Variations In Network Performance Research Articles

5G enabled smart cities: A real-world evaluation and analysis of 5G using a pilot smart city application

Ubiquitous sensing in smart cities is expected to be one of the key beneficiaries of the high bandwidth and low latency capabilities of 5G. However, current 5G deployments still have low population coverage, and are unlikely to reach global coverage of above 80% before 2028. This means that new smart city applications are likely to experience a combination of 4G and 5G, limiting their data-intensive capabilities. Thus, it is necessary to assess the ability of current 5G deployments to support emerging smart city applications, and how they perform in 5G environments. Existing performance evaluations focus either on the 5G core or use instantaneous speed tests, which do not effectively assess the suitability of 5G deployments for smart city applications. In this paper, we present a comprehensive evaluation and analysis of real-world 5G network performance observed through the outcomes of a pilot smart city application, an innovative mobile 5G Internet of Things (IoT) solution to automatically identify and report road assets requiring maintenance. The pilot smart city application was deployed on 11 waste collection service trucks over a 6 month period (June 2022–Dec 2022). We undertook both application-specific and application independent network performance evaluation to assess the ability of the 5G deployment to support uninterrupted smart city services. Our analysis shows that while 5G is capable of supporting mobile video streaming applications, there are significant variations in network performance, which may make it unsuitable for applications that require higher data intensive or near real-time responsiveness.

RURAL TELESURGERY NETWORK CHARACTERIZATION FOR FUTURE REMOTE CARDIAC CATHETER ABLATION

BackgroundTelesurgery involves a remote surgeon operating on a patient over distance using the internet to control a surgical robot. Telesurgery could allow rural patients more equitable access to lifesaving specialty procedures such as cardiac catheter ablation. Advances in telehealth adoption and surgical robotics are lowering the conceptual and technical hurdles for this future method of healthcare delivery. Despite this, important questions remain regarding the safe implementation of telesurgery in rural community hospitals. In particular, it is critical to understand the spatial, temporal, and content dependent variations in network performance between urban and rural hospitals. Presently, no one has meaningfully characterized internet performance for telesurgical procedures in rural areas.ObjectiveThe purpose of this research is to measure real-world internet performance and characterize the risk and severity of network disruptions during simulated telesurgeries between urban and rural hospitals over a long duration.MethodsWe developed a python application to generate and receive simulated telesurgery data between an urban center and small servers that are physically located in rural hospital operating rooms (Figure 1). Simulated telesurgeries were performed daily and nightly for 90min at approximately 2 packets per second.ResultsThe packet latency distribution for 108 simulated surgeries (54 daytime; 54 nighttime) is shown in Figure 2. We found that 99.99% of the packets had a network latency of less than 250ms and only 10% of operations had at one or more packets delayed by 250ms or more.ConclusionFigure 2. Network latency vs. percent of packets for all simulated telesurgeriesView Large Image Figure ViewerDownload Hi-res image Download (PPT) BackgroundTelesurgery involves a remote surgeon operating on a patient over distance using the internet to control a surgical robot. Telesurgery could allow rural patients more equitable access to lifesaving specialty procedures such as cardiac catheter ablation. Advances in telehealth adoption and surgical robotics are lowering the conceptual and technical hurdles for this future method of healthcare delivery. Despite this, important questions remain regarding the safe implementation of telesurgery in rural community hospitals. In particular, it is critical to understand the spatial, temporal, and content dependent variations in network performance between urban and rural hospitals. Presently, no one has meaningfully characterized internet performance for telesurgical procedures in rural areas. Telesurgery involves a remote surgeon operating on a patient over distance using the internet to control a surgical robot. Telesurgery could allow rural patients more equitable access to lifesaving specialty procedures such as cardiac catheter ablation. Advances in telehealth adoption and surgical robotics are lowering the conceptual and technical hurdles for this future method of healthcare delivery. Despite this, important questions remain regarding the safe implementation of telesurgery in rural community hospitals. In particular, it is critical to understand the spatial, temporal, and content dependent variations in network performance between urban and rural hospitals. Presently, no one has meaningfully characterized internet performance for telesurgical procedures in rural areas. ObjectiveThe purpose of this research is to measure real-world internet performance and characterize the risk and severity of network disruptions during simulated telesurgeries between urban and rural hospitals over a long duration. The purpose of this research is to measure real-world internet performance and characterize the risk and severity of network disruptions during simulated telesurgeries between urban and rural hospitals over a long duration. MethodsWe developed a python application to generate and receive simulated telesurgery data between an urban center and small servers that are physically located in rural hospital operating rooms (Figure 1). Simulated telesurgeries were performed daily and nightly for 90min at approximately 2 packets per second. We developed a python application to generate and receive simulated telesurgery data between an urban center and small servers that are physically located in rural hospital operating rooms (Figure 1). Simulated telesurgeries were performed daily and nightly for 90min at approximately 2 packets per second. ResultsThe packet latency distribution for 108 simulated surgeries (54 daytime; 54 nighttime) is shown in Figure 2. We found that 99.99% of the packets had a network latency of less than 250ms and only 10% of operations had at one or more packets delayed by 250ms or more. The packet latency distribution for 108 simulated surgeries (54 daytime; 54 nighttime) is shown in Figure 2. We found that 99.99% of the packets had a network latency of less than 250ms and only 10% of operations had at one or more packets delayed by 250ms or more. Conclusion

