Network-Wide Measurements of TCP RTT in 3G

Romirer-Maierhofer, Peter; Ricciato, Fabio; D’Alconzo, Alessandro; Franzan, Robert; Karner, Wolfgang

doi:10.1007/978-3-642-01645-5_3

Cited by 34 publications

(19 citation statements)

References 6 publications

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“…For this dataset, we mark a "failure" event when the RTT exceeds a fixed threshold T -we set T = 0.5 sec and T = 1.5 sec respectively for UMTS/HSPA and GPRS/EDGE. For more details about the measurement setting see [3]. The rationale for extracting such measurements is that congestion in the downlink path towards the terminals (e.g.…”

Section: Numerical Results From Real Datasetsmentioning

confidence: 99%

Bayesian Estimation of Network-Wide Mean Failure Probability in 3G Cellular Networks

Coluccia

Ricciato

Romirer-Maierhofer

2011

Performance Evaluation of Computer and Communication Systems. Milestones and Future Challenges

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Abstract. Mobile users in cellular networks produce calls, initiate connections and send packets. Such events have a binary outcome -success or failure. The term "failure" is used here in a broad sense: it can take different meanings depending on the type of event, from packet loss or late delivery to call rejection. The Mean Failure Probability (MFP) provides a simple summary indicator of network-wide performance -i.e., a Key Performance Indicator (KPI) -that is an important input for the network operation process. However, the robust estimation of the MFP is not trivial. The most common approach is to take the ratio of the total number of failures to the total number of requests. Such simplistic approach suffers from the presence of heavy-users, and therefore does not work well when the distribution of traffic (i.e., requests) across users is heavy-tailed -a typical case in real networks. This motivates the exploration of more robust methods for MFP estimation. In a previous work [1] we derived a simple but robust sub-optimal estimator, called EPWR, based on the weighted average of individual (per-user) failure probabilities. In this follow-up work we tackle the problem from a different angle and formalize the problem following a Bayesian approach, deriving two variants of non-parametric optimal estimators. We apply these estimators to a real dataset collected from a real 3G network. Our results confirm the goodness of the proposed estimators and show that EPWR, despite its simplicity, yields near-optimum performance.

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Section: Numerical Results From Real Datasetsmentioning

confidence: 99%

Bayesian Estimation of Network-Wide Mean Failure Probability in 3G Cellular Networks

Coluccia

Ricciato

Romirer-Maierhofer

2011

Performance Evaluation of Computer and Communication Systems. Milestones and Future Challenges

Self Cite

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“…Table I summarizes the specifications of the SCP and the hard disk (these values determine the time to retrieve a disk page via the PIR interface, as detailed in [25]). The client communicates with the LBS using a link with round trip time of 700ms and bandwidth 384 Kbitls (i.e., 48 Kbyte/s) -this corresponds to a moving client connected via a 3G data network [19]. The average response time of a method is measured by running a workload of 1,000 shortest path queries.…”

Section: Methodsmentioning

confidence: 99%

Strong location privacy: A case study on shortest path queries

Mouratidis

2013

2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW)

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Ahstract-The last few years have witnessed an increasing availability of location-based services (LBSs). Although partic ularly useful, such services raise serious privacy concerns. For example, exposing to a (potentially untrusted) LBS the client's position may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc.There is a large body of work on protecting the location privacy of the clients. In this paper, we focus on shortest path queries, describe a framework based on private information retrieval (PIR), and conclude with open questions about the practicality of PIR and other location privacy approaches.

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“…Several studies focus on passive measurements from inside mobile carriers [7][8][9]. While important for debugging the infrastructure components of latency, the view from such locations does not necessarily indicate the performance on mobile devices.…”

Section: Related Workmentioning

confidence: 99%

“…This paper differs from previous related work in that our study is longitudinal, continuous, pervasive and gathered from mobile devices using controlled experiments. In contrast, some related work [7][8][9] passively collected network traffic from cellular network infrastructure, using one month of data or less. These studies tend to be limited to a single carrier, hampering our ability to conduct meaningful comparisons across carriers.…”

Section: Introductionmentioning

confidence: 99%

Mobile Network Performance from User Devices: A Longitudinal, Multidimensional Analysis

Nikravesh

Choffnes

Katz-Bassett

et al. 2014

Passive and Active Measurement

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Abstract. In the cellular environment, operators, researchers and end users have poor visibility into network performance for devices. Improving visibility is challenging because this performance depends factors that include carrier, access technology, signal strength, geographic location and time. Addressing this requires longitudinal, continuous and large-scale measurements from a diverse set of mobile devices and networks.This paper takes a first look at cellular network performance from this perspective, using 17 months of data collected from devices located throughout the world. We show that (i) there is significant variance in key performance metrics both within and across carriers; (ii) this variance is at best only partially explained by regional and time-of-day patterns; (iii) the stability of network performance varies substantially among carriers. Further, we use the dataset to diagnose the causes behind observed performance problems and identify additional measurements that will improve our ability to reason about mobile network behavior.

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Network-Wide Measurements of TCP RTT in 3G

Cited by 34 publications

References 6 publications

Bayesian Estimation of Network-Wide Mean Failure Probability in 3G Cellular Networks

Bayesian Estimation of Network-Wide Mean Failure Probability in 3G Cellular Networks

Strong location privacy: A case study on shortest path queries

Mobile Network Performance from User Devices: A Longitudinal, Multidimensional Analysis

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