Round Trip Time Research Articles

R-RDSP: Reliable and Rapidly Deployable Wireless Ad Hoc System for Post-Disaster Management over DDS

After natural disasters such as earthquakes, floods, or wars occur, cellular communication networks often sustain significant damage or become impaired. In these critical situations, first responders must coordinate with other rescue teams to communicate essential information to central command and survivors. To address this challenge, we have developed a reliable and rapidly deployable wireless ad hoc system for post-disaster management using Data Distribution Service (DDS) middleware, specifically RTI-DDS, named R-RDSP. The R-RDSP further enhances these metrics, achieving a 14.5% improvement in end-to-end delay and a 20.24% improvement in round-trip delay over the RDSP scheme. The R-RDSP system consists of three main modules: client, relay, and server. Each module connects to others via an ad hoc network, ensuring direct device-to-device communication without relying on existing infrastructure. The client module collects and sends the victim’s location and emergency messages. The relay modules forward these messages across the ad hoc networks, ensuring minimal delay and high reliability. Finally, the server module receives the messages, processes them, and coordinates the response. Leveraging RTI-DDS for reliable message distribution, the system demonstrates robust performance even under challenging network conditions.

Synchronization Between Kerr Cavity Solitons and Broad Laser Pulse Injection

The synchronization of a soliton frequency comb in a Kerr cavity with pulsed laser injection is studied numerically. The neutral delay differential equation is used to model the light dynamics in the cavity. This model allows for the investigation of both cases where the pulse repetition period is close to the cavity round-trip time and where the repetition period of the injection pulses is close to a rational fraction M/N of the round-trip time. It is demonstrated that solitons can exist in this latter case, provided that the injection pulses are of a higher amplitude, which is directly proportional to the number M. Furthermore, it is shown that the synchronization range of the solitons is also proportional to the number M. The solitons excited by pulses with a period slightly different from the M:N-resonance can be destabilized by the Andronov–Hopf bifurcation, which occurs when the injection level at the soliton position decreases to M times the injection amplitude corresponding to the saddle-node bifurcation in a model equation with uniform injection.

Optical pulse generation with programmable positions in an actively mode-locked optical cavity.

A novel, to our knowledge, approach for generating optical pulses with programmable positions in an actively mode-locked (AML) optical cavity is proposed and experimentally demonstrated. In the AML, active mode locking occurs when the cavity gain exceeds one, and the cavity round trip time equals integer multiples of the repetition period of the electrical driving signal. The generated optical pulses are present at the positions where the optical cavity operates at its maximum transmission points. By periodically controlling the cavity gain with the driving signal, the maximum transmission points can be manipulated using a periodic arbitrary waveform, allowing the positions of the generated optical pulses within one round trip time to be programmed. Thanks to the superposition of the circulating optical field within the optical cavity, the pulse width of the generated pulses can be greatly compressed. In a proof-of-concept experiment, optical pulses with programmable pulse numbers, pulse intervals, and pulse position distributions in one period are generated by programming the driving signals. Optical pulse compression is also successfully verified. Optical pulses with an approximate 34-ps pulse width, ultra-low pulse interval (about 200 ps), and linear positional distribution are achieved.

Multiple shock and acceleration processes of high-velocity flyers driven by the HEAVEN-I laser facility

The experiments of high-velocity flyer acceleration were performed on the HEAVEN-I KrF laser facility with a long-pulse duration (∼ 28 ns). Double-layered flyers consisting of polystyrene and aluminum films can be accelerated to more than 10 km/s measured by VISAR. The polystyrene layer is used as the ablative material, insulation layer, and shock wave regulator. Multiple shock and acceleration processes were observed by adjusting the thickness of the polystyrene layer. We simulated and analyzed the multiple shock processes driven by the long laser pulses and square pressure pulses. The results indicate that the reverberation processes can be induced by the alternating shock and rarefaction waves due to the wave–interface interactions. The reverberations in the Al layer can modulate the pressure evolution and the fine structure of flyer acceleration history. Similar processes in the polystyrene layer can lead to a secondary or multiple shock loading process when the driving pulse duration is several times longer than the shock round trip time in the double-layered flyer. Multiple accelerations can effectively enhance the final velocities in the experimental and simulation results. However, multiple accelerations involve more complex shock loading and unloading processes, and flyers are more prone to breakup compared with single acceleration.

