Compared with using only a single wireless path such as WiFi, leveraging multipath (e.g., WiFi and cellular) can dramatically improve users' quality of experience (QoE) for mobile video streaming. However, Multipath TCP (MPTCP), the de-facto multipath solution, lacks the support to prioritize one path over another. When applied to video streaming, it may cause undesired network usage such as substantial over-utilization of the metered cellular link. In this paper, we propose MP-DASH, a multipath framework for video streaming with the awareness of network interface preferences from users. The basic idea behind MP-DASH is to strategically schedule video chunks' delivery and thus satisfy user preferences. MP-DASH can work with a wide range of off-the-shelf video rate adaptation algorithms with very small changes. Our extensive field studies at 33 locations in three U.S. states suggest that MP-DASH is very effective: it can reduce cellular usage by up to 99% and radio energy consumption by up to 85% with negligible degradation of QoE, compared with off-the-shelf MPTCP.

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 an 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 toward this end by characterizing the operational performance of a tier-1 cellular network in the U.S. 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 s shorter radio resource control timeouts as compared with 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.

Leveraging multiple interfaces (e.g., WiFi and cellular) on mobile devices is known to provide performance gains for applications such as bulk data transfer. In this paper, we complement prior studies by conducting, to the best of our knowledge, the first measurement study of mobile web performance over multipath TCP (MPTCP). Based on experiments using real web pages under diverse settings, we found the upper-layer web protocols can incur complex and sometimes unexpected interactions with the multipath-enabled transport layer. MPTCP always boosts SPDY while may hurt HTTP. MPTCP also helps mitigate SPDY's key limitations of being vulnerable to losses and inefficient bandwidth utilization. We provide in-depth explanations of the root causes, as well as recommendations for improving mobile web performance over MPTCP.

Significant geospatial and temporal correlations, in terms of traffic volume and application access, exist in cellular network usage as shown in recent studies on cellular network measurement. Such geospatial and temporal correlation patterns provide local optimization opportunities to cellular network operators for handling the explosive growth in the traffic volume observed in recent years. To the best of our knowledge, in this paper, we provide the first fine-grained joint characterization of the geospatial and temporal dynamics of application usage in a 3G cellular data network. Our analysis is based on two simultaneously collected traces from the radio access network (containing location records) and the core network (containing traffic records) of a tier-1 cellular network in the United States. To better understand the application usage in our data, we first cluster cell locations based on their application distributions and then study the geospatial and temporal dynamics of application usage across different geographical regions. The results of our measurement study present cellular network operators with fine-grained insights that can be leveraged to tune network parameter settings for better network performance and user experience.

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.

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.

Cellular network-based machine-to-machine (M2M) communication is fast becoming a market-changing force for a wide spectrum of businesses and applications such as telematics, smart metering, point-of-sale terminals, and home security and automation systems. In this paper, we aim to answer the following important question: Does traffic generated by M2M devices impose new requirements and challenges for cellular network design and management? To answer this question, we take a first look at the characteristics of M2M traffic and compare it to traditional smartphone traffic. We have conducted our measurement analysis using a week-long traffic trace collected from a tier-1 cellular network in the US. We characterize M2M traffic from a wide range of perspectives, including temporal dynamics, device mobility, application usage, and network performance. Our experimental results show that M2M traffic exhibits significantly different patterns than smartphone traffic in multiple aspects. For instance, M2M devices have a much larger ratio of uplink-to-downlink traffic volume, their traffic typically exhibits different diurnal patterns, they are more likely to generate synchronized traffic resulting in bursty aggregate traffic volumes, and are less mobile compared to smartphones. On the other hand, we also find that M2M devices are generally competing with smartphones for network resources in co-located geographical regions. These and other findings suggest that better protocol design, more careful spectrum allocation, and modified pricing schemes may be needed to accommodate the rise of M2M devices.

Recent studies on cellular network measurement have provided the evidence that significant geospatial correlations, in terms of traffic volume and application access, exist in cellular network usage. Such geospatial correlation patterns provide local optimization opportunities to cellular network operators for handling the explosive growth in the traffic volume observed in recent years. To the best of our knowledge, in this paper, we provide the first fine-grained characterization of the geospatial dynamics of application usage in a 3G cellular data network. Our analysis is based on two simultaneously collected traces from the radio access network (containing location records) and the core network (containing traffic records) of a tier-1 cellular network in the United States. To better understand the application usage in our data, we first cluster cell locations based on their application distributions and then study the geospatial dynamics of application usage across different geographical regions. The results of our measurement study present cellular network operators with fine-grained insights that can be leveraged to tune network parameter settings.

