Providing Grid Schedulers with Passive Network Measurements

Capacity estimation effective in an IP network path is a key enabling technology for proactive and reactive resource management as well as intelligent planning in next generation IP networks. We analyze capacity measurements at different Internet destinations. Particularly, we use the variable packet size (VPS) method to measure the per-hop capacity in some network paths. This method is based on round trip time (RTT) measurements as well as on the Internet control message protocol, ICMP. The RTT delay is approximated by a gamma distribution. We observe how the measurement accuracy of this active probing is affected by factors such as layer 2 device latencies, limited clock resolution at the probing host, or queuing delay. These factors cause non linearity on the RTT curves obtained and, consequently, inaccuracies on the estimation of path capacities. The use of robust regression to improve linear approximation in the VPS method is proposed. As a result, we obtain better qualitative and quantitative results.

Assigning jobs to optimum resources in a grid environment is the main aim of a grid scheduler. Communication cost has always been an important issue in grid environments. Proposing new scheduling algorithms to consider this cost accurately and allocate jobs to an optimum resource efficiently has always been of great importance. In this paper we have proposed a grid scheduling algorithm that is aware of the costs for different network paths. We have also considered soft real-time characteristics of jobs in our proposed algorithm. We have simulated and compared our algorithm with some key scheduling algorithms such as Least Load First (LLF), Random, and First Come First Served (FCFS) in Gridsim by considering soft real-time jobs. Results show the superiority of our scheduling algorithm due to its ability to predict network cost and to satisfy the demands of soft real-time tasks.

In recent years, privacy issues in the networking field are getting more important. In particular, there is a lively debate about how Internet Service Providers (ISPs) should collect and treat data coming from passive network measurements. This kind of information, such as flow records or HTTP logs, carries considerable knowledge from several points of view: traffic engineering, academic research, and web marketing can take advantage from passive network measurements on ISP customers. Nevertheless, in many cases collected measurements contain personal and confidential information about customers exposed to monitoring, thus raising several ethical issues. Modern web is very different from the one we experienced few years ago: web services converged to few protocols (i.e., HTTP and HTTPS) and a large share of traffic is encrypted. The aim of this work is to provide an insight about which information is still visible to ISPs, with particular attention to novel and emerging protocols, and to what extent it carries personal information. We illustrate that sensible information, such as website history, is still exposed to passive monitoring. We illustrate privacy and ethical issues deriving by the current situation and provide general guidelines and best practices to cope with the collection of network traffic measurements.

We propose a passive measurement methodology to infer and keep track of the values of two important variables associated with a TCP connection: the sender's congestion window (cwnd) and the connection round trip time (RTT). Together, these variables provide a valuable diagnostic of end-user-perceived network performance. Our methodology is validated via both simulation and concurrent active measurements, and is shown to be able to handle various flavors of TCP. Given our passive approach and measurement points within a Tier-1 network provider, we are able to analyze more than 10 million connections, with senders located in more than 45% of the autonomous systems in today's Internet. Our results indicate that sender throughput is frequently limited by a lack of data to send, that the TCP congestion control flavor often has minimal impact on throughput, and that the vast majority of connections do not experience significant variations in RTT during their lifetime

Cellular network operators are now expected to maintain a good Quality of Experience (QoE) for many services beyond circuit-switched voice and messaging. However, new smart-phone services, such as Over The Top (OTT) video delivery, are not under an operator's control. Furthermore, complex interactions between network protocol layers make it challenging for operators to understand how network-level parameters (e.g., inactivity timers, handover thresholds, middle boxes) will influence a specific app's QoE. This paper takes a first step to address these challenges by presenting a novel approach to estimate app QoE using passive network measurements. Our approach uses machine learning to obtain a function that relates passive measurements to an app's QoE. In contrast to previous approaches, our approach does not require any control over app services or domain knowledge about how an app's network traffic relates to QoE. We implemented our approach in Prometheus, a prototype system in a large U.S. cellular operator. We show with anonymous data that Prometheus can measure the QoE of real video-on-demand and VoIP apps with over 80% accuracy, which is close to or exceeds the accuracy of approaches suggested by domain experts.