Speed of Light in Hollow-Core Photonic Bandgap Fiber Approaching That in Vacuum.

A Fresnel mirror is introduced at a hollow-core photonic bandgap fiber end by fusion splicing a short single-mode fiber segment, to reflect the light backward to an optical frequency domain reflectometry. The backward Fresnel reflection is used as a probe light to achieve light speed measurement with a high resolution and a high signal-to-noise ratio. Thus, its group velocity is obtained with the round-trip time delay as well as the beat frequency at the reflection peak. Multiple Fresnel peaks are observed from 2180.00 Hz to 13,988.75 Hz, corresponding to fusion-spliced hollow-core fiber segments with different lengths from 0.2595 m to 1.6678 m, respectively. The speed of light in the air guidance is calculated at 2.9753 × 108 m/s, approaching that in vacuum, which is also in good agreement with 2.9672 × 108 m/s given by the numerical analysis with an uncertainty of 10-3. Our demonstration promises a key to hollow-core waveguide characterization for future wide-bandwidth and low-latency optical communication.

A Modified TCP BBR to Enable High Fairness in High-Speed Wireless Networks

Wireless networks, especially 5G and WiFi networks, have made great strides in increasing network bandwidth and coverage over the past decades. However, the mobility and channel conditions inherent to wireless networks have the potential to impair the performance of traditional Transmission Control Protocol (TCP) congestion control algorithms (CCAs). Google proposed a novel TCP CCA based on Bottleneck Bandwidth and Round-Trip propagation time (BBR), which is capable of achieving high transmission rates and low latency through the estimation of the available bottleneck capacity. Nevertheless, some studies have revealed that BBR exhibits deficiencies in fairness among flows with disparate Round-Trip Times (RTTs) and also displays inter-protocol unfairness. In high-speed wireless networks, ensuring fairness is of paramount importance to guarantee equitable bandwidth allocation among diverse traffic types and to enhance overall network utilization. To address this issue, this paper proposes a BBR–Pacing Gain (BBR–PG) algorithm. By deriving the pacing rate control model, the impact of pacing gain on BBR fairness is revealed. Adjusting the pacing gain according to the RTT can improve BBR’s performance. Simulations and real network experiments have shown that the BBR–PG algorithm retains the throughput advantages of the original BBR algorithm while significantly enhancing fairness. In our simulation experiments, RTT fairness and intra-protocol fairness were improved by 50% and 46%, respectively.

Performance Analysis and Prediction of 5G Round-Trip Time Based on the VMD-LSTM Method

With the increasing level of industrial informatization, massive industrial data require real-time and high-fidelity wireless transmission. Although some industrial wireless network protocols have been designed over the last few decades, most of them have limited coverage and narrow bandwidth. They cannot always ensure the certainty of information transmission, making it especially difficult to meet the requirements of low latency in industrial manufacturing fields. The 5G technology is characterized by a high transmission rate and low latency; therefore, it has good prospects in industrial applications. To apply 5G technology to factory environments with low latency requirements for data transmission, in this study, we analyze the statistical performance of the round-trip time (RTT) in a 5G-R15 communication system. The results indicate that the average value of 5G RTT is about 11 ms, which is less than the 25 ms of WIA-FA. We then consider 5G RTT data as a group of time series, utilizing the augmented Dickey–Fuller (ADF) test method to analyze the stability of the RTT data. We conclude that the RTT data are non-stationary. Therefore, firstly, the original 5G RTT series are subjected to first-order differencing to obtain differential sequences with stronger stationarity. Then, a time series analysis-based variational mode decomposition–long short-term memory (VMD-LSTM) method is proposed to separately predict each differential sequence. Finally, the predicted results are subjected to inverse difference to obtain the predicted value of 5G RTT, and a predictive error of 4.481% indicates that the method performs better than LSTM and other methods. The prediction results could be used to evaluate network performance based on business requirements, reduce the impact of instruction packet loss, and improve the robustness of control algorithms. The proposed early warning accuracy metrics for control issues can also be used to indicate when to retrain the model and to indicate the setting of the control cycle. The field of industrial control, especially in the manufacturing industry, which requires low latency, will benefit from this analysis. It should be noted that the above analysis and prediction methods are also applicable to the R16 and R17 versions.