Cellular network based Machine-to-Machine (M2M) communication is fast becoming a market-changing force for a wide spectrum of businesses and applications such as telematics, smart metering, point-of-sale terminals, and home security and automation systems. In this paper, we aim to answer the following important question: Does traffic generated by M2M devices impose new requirements and challenges for cellular network design and management? To answer this question, we take a first look at the characteristics of M2M traffic and compare it with traditional smartphone traffic. We have conducted our measurement analysis using a week-long traffic trace collected from a tier-1 cellular network in the United States. We characterize M2M traffic from a wide range of perspectives, including temporal dynamics, device mobility, application usage, and network performance.

Recently, practical subframe-level schemes, such as frame combining and partial packet recovery, have been proposed for combating wireless transmission errors. These approaches depend heavily on the bit error behavior of wireless data transmissions, which is overlooked in the literature. We study the characteristics of subframe bit errors and their location distribution by conducting extensive experiments on several IEEE 802.11 WLAN testbeds. Our measurement results identify three bit error patterns: slope-line, saw-line, and finger. Among these three patterns, we have verified that the slope-line and saw-line are present in different physical environments and across various hardware platforms. However, the finger pattern does not appear on some platforms. We discuss our current hypotheses for the reasons behind these bit error patterns and how identifying these patterns may help improve the robustness of WLAN transmissions. We believe that identifiable bit error patterns can potentially introduce new opportunities in channel coding, network coding, forward error correction (FEC), and frame combining.

Existing studies have demonstrated that uneven and dynamic usage patterns by the primary users of license-based wireless communication systems can often lead to temporal and spatial spectrum underutilization. This provides an opportunity for the secondary users (SUs) to tap into underutilized frequency bands provided that they are capable of cognitively accessing systems without colliding or impacting the performance of the primary users (PUs). When there are multiple networks with spare spectrum, secondary users can opportunistically choose the best network to access, subject to certain constraints. In cognitive radio systems, this is referred to as the network selection problem for secondary users. This paper develops a Markov queuing model to obtain the maximum allowable arrival rate of secondary users subject to a target collision probability for the primary users. Based on this model, we design a novel Collision-Constrained Network Selection (CCNS) method that maximizes secondary users' throughput subject to a given PU collision probability. Further, we propose two approaches, referred as CCNS-Greedy and CCNS-Energy, which target to reduce collision probability and to decrease energy consumption of secondary users when the system is underloaded. This, however, has one practical drawback in that the proposed CCNS method depends on PU and SU traffic characteristics such as inter-arrival time and service time, which might not be available in real scenario. We next illustrate that a MEAsurement-based Networks Selection (MEANS) scheme can be used to perform network selection for secondary users based on online measurement of PU collision probability of each network. We evaluated the performance based on extensive simulation, which conclusively shows that the proposed schemes achieve the best performance in terms of resulting PU collision probability, SU throughput, and SU energy consumption, when compared to both Random and Greedy strategies.

Understanding Internet traffic dynamics in large cellular networks is important for network design, troubleshooting, performance evaluation, and optimization. In this paper, we present the results from our study, which is based upon a week-long aggregated flow level mobile device traffic data collected from a major cellular operator's core network. In this study, we measure and characterize the spatial and temporal dynamics of mobile Internet traffic. We distinguish our study from other related work by conducting the measurement at a larger scale and exploring mobile data traffic patterns along two new dimensions -- device types and applications that generate such traffic patterns. Based on the findings of our measurement analysis, we propose a Zipf-like model to capture the volume distribution of application traffic and a Markov model to capture the volume dynamics of aggregate Internet traffic. We further customize our models for different device types using an unsupervised clustering algorithm to improve prediction accuracy.