Abstract. Modern mobile devices offer advanced capabilities for navigation and Location-Based Services (LBS). This study investigates the use of Ultra-Wideband (UWB) and Wi-Fi Round-Trip Time (RTT) measurements for pedestrian localization across various scenarios. We analyze the ranging accuracy of these techniques and evaluate positioning performance using different fusion algorithms. Our proposed collaborative positioning (CP) methodology enhances localization accuracy for user groups within a defined area. Results demonstrate significant improvements in position trueness, with UWB and Wi-Fi RTT achieving enhancements of 74% and 54%, respectively. Additionally, our localization algorithm, leveraging a Peer-to-Infrastructure (P2I) and Peer-to-Peer (P2P) hybrid configuration, increases anchor availability by up to 10%. Even in short-duration anchor loss scenarios (P2P-only), position trueness improves by up to 53%. These findings highlight the potential of UWB and Wi-Fi RTT in real-world pedestrian localization, particularly for urban navigation, smart mobility applications, and emergency response systems.

5G NR mm Wave promises accurate positioning down to the centimeter level. However, mmWave signals endure prismatic propagation, making them prone to signal blockages and non-line of sight (NLoS) communications. To achieve a precise positioning solution, it is rather essential to filter out NLoS gNBs as they yield erroneous pose estimation of IoT vehicular applications. Previous works have attempted to address this issue, however, they are either based on impractical or invalid assumptions about the operation scenario. In this paper, a novel, yet, simple and realistic NLoS detection algorithm is developed. The proposed method measures the discrepancy between Received Signal Strength (RSS)-based and time-based ranges as means to detect NLoS operation. To validate the proposed NLoS detection method, it was incorporated into a Kalman Filter (KF) that fuses the angle of departure (AoD) and round trip time (RTT) measurements from multiple gNBs in a loosely coupled fashion. The proposed method was evaluated on quasi-real measurements acquired from a highly validated 5G simulation tool that simulates the cores of downtown Toronto. The proposed method demonstrates superior results, as it sustains a sub-1m level of accuracy for around 95% of the time, as compared to merely 29% of the time without the NLoS detection.

This paper provides a preliminary investigation into the impact a link with changing propagation delay has on the performance of TCP file transfers. We investigate over a dozen different variable delay patterns, based on spacecraft movement. We highlight the performance impact of such variability, paying close attention to TCP's retransmission timer, which is based on the observed round-trip time of the network path. In addition, we explore one scenario in which the round-trip time across a network path suddenly changes due to a large change in the path between the two end-points. We conclude that the variable delay network paths studied in this paper do not drastically impact TCP performance.

This book constitutes the refereed proceedings of the 10th International Conference on Passive and Active Measurement, PAM 2009, held in Seoul, Korea, in April 2009. The 22 revised full papers and 2 revised demo papers presented were carefully reviewed and selected from 77 submissions. The papers focus on research and practical applications of routing and forwarding, topology and delay, methods for large-scale measurements, wireless, management tools, audio and video traffic, peer-to-peer, traffic measurements, and measurements of anomalous and unwanted traffic.

The General Packet Radio Service (GPRS) is being deployed by GSM network operators world-wide, and promises to provide users with “always-on” data access at bandwidths comparable to that of conventional fixed-wire telephone modems. However, many users have found the reality to be rather different, experiencing very disappointing performance when, for example, browsing the web over GPRS. In this paper, we examine the causes, and show how unfortunate interactions between the GPRS link characteristics and TCP/IP protocols lead to poor performance. A performance characterization of the GPRS link-layer is presented, determined through extensive measurements taken over production networks. We present measurements of packet loss rates, bandwidth availability, link stability, and roundtrip time. The effect these characteristics have on TCP behavior are examined, demonstrating how they can result in poor link utilization, excessive packet queueing, and slow recovery from packet losses. Further, we show that the HTTP protocol can compound these issues, leading to dire WWW performance. We go on to show how the use of a transparent proxy interposed near the wired-wireless border can be used to alleviate many of these performance issues without requiring changes to either client or server end systems.

The round-trip time and congestion window are the most important rate-controlling variables in TCP. We present a novel method for estimating these variables from passive traffic measurements. The method uses four different techniques to infer the minimum round-trip time based the pacing of a limited number of packets. We then estimate the sequence of congestion windows and round-trip times for the whole flow. We validate our algorithms with the ns2 network simulator.