An effective and efficient UAV leader selection scheme in swarm of UAVs

Therefore, this study aims to introduce a novel framework for leader and coordinator selection in a swarm of UAVs that may further reduce communication delay and increase the data transmission rate. The proposed reliable framework avoids single-point failure. We use an integrated greedy approach for leader selection using better channel gain, enhanced data transmission rate, and minimal round-trip delays as metrics. Furthermore, the UAV coordinator is selected based on the nearest distance. In addition, this study also proposes an efficient and iterative algorithm for the effective selection of UAV leaders and coordinators. The experimental results indicate that our proposed protocol minimizes delay by 20% and increases the data transmission rate by 102bps as compared with existing methods.

Analysis of SR-IOV in Docker containers using RTT measurements

Cloud computing, a central pillar of modern IT infrastructure, faces constant challenges in provisioning and optimizing network performance, specifically regarding low-latency communication. This study investigates the impact of Single Root I/O Virtualization (SR-IOV) as a critical Quality of Service (QoS) enabler in virtualized environments. Data plane innovative technologies for virtual servers, especially SR-IOV technology, emerged as a promising solution adopted in data centers. When combined with Peripheral Component Interconnect (PCI) Passthrough in Docker environments, SR-IOV promises significant network performance gains. Our rigorous experimental methodology demonstrates that integrating SR-IOV reduces Round-Trip Time (RTT) latency by up to 15 times compared to the traditional Linux based Bridge configuration used in Docker, without significant additional costs. This research is particularly relevant for system administrators, data center professionals, and network traffic engineers, providing them valuable information into optimizing communication in cloud computing environments. By addressing this critical gap in knowledge, our study serves as a practical guide for the effective implementation these emerging technologies for network virtualization. In terms of practical applicability, the results raise valuable insights into the performance and implications of implementing SR-IOV and PCI Passthrough in a Docker environment. As a result, more informed decisions are tailored to the specific requirements of different usage scenarios.

A lightweight RDMA connection protocol based on post-hoc confirmation

With the increasing scale and complexity of high-performance computing systems, the rising failure rate poses significant challenges for RDMA networks that aim for high bandwidth and low latency. RDMA networks require hardware-level end-to-end reliable data transmission services to avoid the high cost of software failure recovery. Tianhe HPC interconnection network adopts a NIC-based RDMA reliable connection protocol, RCP. RCP establishes a connection for each message that enters the NIC and releases it after the transmission is complete. However, this introduces an additional round-trip time RTT connection overhead for each message, which severely impacts the performance of networks dominated by short messages in high-performance computing systems. We have found that utilization of receiver-side connection resources has been consistently low because maintaining message-grained connections on the NIC results in rapid release of connections. Therefore, we propose a lightweight RDMA connection protocol based on post-hoc confirmation, PCP. PCP assumes the receiver has connection resources by default and eliminates the need for confirmation from the receiver before sending a message, thus reducing the connection overhead of almost all messages by one RTT. At the same time, PCP also includes mechanisms to address the special case where the receiver lacks connection resources. Evaluation results demonstrate that PCP significantly optimizes short messages and applications dominated by short messages. Moreover, PCP further reduces the usage of receiver-side connection resources. Additionally, PCP does not experience performance degradation even under large-scale heavy loads and severe endpoint congestion.

Adaptive control of networked control systems under DoS attacks

This research introduces a new adaptive control approach tailored for networked control systems, aimed at addressing the challenges of Denial of Service (DoS) attacks and round-trip time delays. Initially, a compensation mechanism based on estimated values is introduced to counter DoS attacks; subsequently, for round-trip time delay issues, a predictive delay compensation control strategy is designed. The proposed control strategy does not rely on the specific structure or a particular model of the system, but instead solely updates the controller using the system's input and output values. Moreover, we successfully demonstrate the bounded stability of the system using the direct Lyapunov method. Ultimately, the effectiveness and practicality of this method are confirmed through simulation results.