Data-Driven Construction of User Utility Functions from Radio Connection Traces in LTE

In recent years, the number of services in mobile networks has increased exponentially. This increase has forced operators to change their network management processes to ensure an adequate Quality of Experience (QoE). A key component in QoE management is the availability of a precise QoE model for every service that reflects the impact of network performance variations on the end-user experience. In this work, an automatic method is presented for deriving Quality-of-Service (QoS) thresholds in analytical QoE models of several services from radio connection traces collected in an Long Term Evolution (LTE) network. Such QoS thresholds reflect the minimum connection performance below which a user gives up its connection. The proposed method relies on the fact that user experience influences the traffic volume requested by users. Method assessment is performed with real connection traces taken from live LTE networks. Results confirm that packet delay or user throughput are critical factors for user experience in the analyzed services.

Analysis of Transportation Network Vulnerability and Resilience within an Urban Agglomeration: Case Study of the Greater Bay Area, China

Recently, urban agglomerations have become the main platform of China’s economic development. As one of those, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has an important strategic position in national blueprints. Its amazing achievement is inseparable from reliable and resilient transportation networks. With the aim of improving the sustainability of the GBA, this paper presents a novel view of vulnerability and resilience of integrated transportation networks within an urban agglomeration. According to complex network theory, the integrated transportation network model of the GBA was established. Various scenarios were considered to improve the overall level of defensive ability, including random failures, targeted attacks and natural hazards. Vulnerability and resilience assessment models were developed to investigate the influences on the whole network. Finally, a simulation analysis was conducted on the GBA to examine the variations in network performance when faced with different attack scenarios. The results indicate that the transportation network of the GBA is more vulnerable and has less resilience to targeted attacks, while natural hazards had little influence on the performance, to a certain extent. Moreover, the betweenness recovery strategy seemed to be the best choice for every attack scenario.

Investigation and optimization method for wireless AP deployment based indoor network

In indoor communication, when handling the design issue for the wireless network, it is very important to select the appropriate wireless Access Point (AP) devices and specify the optimum locations for these devices deployment. In addition, reducing the total number of disseminated devices. In this paper, it has been investigating the network performance on the presidency building of middle technical university and based on AP deployment in the targeted building. Such investigation has been achieved using Wireless InSite software, based on the calculation of the parameters of path loss, and received power. Results obtained show significant variation in network performance and coverage at a different part of the building. As a result, a significant contribution has been proposed in enhancing the network performance, reducing the number of utilized AP devices from 13 to 8 devices. Furthermore, reducing both the total implementation costs and the interference effects inside the building.

