We present a long term and large scale study of the experience of mobile users through two popular but contrasting applications in the wild. To conduct this study, we implemented a measurement framework and library, called Insight, which has been deployed on these two applications that are available through Apple's App Store and Google's Android Market. One of them, Parallel Kingdom (PK), is a popular massively multiplayer online role-playing game (MMORPG) which has over a million unique users distributed more than 120 countries. The other application, StudyBlue (SB), is an educational application with over 160,000 unique users. Our study spans most of the life of the PK game (more than 3 years) while our deployment with SB has been running for over a year now. We use Insight to collect diverse information about network behavior, application usage and footprints, platform statistics, user actions, and various factors affecting application revenues.

The set of virtual devices offered by a hypervisor to its guest VMs is a virtualization component ripe with security exploits -- more than half of all vulnerabilities of today's hypervisors are found in this codebase. This paper presents Min-V, a hypervisor that disables all virtual devices not critical to running VMs in the cloud. Of the remaining devices, Min-V takes a step further and eliminates all remaining functionality not needed for the cloud.

This paper introduces models and a system for designing 802.11 wireless LANs (WLANs) using flexible channelization— the choice of an appropriate channel width and center frequency for each transmission. In contrast to current 802.11 systems that use fixed width channels, the proposed system, FLUID, configures all access points and their clients using flexible channels. We show that a key challenge in designing such a system stems from managing the effects of interference due to multiple transmitters employing variable channel widths, in a network-wide setting. We implemented FLUID in an enterprise-like setup using a 50 node testbed (with off-the shelf wireless cards) and we show that FLUID improves the average throughput by 59 percent across all PHY rates, compared to existing fixed-width approaches.

In this paper, we propose Airshark -- a system that detects multiple non-WiFi RF devices in real-time and using only commodity WiFi hardware. To motivate the need for systems like Airshark, we start with measurement study that characterizes the usage and prevalence of non-WiFi devices across many locations. We then present the design and implementation of Airshark. Airshark extracts unique features using the functionality provided by a WiFi card to detect multiple non-WiFi devices including fixed frequency devices (e.g., ZigBee, analog cordless phone), frequency hoppers (e.g., Bluetooth, game controllers like Xbox), and broadband interferers (e.g., microwave ovens). Airshark has an average detection accuracy of 91-96%, even in the presence of multiple simultaneously active RF devices operating at a wide range of signal strengths (-80 to -30 dBm), while maintaining a low false positive rate. Through a deployment in two production WLANs, we show that Airshark can be a useful tool to the WLAN administrators in understanding non-WiFi interference.

This paper introduces models and a system for designing 802.11 wireless LANs (WLANs) using flexible channelization -- the choice of an appropriate channel width and center frequency for each transmission. In contrast to current 802.11 systems that use fixed width channels, the proposed system, FLUID, configures all access points and their clients using flexible channels. We show that a key challenge in designing such a system stems from managing the effects of interference due to multiple transmitters employing variable channel widths, in a network-wide setting. We implemented FLUID in an enterprise-like setup using a 50 node testbed (with off-the shelf wireless cards) and we show that FLUID improves the average throughput by 59% across all PHY rates, compared to existing fixed-width approaches.

WiFi radios in smart-phones consume a significant amount of power when active. The 802.11 standard allows these devices to save power through an energy-conserving Power Save Mode (PSM). However, depending on the PSM implementation strategies used by the clients/Access Points (APs), we find competing background traffic results in one or more of the following negative consequences: a significant increase, up to 300%, in a client's energy consumption, a decrease in wireless network capacity due to unnecessary retransmissions, and unfairness.

A recent approach-COPE, presented by Katti (Proc. ACM SIGCOMM 2006, pp. 243-254)-for improving the throughput of unicast traffic in wireless multihop networks exploits the broadcast nature of the wireless medium through opportunistic network coding. In this paper, we analyze throughput improvements obtained by COPE-type network coding in wireless networks from a theoretical perspective. We make two key contributions. First, we obtain a theoretical formulation for computing the throughput of network coding on any wireless network topology and any pattern of concurrent unicast traffic sessions. Second, we advocate that routing be made aware of network coding opportunities rather than, as in COPE, being oblivious to it. More importantly, our model considers the tradeoff between routing flows close to each other for utilizing coding opportunities and away from each other for avoiding wireless interference. Our theoretical formulation provides a method for computing source-destination routes and utilizing the best coding opportunities from available ones so as to maximize the throughput. We handle scheduling of broadcast transmissions subject to wireless transmit/receive diversity and link interference in our optimization framework. Using our formulations, we compare the performance of traditional unicast routing and network coding with coding-oblivious and coding-aware routing on a variety of mesh network topologies, including some derived from contemporary mesh network testbeds. Our evaluations show that a route selection strategy that is aware of network coding opportunities leads to higher end-to-end throughput when compared to coding-oblivious routing strategies.

Enterprise WLANs have made a dramatic shift towards centralized architectures in the recent past. The reasons for such a change have been ease of management and better design of various control and security functions. The data path of WLANs, however, continues to use the distributed, random-access model, as defined by the popular DCF mechanism of the 802.11 standard. While theoretical results indicate that a centrally scheduled data path can achieve higher efficiency than its distributed counterpart, the likely complexity of such a solution has inhibited practical consideration. In this paper, we take a fresh, implementation and deployment oriented, view in understanding data path choices in enterprise WLANs. We perform extensive measurements to characterize the impact of various design choices, like scheduling granularity on the performance of a centralized scheduler, and identify regions where such a centralized scheduler can provide the best gains.Our detailed evaluation with scheduling prototypes deployed on two different wireless testbeds indicates that DCF is quite robust in many scenarios, but centralization can play a unique role in 1) mitigating hidden terminals - scenarios which may occur infrequently, but become pain points when they do and 2) exploiting exposed terminals - scenarios which occur more frequently, and limit the potential of successful concurrent transmissions. Motivated by these results, we design and implement CENTAUR - a hybrid data path for enterprise WLANs, that combines the simplicity and ease of DCF with a limited amount of centralized scheduling from a unique vantage point. Our mechanisms do not require client cooperation and can support legacy 802.11 clients.