On the Integration of Standard Deviation and Clustering to Promote Scalable and Precise Wi-Fi Round-Trip Time Positioning

Recently, the use of fingerprinting has been proposed for positioning using the Wi-Fi RTT estimations gathered by IEEE 802.11mc devices. Wi-Fi RTT poses a challenge on scalability due to the location-specific traffic injected in the network, which may limit the data traffic transmissions of other Wi-Fi users. In this respect, fingerprinting has been regarded as a promising scalable technique, compared to multilateration. While coupling other metrics should bring relief to the system, reducing the number of APs to which RTT measurements are requested alleviates the burden in specific cells. But how far may we go? This paper assesses several methods aimed at reducing the Wi-Fi RTT overhead while preserving the precision of the calculated position. The use of the Wi-Fi RTT standard deviation is assessed for the first time, being especially useful when the number of RTT procedures is minimized. The application of clustering can also improve position estimates while leveraging bandwidth for other users’ purposes.

TCP BBR-n interplay with modern AQM in Wireless-N/AC networks: Quest for the golden pair.

Effective congestion control on the internet has been a problem since its inception. Transmission Control Protocol (TCP), being the most widely used transport layer protocol tries to mitigate it using a variety of congestion control algorithms. Cubic, Reno, and Bottleneck Bandwidth and Round-trip propagation time (BBR) are the most deployed congestion controls. BBR v2 is leading the congestion control race with its superior performance in terms of better throughput and lower latency. Furthermore, Active Queue Management (AQM) algorithms try to mitigate the congestion control at the network layer through active buffer control to avoid bufferbloat. The most efficient congestion control occurs when TCP and AQM work together. Indeed, it is the TCP-AQM algorithm "Golden pair" that can result in the most efficient performance. This paper proposes such a novel pair based on our previously tested and published BBR-n (BBR new) with the most effective of the modern AQMs, that completely gels together to provide lower latency in wireless networks based on Wireless N/AC. Real-time experiments were performed using Flent on our physical testbed with BBR-n and modern AQMs such as Fair Queuing (FQ), Constrained Delay (CoDel), Proportional Integral controller Enhanced (PIE), Common Applications Kept Enhanced (Cake) and Flow Queuing Controlled Delay (FQ_CoDel). Various tests done on our physical testbed helped us identify CAKE as the most optimum AQM that fits with our proposed BBR-n while providing optimum throughput and lower latency in 802.11N/AC-based wireless networks.

Comparative analysis of quantum two-way time transfer and quantum round-trip time transfer in consistent spatiotemporal settings

In this study, we conducted experiments using a single energy-time entangled biphoton source to compare the performance of quantum two-way time transfer (Q-TWTT) and quantum round-trip time transfer (Q-RTTT) under consistent spatiotemporal conditions. By conducting experiments with different fiber links of 11.3 km, 22.4 km, and 55.6 km, while ensuring uniform photon counts received by the single-photon detectors, we measured standard deviations (SDs) and stabilities of the time offsets. The measured SDs for Q-TWTT and Q-RTTT were 0.46 ps and 0.65 ps over the 11.3 km fiber, 1.14 ps and 1.3 ps over the 22.4 km fiber, 3.98 ps and 4.39 ps over the 55.6 km fiber, respectively. These results show good agreement with theoretical predictions, and the smaller SDs for Q-TWTT can be directly attributed to protocol-specific factors related to system symmetry. The long-term time stabilities of Q-TWTT and Q-RTTT were evaluated in terms of time deviation (TDEV). At an average time of 12680 s, the measured TDEVs were 0.49 ps and 0.63 ps for the 11.3 km fiber, 0.59 ps and 0.7 ps for the 22.4 km fiber, 1.01 ps and 1.36 ps for the 55.6 km fiber, respectively. The results validate that Q-TWTT exhibits superior time transfer performance compared to Q-RTTT, highlighting the advantages of Q-TWTT in practical applications.

Quantitative and Qualitative Analysis of Aircraft Round-Trip Times Using Phase Type Distributions

One of the major issues facing commercial airlines is the time that it takes to board passengers. Further, most airlines wish to increase the number of trips that an aircraft can make between two or more cities. Thus, reducing the overall boarding times by a few minutes will have a significant impact on the number of trips made by an aircraft, as well as enabling improvements in key measures such as the median and 75th and 95th percentiles. Looking at such measures other than the mean is critical as it is well known that the mean can under- or overestimate the performance of any model. While there is considerable literature on the study of strategies to decrease boarding times, the same cannot be said about the study of the boarding time given a particular strategy for boarding. Thus, the focus of this paper is to study analytically (using suitable stochastic models) and numerically the impact of reducing the average time on the key measures to help the system to plan accordingly. This is achieved using a well-known probability distribution, namely the phase type distribution, to model various events involved in the boarding process. Illustrative numerical results show a reduction in the percentile values when the average boarding times are decreased. Understanding the percentiles of the boarding times, as opposed to relying only on the average boarding times, will help management to adopt a better boarding strategy that in turn will lead to an increase in the number of trips that an aircraft can make.