Time-Aware VMFlow Placement, Routing, and Migration for Power Efficiency in Data Centers

Increased power usage and network performance variation due to best-effort bandwidth sharing significantly affect tenancy cost, cloud adoption, and data center efficiencies. In this paper, we propose a novel time-aware request model which enables tenants to specify an estimated required time-duration, in addition to their required server resources for Virtual Machines (VMs) and network bandwidth for their communication. We investigate the VM-placement and routing problem, which allocates both server and network resources for the specified time-duration, to provide resource guarantees. Further, we exploit VM-migration while considering its power consumption overhead, to improve power saving and resource utilization. Using the multi-component utilization-based power model, we formulate the problem as an optimization problem that maximizes the acceptance rate while consuming as low power as possible. We develop fast online heuristics that allocate resources for requests, considering their duration and bandwidth demand. We also develop migration policies augmenting these heuristics. For migration heuristics, we propose server-migration and switch-migration approaches, which migrate the VMs between the powered-on servers only if their migrations result in turning-off at least one server and switch, respectively. We demonstrate the effectiveness of the proposed heuristics in terms of power saving, acceptance ratio, and migration overhead using comprehensive simulation results.

Improvements on Lightning Density Estimation Based on Analysis of Lightning Location System Performance Parameters: Brazilian Case

Density maps are one of the most common and powerful lightning data applications, and they are more efficient the more detailed they are. When working with CG lightning data from lightning location systems, some aspects must be included in the analysis to overcome network performance variations. Two parameters are typically used to evaluate system performance: detection efficiency (DE) and location accuracy (LA).For the Brazilian National Integrated Lightning Detection Network, DE is typically evaluated by models, and LA is analyzed through confidence ellipses. This paper presents climatological analysis of lightning activity, including the most recent relative DE model developed in Brazil, as well as an adapted kernel smoothing method based on confidence ellipses [called Gaussian kernel based on confidence ellipses (GKBCE)] as approaches to minimize and/or include the spatial variation of the system's performance in the analysis. The maps are produced over the central-south portion of Brazil (mainly along ITAIPU power transmission lines), using 11 years of data available from the network (from January 1999 to December 2009). The model increased density by ~20% over the entire region, without making considerable changes to the spatial pattern. The GKBCE seems to work well in smoothing, obtaining better results than the standard cell count (quadrat) method, by working independently of the grid size (allowing the creation of high-resolution maps), and by including location errors in the analysis. The use of these procedures might result in more detailed maps and more suitable results when analyzing lightning data.

Methods to Overcome Lightning Location System Performance Limitations on Spatial and Temporal Analysis: Brazilian Case

Abstract One of the most interesting attributes of Lightning Location Systems (LLSs) data is that they can be analyzed in several ways according to the objectives of the study. However, the quality of the data is governed by the system performance and has some limitations when analyzed at different temporal/spatial scales, and these limitations will depend on the analysis method. This work focuses on approaches to minimize the variations associated with LLS performance. In this way, specific network configurations for the Brazilian Lightning Detection Network (BLDN) were obtained through the reprocessing of selected sensor data, resulting in three distinct datasets. Each dataset was then evaluated using different procedures: trimmed flash (exclusion of low current discharges), thunderstorm days (TDs), and thunderstorm hours (THs). The comparison between TDs obtained from the LLS and TDs available from surface stations shows consistent results with a good correlation of those datasets. An 11-yr analysis of BLDN data also shows that improvement (over time) of the system sensitivity has led to the detection of an increasing number of low peak current events. By eliminating low peak current discharges (less than 19 kA), the sensitivity variation was significantly reduced, partially “normalizing” long-term performance. TDs and THs were the most effective method to normalize temporal variations of the lightning activity, overcoming most of the network performance variations. From the spatial perspective, TDs and THs also seem to produce the most reliable lightning distribution. These results might guide long-term temporal and spatial analysis of lightning data, providing a more stable approach that is independent of system performance.

Analysis and practical guideline of constraint-based boolean method in genetic network inference.