Current grid technologies offer unlimited computational power and storage capacity for scientific research and business activities in heterogeneous areas over the world. Thanks to the grid, different virtual organizations can operate together in order to achieve common goals. However, concrete use cases demand a more close interaction between various types of instruments accessible from the grid, and the classical grid infrastructure, typically composed of computing and storage elements. We cope with this open problem by proposing and realizing the first release of the Instrument Element, i.e., a new grid component that provides the computational/data grid with an abstraction of real instruments, and grid users with a more interactive interface to control them. In this paper, we discuss in detail the proposed software architecture for this new component, then we report some performance results concerning its first prototype, and finally we present a pair of concrete use cases, which the Instrument Element has been successfully integrated with.

We propose the first practical solution to the longstanding problem of secure wireless routing in the presence of colluding attackers. Our secure routing protocol, Sprout, continuously tries new routes to the destination. Routes are probabilistically generated, with complete disregard for performance metrics. This makes Sprout uniquely resilient to attack: it cannot be tempted by shortcuts. In order to avoid compromised routes, and to ensure good overall performance, the quality of each active route is monitored by means of signed end-to-end acknowledgments. The amount of traffic sent on each route is adjusted accordingly. Sprout effectively mitigates the vast majority of known routing layer attacks, even when under assault from a large number of colluding attackers. Experiments on our 31-node testbed demonstrates the real-world performance of Sprout in terms of packet delivery ratio, round-trip times and TCP throughput. Our security analysis and simulation results show that Sprout is able to quickly find working paths in networks of hundreds of nodes and dozens or more attackers. For example, in a network of 200 nodes and an astounding 64 attackers, Sprout, on average, found a successful route within less than 10 attempts. Yet, in benign settings, Sprout provides TCP throughput within 15% of the shortest path throughput Overall, Sprout consistently delivers high, reliable performance in benign as well as hostile environments.

Google proposed a new TCP congestion control algorithm (CCA), Bottleneck Bandwidth and Round-trip propagation time (BBR) which has opened up new dimensions in congestion control. BBR tries to operate near Kleinrock's operating point to avoid excessive queue formation at the bottleneck and to use the link bandwidth optimally. BBR creates a model of the network path by measuring the bottleneck bandwidth and minimum round-trip time (RTT) to maximize the delivery rate and minimize latency. BBR v2 is an updated version of BBR which addresses many shortcomings of the original BBR (BBR v1) such as interprotocol fairness, RTT fairness, and excessive retransmissions. However, BBR v2 has certain limitations in its operation in IEEE 802.11ac (Wi-Fi 5) networks. The default BBR v2 limits the throughput of Wi-Fi 5 and an increased latency has been observed. This is because the Wi-Fi 5 frame aggregation logic is underutilized and fewer frames are being sent to the Wi-Fi 5 interface. In this paper, we have proposed BBR-n (BBR new) which provides better throughput than the generic BBR v2 in the Wi-Fi 5 networks. Real-time experiments were performed over a physical testbed using Flent to confirm that BBR-n achieves over double throughput as compared to generic BBR v2 and reduced latency in networks as compared to pure loss-based variants such as Cubic and Reno.

Google proposed a new congestion control algorithm (CCA) based on bottleneck bandwidth and round-trip propagation time (BBR), which is considered to open a new era of congestion control. BBR creates a network path model by measuring the available bottleneck bandwidth and the minimum round-trip time (RTT) to maximize delivery rate and minimize latency. The BBR v2 algorithm is a recently updated version by Google, which aims to improve some of the problems in the original BBR (BBRv1) algorithm, such as interprotocol fairness issues, RTT fairness issues, and excessive retransmissions. The BBRv2 evaluation results show that it can improve the coexistence with the loss_based algorithm and alleviate some of the shortcomings in BBRv1. However, when multiple BBRv2 flows enter the same link at different times, fair convergence cannot be achieved, and RTT fairness still exists. Based on these problems, we analyze the root cause and proposed an improved algorithm BBRv2+, which uses flow-aware explicit congestion notification (ECN) to quantify queue information and feedback on the accurate congestion degree. BBRv2+ algorithm can avoid blind window constraints and selectively mark packets so that different flows can converge to fairness. In the simulation experiment of Network Simulator 3 (NS3), the results show that the BBRv2+ algorithm can improve intraprotocol fairness and RTT fairness and ensure bandwidth utilization and interprotocol fairness.