Round-Trip Time Ranging to Wi-Fi Access Points Beats GNSS Localization

Wi-Fi round-trip time (RTT) ranging has proven successful in indoor localization. Here, it is shown to be useful outdoors as well—and more accurate than smartphone code-based GNSS when used near buildings with Wi-Fi access points (APs). A Bayesian grid with observation and transition models is used to update a probability distribution of the position of the user equipment (UE). The expected value (or the mode) of this probability distribution provides an estimate of the UE location. Localization of the UE using RTT ranging depends on knowing the locations of the Wi-Fi APs. Determining these positions from floor plans can be time-consuming, particularly when the APs may not be accessible (as is often the case in order to prevent unauthorized access to the network). An alternative is to invert the Bayesian grid method for locating the UE—which uses distance measurements from the UE to several APs with known position. In the inverted method we instead locate the AP using distance measurements from several known positions of the UE. In localization using RTT, at any given time, a decision has to be made as to which APs to range to, given that there is a cost associated with each “range probe” and that some APs may not respond. This can be problematic when the APs are not uniformly distributed. Without a suitable ranging strategy, one can enter a dead-end state where there is no response from any of the APs currently being ranged to. This is a particular concern when there are local clusters of APs that may “capture” the attention of the RTT app. To avoid this, a strategy is developed here that takes into account distance, signal strength, time since last “seen”, and the distribution of the directions to APs from the UE—plus a random contribution. We demonstrate the method in a situation where there are no line-of-sight (LOS) connections and where the APs are inaccessible. The localization accuracy achieved exceeds that of the smartphone code-based GNSS.

Development, deployment and scaling of operating room-ready artificial intelligence for real-time surgical decision support

Deep learning for computer vision can be leveraged for interpreting surgical scenes and providing surgeons with real-time guidance to avoid complications. However, neither generalizability nor scalability of computer-vision-based surgical guidance systems have been demonstrated, especially to geographic locations that lack hardware and infrastructure necessary for real-time inference. We propose a new equipment-agnostic framework for real-time use in operating suites. Using laparoscopic cholecystectomy and semantic segmentation models for predicting safe/dangerous (“Go”/”No-Go”) zones of dissection as an example use case, this study aimed to develop and test the performance of a novel data pipeline linked to a web-platform that enables real-time deployment from any edge device. To test this infrastructure and demonstrate its scalability and generalizability, lightweight U-Net and SegFormer models were trained on annotated frames from a large and diverse multicenter dataset from 136 institutions, and then tested on a separate prospectively collected dataset. A web-platform was created to enable real-time inference on any surgical video stream, and performance was tested on and optimized for a range of network speeds. The U-Net and SegFormer models respectively achieved mean Dice scores of 57% and 60%, precision 45% and 53%, and recall 82% and 75% for predicting the Go zone, and mean Dice scores of 76% and 76%, precision 68% and 68%, and recall 92% and 92% for predicting the No-Go zone. After optimization of the client-server interaction over the network, we deliver a prediction stream of at least 60 fps and with a maximum round-trip delay of 70 ms for speeds above 8 Mbps. Clinical deployment of machine learning models for surgical guidance is feasible and cost-effective using a generalizable, scalable and equipment-agnostic framework that lacks dependency on hardware with high computing performance or ultra-fast internet connection speed.

Long Round-Trip Time Delay Effects on Performance of a Simulated Appendectomy Task.