Boolean-based method, despite of its simplicity, would be a more attractive approach for inferring a network from high-throughput expression data if its effectiveness has not been limited by high false positive prediction. In this study, we explored factors that could simply be adjusted to improve the accuracy of inferring networks. Our work focused on the analysis of the effects of discretisation methods, biological constraints, and stringency of Boolean function assignment on the performance of Boolean network, including accuracy, precision, specificity and sensitivity, using three sets of microarray time-series data. The study showed that biological constraints have pivotal influence on the network performance over the other factors. It can reduce the variation in network performance resulting from the arbitrary selection of discretisation methods and stringency settings. We also presented the master Boolean network as an approach to establish the unique solution for Boolean analysis. The information acquired from the analysis was summarised and deployed as a general guideline for an efficient use of Boolean-based method in the network inference. In the end, we provided an example of the use of such a guideline in the study of Arabidopsis circadian clock genetic network from which much interesting biological information can be inferred.

A network performance sensitivity metric for parallel applications

Excessive run time variability of parallel application codes on commodity clusters is a significant challenge. To gain insight into this problem, our earlier work developed tools to emulate parallel applications (PACE) by simulating computation and using the cluster's interconnection network for communication, and further study parallel application run time sensitivity effects to controlled network performance degradation (PARSE). This work expands our previous efforts by presenting a metric derived from PARSE test results conducted on several widely used parallel benchmarks and application code fragments. The metric suggests that a parallel application's sensitivity to network performance variation can be quantified relative to its behaviour in optimal network performance conditions. Ideas on how this metric can be useful to parallel application development, cluster system performance management and system administration are also presented.

An Anticipative Recursively Adjusting Mechanism for parallel file transfer in data grids

AbstractData Grids enable the sharing, selection, and connection of a wide variety of geographically distributed computational and storage resources for content needed by large‐scale data‐intensive applications such as high‐energy physics, bioinformatics, and virtual astrophysical observatories. In Data Grids, co‐allocation architectures were developed to enable parallel downloads of data sets from selected replica servers. As Internet is usually the underlying network of a grid, network bandwidth plays as the main factor affecting file transfers between clients and servers. In this paradigm, there are still some challenges that need to be solved, such as to reduce differences in finish times between selected replica servers, to avoid traffic congestion resulting from transferring the same blocks in different links among servers and clients, and to manage network performance variations among parallel transfers. In this paper, we propose the Anticipative Recursively Adjusting Mechanism (ARAM) scheme to adjust the workloads on selected replica servers and handle unpredictable variations in network performance by those servers. Our algorithm is based on using the finish rates for previously assigned transfers to anticipate the bandwidth status for the next section to adjust workloads, and to reduce file transfer times in grid environments. Our approach is useful in grid environments with unstable network link. It not only reduces idle time wasted waiting for the slowest server, but also decreases file transfer completion times. Copyright © 2010 John Wiley & Sons, Ltd.

The role of continuous monitoring in a 24/7 telecardiology consultation service—a feasibility study

Today's coronary care unit patients include those with complicated and uncomplicated myocardial infarction, decompensated heart failure and frank cardiogenic shock, severe valvular heart disease, high-grade conduction disturbances, and incessant ventricular arrhythmias. Increasingly in modern medicine, these conditions are not seen in isolation but rather in connection with a series of additional medical comorbidities. Increased life expectancy results in an increase in the prevalence of chronic cardiovascular diseases and an increased demand for health care services. Telemedicine is the provision of health care services, through the use of information and communication technology, in situations where the health care professional and the patient, or 2 health care professionals, are not in the same location. It involves the secure transmission of medical data and information, through text, sound, images, or other forms needed for the prevention, diagnosis, treatment, and follow-up of a patient. Telecardiology is one of the oldest applications in telemedicine and has been largely applied during the last 10 to 20 years. This study evaluated the feasibility of remote surveillance of coronary care unit and cardiology ward patient monitoring data by a “telecardiologist” with access to electronic health care record data and digitally stored 12-lead electrocardiograms. The remote access to the hospital intranet proved to be technically feasible. Also, the server applications used over the remote connection proved to be reliable and showed robustness against network performance variations. Extending remote patient surveillance to other hospitals is possible, provided that similar electrocardiogram and electronic health care record applications are available and a remote access can be arranged to them. However, the usability from cardiologist's perspective may be degraded if connecting with multiple applications and hospital networks is needed. The study indicated potential for speeding up the diagnostic and therapeutic processes in the hospital, although the study was limited in that the telecardiologist played a passive role and did not acutely impact patient care. In the future, the system could be expanded to surveillance of smaller hospitals. Telemedicine has the potential to aid in solving the conflict between aging of population, rise in the demand for critical care services, and shortage of professional personnel. This might, however, require a more active remote surveillance than the one tested in this study. Privacy- and security-related aspects are major components of building trust and confidence in telemedicine systems. In telecardiology, the real-time interactive telemedicine model with 24/7 service has potential superior performance compared with a store-and-forward telemedicine model.