IP prefix hijacking is one of the top security threats targeting today's Internet routing protocol. Several schemes have been proposed to either detect or mitigate prefix hijacking events. However, none of these approaches is adopted and deployed on a large-scale on the Internet for reasons such as scalability, economical practicality, or unrealistic assumptions about the collaborations among ISPs. Thus there are no actionable and deployable solutions for dealing with prefix hijacking. In this paper, we study key issues related to deploying and operating an IP prefix hijacking detection and mitigation system. Our contributions include (i) deployment strategies for hijacking detection and mitigation system (named as TowerDefense): a practical service model for prefix hijacking protection and effective algorithms for selecting agent locations for detecting and mitigating prefix hijacking attacks; and (ii) large scale experiments on PlanetLab and extensive analysis on the performance of TowerDefense.

Measurement studies have shown that uneven and dynamic usage patterns by the primary users of license based wireless communication systems often lead to temporal and spatial spectrum underutilization. This provides an opportunity for secondary users to tap into underutilized frequency bands provided that they are capable of cognitively accessing without colliding or impacting the performance of the primary users. When there are multiple networks with spare spectrum, secondary users can opportunistically choose the best network to access, subject to certain constraints. In cognitive radio systems, this is referred to as the network selection problem. In this paper, multiple network selection strategies namely, random, weighted, and greedy, are comprehensively evaluated. It is found that without adequate admission control, those methods cannot provide sufficient service protection for the primary users. Next, a Markov decision model is applied to obtain the maximum allowable arrival rate for secondary users subject to a target collision probability for the primary users. Based on this model, a Collision-Constrained Network Selection (CCNS) method is proposed that maximizes system throughput subject to a given collision probability. Simulations show that comparing to random, weighted, and greedy strategies CCNS achieves an improved performance in terms of system throughput and collision probability.

Multiple co-channel WLAN BSSes (i.e., WLAN cells) overlapping in coverage are generally considered undesirable because members of the OBSSes compete for channel access, which typically increases the contention level of wireless medium access and reduces overall system performance. In this paper, we propose to use channel access throttling (CAT) for managing Wireless LAN radio resources for overlapping BSSes (OBSSes). CAT provides an access point (AP) of each BSS with a mechanism to control channel access parameters of its member stations on the fly. By coordinating the CAT operations of the OBSS APs, we can enable privileged channel access to an individual BSS at a particular time, for example, by assigning high priority access parameters to member stations associated with the BSS. By controlling how much each BSS may be given the privileged channel access, we can also achieve a proportional partitioning of channel capacity among OBSSes. We present evaluation results obtained from both simulations and experiments using testbed built with commercial off-the-shelf (COTS) WLAN hardware and open-source device driver. Our results show that with CAT, not only can we proportionally partition channel capacity among the OBSSes, but also improve channel utilization efficiency and increase overall capacity.

In IEEE 802.11 Wireless LAN (WLAN) systems, techniques such as acknowledgement, retransmission, and transmission rate adaptation, are frame-level mechanisms designed for combating transmission errors. Recently sub-frame level mechanisms such as frame combining have been proposed by the research community. In this paper, we present results obtained from our bit error study for identifying sub-frame error patterns because we believe that identifiable bit error patterns can potentially introduce new opportunities in channel coding, network coding, forward error correction (FEC), and frame combining mechanisms. We have constructed a number of IEEE 802.11 wireless LAN testbeds and conducted extensive experiments to study the characteristics of bit errors and their location distribution. Conventional wisdom dictates that bit error probability is the result of channel condition and ought to follow corresponding distribution. However our measurement results identify three repeatable bit error patterns that are not induced by channel conditions. We have verified that such error patterns are present in WLAN transmissions in different physical environments and across different wireless LAN hardware platforms. We also discuss our current hypotheses for the reasons behind these bit error probability patterns and how identifying these patterns may help improving WLAN transmission robustness.

The de facto QoS channel access method for the IEEE 802.11 Wireless LANs is the Enhanced Distributed Channel Access (EDCA) mechanism, which differentiates transmission treatments for data frames belonging to different traffic categories with four different levels of channel access priority. In this paper, we propose extending EDCA with Channel Access Throttling (CAT) for more flexible and efficient QoS support. By assigning different member stations different channel access parameters, CAT differentiates channel access priorities not between traffic categories but between member stations. Then by dynamically changing the channel access parameters of each member station based on a pre-computed schedule, CAT enables EDCA WLANs the benefits of scheduled access QoS. We also present evaluation results of CAT obtained from both simulations and experiments conducted using off-the-shelf WLAN hardware and open-source device driver. Our results show that CAT can proportionally partition channel capacity, significantly improve performance of multimedia applications, effectively achieve performance protection for admitted flows, and increase per cell VoIP call capacity by up to 41%.