We present a measurement study of a large-scale urban WiFi mesh network consisting of more than 250 Mesh Access Points (MAPs), with paying customers that use it for Internet access. Our study, involved collecting multi-modal data, e.g., through continuous gathering of SNMP logs, syslogs, passive traffic capture, and limited active measurements in different parts of the city. Our study is split into four components — planning and deployment of the mesh, success of mesh routing techniques, likely experience of users, and characterization of how the mesh is utilized. During our data collection process that spanned 8 months, the network changed many times due to hardware and software upgrades. Hence to present a consistent view of the network, the core dataset used in this paper comes from a two week excerpt of our dataset. This part of the dataset had more than 1.7 million SNMP log entries (from 224 MAPs) and more than 100 hours of active measurements. The scale of the study allowed us to make many important observations that are critical in planning and using WiFi meshes as an Internet access technology. For example, our study indicates that the last hop 2.4GHz wireless link between the mesh and the client is the major bottleneck in client performance. Further we observe that deploying the mesh access points on utility poles results in performance degradation for indoor clients that receive poor signal from the access points.

We present an experimental study of IEEE 802.11n (high throughput extension to the 802.11 standard) using commodity wireless hardware. 802.11n introduces a variety of new mechanisms including physical layer diversity techniques, channel bonding and frame aggregation mechanisms. Using measurements from our testbed, we analyze the fundamental characteristics of 802.11n links and quantify the gains of each mechanism under diverse scenarios. We show that the throughput of an 802.11n link can be severely degraded (up ≈85%) in presence of an 802.11g link. Our results also indicate that increased amount of interference due to wider channel bandwidths can lead to throughput degradation. To this end, we characterize the nature of interference due to variable channel widths in 802.11n and show that careful modeling of interference is imperative in such scenarios. Further, as a reappraisal of previous work, we evaluate the effectiveness of MAC level diversity in the presence of physical layer diversity mechanisms introduced by 802.11n.

It is well known that a packet loss in 802.11 can happen either due to collision or an insufficiently strong signal. However, discerning the exact cause of a packet loss, once it occurs, is known to be quite difficult. In this paper we take a fresh look at this problem of wireless packet loss diagnosis for 802.11-based communication and propose a promising technique called COLLIE. COLLIE performs loss diagnosis by using newly designed metrics that examine error patterns within a physical-layersymbolin order to expose statistical differences between collision and weak signal based losses. We implement COLLIE through custom driver-level modifications in Linux and evaluate its performance experimentally. Our results demonstrate that it has an accuracy ranging between 60-95% while allowing a false positive rate of up to 2%. We also demonstrate the use of COLLIE in subsequent link adaptations in both static and mobile wireless usage scenarios through measurements on regular laptops and the Netgear SPH101 Voice-over-WiFi phone. In these experiments, COLLIE led to throughput improvements of 20- 60% and reduced retransmission related costs by 40% depending upon the channel conditions.

Local network coding is growing in prominence as a technique to facilitate greater capacity utilization in multi-hop wireless networks. A specific objective of such local network coding techniques has been to explicitly minimize the total number of transmissions needed to carry packets across each wireless hop. While such a strategy is certainly useful, we argue that in lossy wireless environments, a better use of local network coding is to provide higher levels of redundancy even at the cost of increasing the number of transmissions required to communicate the same information. In this paper we show that the design space for effective redundancy in local network coding is quite large, which makes optimal formulations of the problem hard to realize in practice. We present a detailed exploration of this design space and propose a suite of algorithms, called CLONE, that can lead to further throughput gains in multi-hop wireless scenarios. Through careful analysis, simulations, and detailed implementation on a real testbed, we show that some of our simplest CLONE algorithms can be efficiently implemented in today's wireless hardware to provide a factor of two improvement in throughput for example scenarios, while other, more effective, CLONE algorithms require additional advances in hardware processing speeds to be deployable in practice.

A recent approach, COPE, for improving the throughput of unicast traffic in wireless multi-hop networks exploits the broadcast nature of the wireless medium through opportunistic network coding. In this paper, we analyze throughput improvements obtained by COPE-type network coding in wireless networks from a theoretical perspective. We make two key contributions. First, we obtain a theoretical formulation for computing the throughput of network coding on any wireless network topology and any pattern of concurrent unicast traffic sessions. Second, we advocate that routing be made aware of network coding opportunities rather than, as in COPE, being oblivious to it. More importantly, our work studies the tradeoff between routing flows "close to each other" for utilizing coding opportunities and "away from each other" for avoiding wireless interference. Our theoretical formulation provides a method for computing source-destination routes and utilizing the best coding opportunities from available ones so as to maximize the throughput. We handle scheduling of broadcast transmissions subject to wireless transmit/receive diversity and link interference in our optimization framework. Using our formulations, we compare the performance of traditional unicast routing and network coding with coding-oblivious and coding-aware routing on a variety of mesh network topologies, including some derived from contemporary mesh network testbeds. Our evaluations show that a route selection strategy that is aware of network coding opportunities leads to higher end-to-end throughput when compared to coding-oblivious routing strategies.