Networked Control Systems: From Independent Designs of the Network QoS and the Control to the Co-design

Taking a network QoS designer's point of view, this paper firstly reviews some of the recent advances on the NCS (Networked Control Systems) design then analyzes its requirements in terms of network QoS guarantees and its capacity to tolerate network performance variation. Current deterministic QoS design approach (including traffic schedulability analysis) may lead to network resource over-provisioning problem since worst-case scenario is often dictated to network QoS designers by the control application. We show that integrated control and network QoS co-design consists in a better solution to this problem. Taking into account the current available results, we see that more research efforts remain to do on control and network QoS co-design and on the development of on-line adaptive QoS mechanisms.

SPADES a system for parallel-agent, discrete-event simulation

Simulations are an excellent tool for studying AI. However, the simulation technology in use by, and designed for, the AI community often fails to take advantage of much of the work in the larger simulation community to produce stable, repeatable, and efficient simulations. I present SPADES (SYSTEM FOR PARALLEL-AGENT DISCRETE-EVENT SIMULATION) as a simulation substrate for the AI community. SPADES focuses on the agent as a fundamental simulation component. The thinking time of an agent is tracked and reflected in the results of the agents' actions. SPADES supports and manages the distribution of agents across machines while it is robust to variations in network performance and machine load. SPADES is not tied to any particular simulation and is a powerful new tool for creating simulations for the study of AI.

Block-cyclic redistribution over heterogeneous networks

Clusters of workstations and networked parallel computing systems are emerging as promising computational platforms for HPC applications. The processors in such systems are typically interconnected by a collection of heterogeneous networks such as Ethernet, ATM, and FDDI, among others. In this paper, we develop techniques to perform block-cyclic redistribution over P processors interconnected by such a collection of heterogeneous networks. We represent the communication scheduling problem using a timing diagram formalism. Here, each interprocessor communication event is represented by a rectangle whose height denotes the time to perform this event over the heterogeneous network. The communication scheduling problem is then one of appropriately positioning the rectangles so as to minimize the completion time of all the communication events. For the important case where the block size changes by a factor of K, we develop a heuristic algorithm whose completion time is at most twice the optimal. The running time of the heuristic is \mathrm{O}(PK^2). Our heuristic algorithm is adaptive to variations in network performance, and derives schedules at run-time, based on current information about the available network bandwidth. Our experimental results show that our schedules always have communication times that are very close to optimal.

A framework based approach to the development of network aware applications

Modern networks provide a QoS (quality of service) model to go beyond best-effort services, but current QoS models are oriented towards low-level network parameters (e.g., bandwidth, latency, jitter). Application developers, on the other hand, are interested in quality models that are meaningful to the end-user and, therefore, struggle to bridge the gap between network and application QoS models. Examples of application quality models are response time, predictability or a budget (for transmission costs). Applications that can deal with changes in the network environment are called network-aware. A network-aware application attempts to adjust its resource demands in response to network performance variations. This paper presents a framework-based approach to the construction of network-aware programs. At the core of the framework is a feedback loop that controls the adjustment of the application to network properties. The framework provides the skeleton to address two fundamental challenges for the construction of network-aware applications: how to find out about dynamic changes in network service quality; and how to map application-centric quality measures (e.g., predictability) to network-centric quality measures (e.g., QoS models that focus on bandwidth or latency). Our preliminary experience with a prototype network-aware image retrieval system demonstrates the feasibility of our approach. The prototype illustrates that there is more to network-awareness than just taking network resources and protocols into account and raises questions that need to be addressed (from a software engineering point of view) to make a general approach to network-aware applications useful.