As more and more Internet IP prefix hijacking incidents are being reported, the value of hijacking detection services has become evident. Most of the current hijacking detection approaches monitor IP prefixes on the control plane and detect inconsistencies in route advertisements and route qualities. We propose a different approach that utilizes information collected mostly from the data plane. Our method is motivated by two key observations: when a prefix is not hijacked, 1) the hop count of the path from a source to this prefix is generally stable; and 2) the path from a source to this prefix is almost always a super-path of the path from the same source to a reference point along the previous path, as long as the reference point is topologically close to the prefix. By carefully selecting multiple vantage points and monitoring from these vantage points for any departure from these two observations, our method is able to detect prefix hijacking with high accuracy in a light-weight, distributed, and real-time fashion. Through simulations constructed based on real Internet measurement traces, we demonstrate that our scheme is accurate with both false positive and false negative ratios below 0.5%.

In this paper, we propose an enhancement to the IEEE 802.11 distributed coordination function (DCF). The enhancement improves the level of channel spatial reuse; thus, it improves overall network data throughput in dense deployments. Our modification, named the location-enhanced DCF (LED), incorporates location information in DCF frame exchange sequences so that stations sharing the communication channel are able to make better interference predictions and blocking assessments. Hence, more concurrent transmissions can be conducted in densely deployed wireless LANs. The potential performance enhancement of LED is studied both analytically and via ns-2 simulations. The results show that the LED method achieves significant throughput improvements over the original DCF.

In this paper, we propose an enhancement to the existing IEEE 802.11 distributed coordination function (DCF) MAC to improve channel spatial reuse efficiency, and thus improve overall network data throughput. Our modification, named the location enhanced DCF (LED) for IEEE 802.11, incorporates location information in DCF frame exchange sequences so that stations sharing the communication channel are able to make better interference predictions and blocking assessments. Utilizing an underlying physical layer design that supports frame capture, the LED enhanced interference estimation can increase overall network data throughput by permitting more concurrent transmissions. In this paper we also analytically study the potential performance enhancement of the LED over the original IEEE 802.11 DCF. The results are verified using the ns-2 simulator, which shows that up to 35% of DCF blocking decisions are unnecessary and our LED method can achieve up to 22% more throughput than the original DCF.

We present a framework for agreements in pervasive environments called the Universal Pervasive Transaction Framework (UPTF) for parties transacting in wireless insecure environments using mobile devices. We discuss one type of such agreement with commercial interest, namely mobile payments from a payer to a payee. We have implemented two complete systems for purchasing and payment with mobile devices utilizing UPTF. The first introduces a special purpose, new mobile device called the Universal Pervasive Transaction Device (UPTD) and the second utilizes J2ME-capable mobile phones.

In this paper we propose a multicast routing protocol for mobile ad hoc networks (MANETs). The protocol-termed differential destination mmulticast (DDM)-differs from common approaches proposed for MANET multicast routing in two ways. Firstly, instead of distributing membership control throughout the network, DDM concentrates this authority at the data sources (i.e. senders) thereby giving sources knowledge of group membership. Secondly, differentially-encoded, variable-length destination headers are inserted in data packets which are used in combination with unicast routing tables to forward multicast packets towards multicast receivers. Instead of requiring that multicast forwarding state to be stored in all participating nodes, this approach also provides the option of stateless multicasting. Each node independently has the choice of caching forwarding state or having its upstream neighbor to insert this state into self-routed data packets, or some combination thereof. The protocol is best suited for use with small multicast groups operating in dynamic networks of any size.

This paper summarizes work underway at the University of Maryland on the design of a protocol kernel for mobile ad hoc networks. The kernel's architecture is modular, and follows a composition-based approach to protocol kernel construction. In this approach, interacting policies are logically, vertically closely-coupled, but physically loosely-coupled. Thus, various components of the kernel may be changed more easily. The architecture supports the notion of routing through an IP-layer routing "fabric", a construction which is a logical union of multiple, multi-hop topologies-each network using a different link layer technology. The architecture explicitly separates the policy functions of data routing and forwarding-an approach that more clearly associates a policy with its function, requires independent specification of both policies and results in a more flexible and configurable kernel.