LTE 4G is the next generation of cellular network which specifically aims to improve the network performance for data traffic and is currently being rolled out by many network operators. We present results from an extensive LTE measurement campaign in Dublin, Ireland using a custom performance measurement tool. Performance data was measured at a variety of locations within the city (including cell edge locations, indoors, outdoors etc) as well as for mobile users on public transport within the city. Using this data we derive a model of the characteristics of link layer RTT and bandwidth vs link signal strength. This model is suited to use for performance evaluation of applications and services, and since it is based on real measurements it allows realistic evaluation of performance.
A number of other studies measure throughput and or latency information, but tend to focus on their impact on TCP or its derivatives @cite_19 @cite_14 @cite_6 @cite_8 @cite_11 @cite_5 @cite_12 . Additionally, there are studies that present measurements but do not use these to develop a model suited to performance evaluation @cite_18 .
@cite_18 @cite_14 @cite_8 @cite_6 @cite_19 @cite_5 @cite_12 @cite_11
2065831914 1964476812 2153757920 2153771889 2051619378 2147201699 2172200121
Over the past two or three years, wireless cellular networks have become faster than before, most notably due to the deployment of LTE, HSPA+, and other similar networks. LTE throughputs can reach many megabits per second and can even rival WiFi throughputs in some locations. This paper addresses a fundamental question confronting transport and application-layer protocol designers: which network should an application use? WiFi, LTE, or Multi-Path TCP (MPTCP) running over both? We compare LTE and WiFi for transfers of different sizes along both directions (i.e. the uplink and the downlink) using a crowd-sourced mobile application run by 750 users over 180 days in 16 different countries. We find that LTE outperforms WiFi 40 of the time, which is a higher fraction than one might expect at first sight. We measure flow-level MPTCP performance and compare it with the performance of TCP running over exclusively WiFi or LTE in 20 different locations across 7 cities in the United States. For short flows, we find that MPTCP performs worse than regular TCP running over the faster link; further, selecting the correct network for the primary subflow in MPTCP is critical in achieving good performance. For long flows, however, selecting the proper MPTCP congestion control algorithm is equally important. To complement our flow-level analysis, we analyze the traffic patterns of several mobile apps, finding that apps can be categorized as "short-flow dominated" or "long-flow dominated". We then record and replay these patterns over emulated WiFi and LTE links. We find that application performance has a similar dependence on the choice of networks as flow-level performance: an application dominated by short flows sees little gain from MPTCP, while an application with longer flows can benefit much more from MPTCP --- if the application can pick the right network for the primary subflow and the right choice of MPTCP congestion control. This paper investigates the interactions between two-way TCP connections over 3GPP LTE networks. In the LTE network, the two-way TCP flows share buffers on a common bottleneck, i.e., the radio access links. The behaviors of TCPs significantly influence the others in the opposite direction. Specifically, the radio links of LTE are asymmetric, which may induce drastic interactions of TCPs and rapid draining of downlink buffer. The periodic idleness of downlink is a huge waste of the precious radio bandwidth and results in considerable performance degradation. In the viewpoint of Coupled Queues, we thoroughly understand the interacting TCPs and explain the reason for performance degradation. Based on a straightforward modeling procedure, we formalize the evolution of two-way TCPs and model the bottleneck queue size in every slot. The model indicates the queues are close coupled, which is verified with simulations on NS2. If the uplink (queue) is fully utilized, the downlink (queue) will always be underutilized even idle, and vice versa. Furthermore, an effective solution called Preemptive ACK Queueing (PAQ) is designed to decouple the queues, which improves the performance of two-way TCPs over LTE networks. During crowded events, cellular networks face voice and data traffic volumes that are often orders of magnitude higher than what they face during routine days. Despite the use of portable base stations for temporarily increasing communication capacity and free Wi-Fi access points for offloading Internet traffic from cellular base stations, crowded events still present significant challenges for cellular network operators looking to reduce dropped call events and improve Internet speeds. For effective cellular network design, management, and optimization, it is crucial to understand how cellular network performance degrades during crowded events, what causes this degradation, and how practical mitigation schemes would perform in real-life crowded events. This paper makes a first step towards this end by characterizing the operational performance of a tier-1 cellular network in the United States during two high-profile crowded events in 2012. We illustrate how the changes in population distribution, user behavior, and application