TCP over CDMA2000 Networks: A Cross-Layer Measurement Study

Mattar, Karim; Sridharan, Ashwin; Zang, Hui; Matta, Ibrahim; Bestavros, Azer

doi:10.1007/978-3-540-71617-4_10

Cited by 16 publications

(12 citation statements)

References 15 publications

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“…In [6], the authors compare LTE and HSPA networks by conducting high precision latency measurements for an operator in Austria. In [16,4,17,18], authors studied the TCP performance in CDMA2000 networks. In [16], the authors investigate the steady-state TCP performance over CDMA 1x EV-DO downlink/uplink with the active measurement of long-lived TCP connections at the end-points for a Korean operator.…”

Section: Related Workmentioning

confidence: 99%

“…In [16], the authors investigate the steady-state TCP performance over CDMA 1x EV-DO downlink/uplink with the active measurement of long-lived TCP connections at the end-points for a Korean operator. [18,4] conducted a cross-layer measurement of transport, physical and MAC layer parameters. [18] characterizes the wireless scheduler in a commercial CDMA2000 network and its impact on TCP performance by performing end-to-end experiments and sending UDP and TCP packets.…”

Section: Related Workmentioning

confidence: 99%

“…[18,4] conducted a cross-layer measurement of transport, physical and MAC layer parameters. [18] characterizes the wireless scheduler in a commercial CDMA2000 network and its impact on TCP performance by performing end-to-end experiments and sending UDP and TCP packets.…”

Section: Related Workmentioning

confidence: 99%

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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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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

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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“…Several studies have examined spectrum usage and application characteristics in cellular data networks [4,5,6]. Much of this prior work uses small scale measurements taken from a few mobile clients.…”

Section: Introductionmentioning

confidence: 99%

Comparing and Contrasting Smartphone and Non-Smartphone Usage

Carolan

McLoone

Farrell

2013

24th IET Irish Signals and Systems Conference (ISSC 2013)

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_______________________________________________________________________________Abstract-This paper presents a large-scale network wide analysis of both user behaviour and network dynamics in a live nationwide 2G/3G network. The employed data set tracks over one million subscribers across upwards of ten thousand base stations covering the entirety of the Republic of Ireland. The data set was captured in 2011 and includes a large group of bill-pay and pre-pay smartphone subscribers. The proliferation of smartphones has been a major and recent change to networks worldwide. In light of the recent changes in network access technologies much of the earlier work in this field is now out of date. This paper compares and contrasts the traffic usage of smartphone subscribers and nonsmartphone subscribers. A key aim of this work is to quantify and qualify the change brought about by smartphones. Unlike previous studies, we look to the future by treating all traffic including voice calls and SMS as an equivalent data service, as will be the case in 4G. This paper also explores the temporal and spatial properties of both bill-pay and pre-pay smartphone usage and concludes by summarising our key findings & their implications.

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“…The set of data rates is obtained by choosing a combination of the RF control variables that produces the highest channel data rate under a particular channel condition 2 for a target FER. Similarly, scheduling policies typically assign the highest possible data rate allowed (for a given channel condition) from the set of given data rates that can clear the buffer backlog 3 (see [2] for a detailed characterization of this behavior). While ideal for inelastic constant rate applications, this resource allocation methodology can produce suboptimal performance of elastic applications and protocols, in particular TCP, that adapt their rate in response to feedback from the receiver.…”

Section: Introductionmentioning

confidence: 99%

TCP-Aware Channel Allocation in CDMA Networks

Ghaderi

Sridharan

Zang

et al. 2009

IEEE Trans. on Mobile Comput.

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Abstract-This paper explores the use of rate adaptation in cellular networks to maximize throughput of long-lived TCP sessions. Modern cellular networks incorporate RF technology that allows them to dynamically vary the wireless channel rate in response to user demands and channel conditions. However, the set of data rates as well as the scheduler's rate adaptation policy are typically chosen to maximize the throughput of inelastic connections. We focus on the problem of maximizing the throughput of TCP connections and propose a joint optimization of MAC and physical layer parameters with respect to TCP sending rate. In particular, we propose a simple TCP-aware channel scheduler that adapts the wireless channel rate to changes in the TCP sending rate and explore its performance for both single and multiple concurrent sessions. In the case of a single TCP session, we develop a fluid model of its steady-state behavior in such a system that adapts between two channel rates. The accuracy of the model, its utility in selecting optimal rates as well as the performance of systems with up to three channel rates are explored with ns-2 simulations. Our results indicate that a two-rate scheme improves TCP throughput by 15 to 20 percent over a system that does not exploit rate adaptation and that little additional benefit accrues from the addition of a third channel rate. Finally, we extend the framework to scenarios where bandwidth is shared by multiple TCP sessions. We propose two channel allocation algorithms, one relying on detailed TCP state information, the other not, and explore their performance through simulation. Our results indicate that TCP throughput is relatively insensitive to either channel allocation algorithm, and adaptive rate variation is the dominant factor in performance.

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TCP over CDMA2000 Networks: A Cross-Layer Measurement Study

Cited by 16 publications

References 15 publications

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

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

Comparing and Contrasting Smartphone and Non-Smartphone Usage

TCP-Aware Channel Allocation in CDMA Networks

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