INTRODUCTION: No current astronauts have surgical training, and medical capabilities for future missions do not account for it. We sought to determine the effect of communication delays and text-based communication on emergency medicine physician (EMP) performance of a simulated surgical procedure and the ideal training paradigm for remote surgery.METHODS: In this study, 12 EMPs performed an appendectomy on a virtual reality laparoscopic simulator after tutorial. EMPs were randomized into two groups: one (bedside) group performing with bedside directing from a surgeon and the second (remote) group performing with text-based communications relayed to the surgeon after a 210-s time delay. Both groups performed a second simulated surgery 7 mo later with 240-s delay. Collected data included time to completion, number of movements, path length, economy of motion, percentage of time with appropriate camera positioning, texts sent, and major complications.RESULTS: The remote group took significantly longer to complete the task, used more total movements, had longer path length, and had significantly worse economy of motion during the initial trial. At the 7-mo simulation, there were no significant differences between the two groups. There was a nonsignificant increase in critical errors in the remote group at follow-up (50% vs. 20% of trials).DISCUSSION: EMPs are technically able to perform a surgical operation with delayed just-in-time telementoring guidance via text-based communication. However, the ideal paradigm for training non-surgeons to perform surgical operations is unclear but is likely real-time bedside training rather than remote training.Kamine TH, Siu M, Stegemann S, Formanek A, Levin D. Long round-trip time delay effects on performance of a simulated appendectomy task. Aerosp Med Hum Perform. 2024; 95(9):703-708.

Horizontally Scalable Implementation of a Distributed DBMS Delivering Causal Consistency via the Actor Model

Causal Consistency has been proven to be the strongest type of consistency that can be achieved in a fault-tolerant, distributed system. This paper describes an implementation of D-Thespis, which is an approach that employs the actor mathematical model of concurrent computation to establish a distributed middleware that enforces causal consistency on a widely used relational database management system (RDBMS). D-Thespis prioritises developer experience by encapsulating the intricacies of causal consistency behind an interface that is accessible over standard REST protocol. Here, we discuss several novel results. Firstly, we define a method that builds a causally consistent DBMS supporting elastic horizontal scalability. Secondly, we deliver a cloud-native implementation of the middleware and provide results and insights on 6804 benchmark configurations executed on our implementation while running on a public cloud infrastructure across several data centres. The evaluation concerns transaction processing performance, an evaluation of our implementation’s update visibility latency, and a memory profiling exercise. The results of our evaluation show that under a transactional workload, a single-node installation of our implementation of D-Thespis is 1.5 times faster than a relational DBMS running serialisable transaction processing, while the performance of the middleware can improve by more than three times when scaled horizontally within the same data centre. Our study of the memory profile of the D-Thespis implementation shows that the system distributes its memory requirements evenly across all the available machines, as it is scaled horizontally. Finally, we also illustrate how our middleware propagates data changes across geographically-distributed infrastructures in a timely manner: our tests show that most of the effects of data change operations in one data centre are available in a remote data centre within less than 300 ms over and above the network round trip latency between the two data centres.

DIS-Guard: Enhancing SDN resilience to topology and RCO attacks

SDN controllers employ discovery protocols with LLDP packets to discover the network topology; however, this approach is susceptible to topology attacks due to the static reuse of LLDP packets without proper origin verification or integrity checks. This paper proposes a novel form of topology attack called the Round-trip time Confusion Onslaught (RCO) attack. Our findings showcase the capability of the RCO attack to mislead the discovery service of SDN controllers and bypass the Real-time Link Verification (RLV) defence mechanism, which depends on timing features in Machine Learning (ML) models. The RCO attack significantly reduces the effectiveness of the RLV mechanism in terms of True Positive Rate (TPR), Precision, F1-score, and Cohen’s Kappa and increases the False Positive Rate (FPR). These results underscore the difficulties in achieving dependable ML accuracy in topology attack detection. Accordingly, we propose the DIS-Guard framework, designed to protect and improve the efficiency of discovery protocols within SDN controllers. This framework utilizes the mutual Transport Layer Security (mTLS) protocol to discover hosts proactively. Moreover, it employs a novel combination of a chaos-tent map and the proposed statistical method for link discovery. Through extensive evaluation, we illustrate DIS-Guard’s superior performance and security over the established Ryu (switches.py) controller and the RLV defence mechanism. Notably, DIS-Guard reduces host-to-host access delays, decreases LLDP packet transmission and reception significantly, and improves control channel efficiency. Collectively, these quantifiable benefits manifest the efficacy of DIS-Guard as a significantly optimized solution for SDN security and performance.