workload during crowded events result in significant voice and data performance degradation, including more than two orders of magnitude increase in connection failures. Our findings suggest two mechanisms that can improve performance without resorting to costly infrastructure changes: radio resource allocation tuning and opportunistic connection sharing. Using trace-driven simulations, we show that more aggressive release of radio resources via 1-2 seconds shorter RRC timeouts as compared to routine days helps to achieve better tradeoff between wasted radio resources, energy consumption, and delay during crowded events; and opportunistic connection sharing can reduce connection failures by 95 when employed by a small number of devices in each cell sector. With lower latency and higher bandwidth than its predecessor 3G networks, the latest cellular technology 4G LTE has been attracting many new users. However, the interactions among applications, network transport protocol, and the radio layer still remain unexplored. In this work, we conduct an in-depth study of these interactions and their impact on performance, using a combination of active and passive measurements. We observed that LTE has significantly shorter state promotion delays and lower RTTs than those of 3G networks. We discovered various inefficiencies in TCP over LTE such as undesired slow start. We further developed a novel and lightweight passive bandwidth estimation technique for LTE networks. Using this tool, we discovered that many TCP connections significantly under-utilize the available bandwidth. On average, the actually used bandwidth is less than 50 of the available bandwidth. This causes data downloads to be longer, and incur additional energy overhead. We found that the under-utilization can be caused by both application behavior and TCP parameter setting. We found that 52.6 of all downlink TCP flows have been throttled by limited TCP receive window, and that data transfer patterns for some popular applications are both energy and network unfriendly. All these findings highlight the need to develop transport protocol mechanisms and applications that are more LTE-friendly. With the popularity of mobile devices and the pervasive use of cellular technology, there is widespread interest in hybrid networks and on how to achieve robustness and good performance from them. As most smart phones and mobile devices are equipped with dual interfaces (WiFi and 3G 4G), a promising approach is through the use of multi-path TCP, which leverages path diversity to improve performance and provide robust data transfers. In this paper we explore the performance of multi-path TCP in the wild, focusing on simple 2-path multi-path TCP scenarios. We seek to answer the following questions: How much can a user benefit from using multi-path TCP over cellular and WiFi relative to using the either interface alone? What is the impact of flow size on average latency? What is the effect of the rate route control algorithm on performance? We are especially interested in understanding how application level performance is affected when path characteristics (e.g., round trip times and loss rates) are diverse. We address these questions by conducting measurements using one commercial Internet service provider and three major cellular carriers in the US. Mobile network operators have a significant interest in the performance of streaming video on their networks because network dynamics directly influence the Quality of Experience (QoE). However, unlike video service providers, network operators are not privy to the client- or server-side logs typically used to measure key video performance metrics, such as user engagement. To address this limitation, this paper presents the first large-scale study characterizing the impact of cellular network performance on mobile video user engagement from the perspective of a network operator. Our study on a month-long anonymized data set from a major cellular network makes two main contributions. First, we quantify the effect that 31 different network factors have on user behavior in mobile video. Our results provide network operators direct guidance on how to improve user engagement --- for example, improving mean signal-to-interference ratio by 1 dB reduces the likelihood of video abandonment by 2 . Second, we model the complex relationships between these factors and video abandonment, enabling operators to monitor mobile video user engagement in real-time. Our model can predict whether a user completely downloads a video with more than 87 accuracy by observing only the initial 10 seconds of video streaming sessions. Moreover, our model achieves significantly better accuracy than prior models that require client- or server-side logs, yet we only use standard radio network statistics and or TCP IP headers available to network operators. The popularity of smartphones and smartphone applications means that data is the dominant traffic type in current mobile networks. In this paper we present our work on a systematic investigation into facets of the LTE EPC architecture that impact the performance of TCP as the predominant transport layer protocol used by applications on mobile networks. We found that (1) load increase in a cell causes dramatic bandwidth reduction on UEs and significantly degrades TCP performance, (2) seamless handover causes significant TCP losses while lossless handover increases TCP segments' delay.