performed on DLT technology vulnerabilities, uses, and key characteristics. DLT consensus protocols were studies (e.g., RAFT, named after Reliable, Replicated, Redundant, And Fault-Tolerant). Also, cryptography, public, private and permissioned or permissionless systems were assessed. Grid Guard implements a permissioned private DLT. Consensus algorithm selection and choice of DLT implementation depended heavily on the use-case. For this use-case, parameters were selected to measure performance and existing tools for assessment. Benchmarking was performed theoretically and practically. During phase 2 hashed transactions/blocks were inserted into the ledger every second. During phase 2 of the Grid Guard DLT project, a prototype framework was developed and demonstrated for attestation of critical substation devices and data using precision timing systems that use PTP and IRIG-B protocols) on a testbed of operational devices that emulated a distribution substation, control center, and power metering infrastructure using real Operational Technology (OT). The testbed includes OT devices such as protective relays, human machine interfaces (HMI), and power meters. To determine when to collect and compare system and network baselines, an initial examination of an anomaly detection capability to identify malicious manipulation of data streams was conducted. The resulting anomaly detection was demonstrated in a set of experiments and leveraged to trigger device artifact attestation checks. Attestation checks occur against device configuration baselines when compared with the immutable blockchain-stored baselines, which provided a cryptographically supported means by which to store baselines. The electrical substation-grid testbed was created to test the Grid Guard framework. The testbed emulates the operations of a portion of a power grid and SCADA systems as closely as possible. The testbed integrates real protocols, mainly IEC 61850 standard protocols, such as the Sampled Value (SV) and the GOOSE protocols. The testbed also supports DNP3 and other layer 2 and layer 3 protocols such as Telnet, SSH, SFTP/FTP and other proprietary protocols needed to connect to industrial control system equipment. The testbed emulates real power conditions using the OpalRT hardware-in-the-loop (HIL) device which can create fault situations that cannot be easily tested on real systems. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that electrical utilities commonly use.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Improving Resilience of Bus Bunching Holding Strategy through a Rolling Horizon Approach

Providing public transportation with quality service is critical to attracting more passengers to the system. However, high-demand routes are prone to the so-called bus bunching -- a tendency of buses to group as a consequence of variations in travel times and demands. Bus holding is applied to overcome this effect. In this study, we present a novel method for bus holding in which the control law is based only on the buses' position using a computationally efficient rolling horizon approach. The method uses similar inputs as linear control approaches while not increasing significantly the computational time. However, the method overcomes key a weakness of the linear control approach thanks to the explicit constraint handling that always ensures the control action effectiveness. Simulation experiments in a validation case and a model-specific for a bus rapid transit line in Curitiba, Brazil showed a reduced holding time and improved resilience, delivering more than 20% reduction in delay time accounting for the on-board and station delays.

33 ADVANCED PROPULSION SYSTEMS↗

2004-2006 Puget Sound Traffic Choices Study

The 2004-2006 Puget Sound Traffic Choices Study tested the hypothesis that time-of-day variable road tolling in Seattle, Washington, could reduce traffic congestion and generate revenue. In 2002, the Puget Sound Regional Council received a grant from the Federal Highway Administration for a pilot project on congestion-based tolling. To test the hypothesis, the study placed global positioning system data loggers into the vehicles of about 275 households in the Seattle metropolitan area. The project recorded roughly 18 months of trip data (from November 2004 to April 2006) and included more than 400 vehicles. For most vehicles, the tolling influence experiment phase of the study began in July 2005 and lasted for 32 weeks. The three months immediately preceding the experiment period for each vehicle served as the control period.

1Hz data↗

Obfuscation for high-performance computing systems

An example method includes initializing, by an obfuscation computing system, communications with nodes in a distributed computing platform, the nodes including one or more compute nodes and a controller node, and performing at least one of: (a) code-level obfuscation for the distributed computing platform to obfuscate interactions between an external user computing system and the nodes, wherein performing the code-level obfuscation comprises obfuscating data associated with one or more commands provided by the user computing system and sending one or more obfuscated commands to at least one of the nodes in the distributed computing platform; or (b) system-level obfuscation for the distributed computing platform, wherein performing the system-level obfuscation comprises at least one of obfuscating system management tasks that are performed to manage the nodes or obfuscating network traffic data that is exchanged between the nodes.

97 MATHEMATICS AND COMPUTING↗