Shruti Sanadhya

Asymmetric caching: improved network deduplication for mobile devices

Network deduplication (dedup) is an attractive approach to improve network performance for mobile devices. With traditional deduplication, the dedup~source uses only the portion of the cache at the dedup~destination that it is aware of. We argue in this work that in a mobile environment, the dedup~destination (say the mobile) could have accumulated a much larger cache than what the current dedup~source is aware of. This can occur because of several reasons ranging from the mobile consuming content through heterogeneous wireless technologies, to the mobile moving across different wireless networks. In this context, we propose asymmetric caching, a solution that is overlaid on baseline network deduplication, but which allows the dedup~destination to selectively feedback appropriate portions of its cache to the dedup~source with the intent of improving the redundancy elimination efficiency. We show using traffic traces collected from 30 mobile users, that with asymmetric caching, over 89% of the achievable redundancy can be identified and eliminated even when the dedup~source has less than one hundredth of the cache size as the dedup~destination. Further, we show that the ratio of bytes saved from transmission at the dedup~source because of asymmetric caching is over 6x that of the number of bytes sent as feedback. Finally, with a prototype implementation of asymmetric caching on both a Linux laptop and an Android smartphone, we demonstrate that the solution is deployable with reasonable CPU and memory overheads.

On link rate adaptation in 802.11n WLANs

The IEEE 802.11n standard is gaining popularity to achieve high throughput in Wireless LANs. In this paper, we explore link adaptation in practical 802.11n systems using experiments with off-the-shelf hardware. Our experiments reveal several non-trivial insights. Specifically, (1) trivial extensions of algorithms developed for 802.11g provide minimal benefits in 802.11n systems; (2) in contrast to theoretical expectation, multiple antenna transmission does not always lead to higher throughput in practice; (3) both stream and antenna selection are essential to reap the full benefits of MIMO technologies. We use insights developed from experiments to develop a new metric for stream selection called the Median Multiplexing Factor (MMF). The proposed metric can be used to develop intelligent rate selection algorithms that can achieve high throughput with purely software changes.

Adaptive flow control for TCP on mobile phones

The focus of this work is to study the efficacy of TCPs flow control algorithm on mobile phones. Specifically, we identify the design limitations of the algorithm when operating in environments, such as mobile phones, where flow control assumes greater importance because of device resource limitations. We then propose an adaptive flow control (AFC) algorithm for TCP that relies not just on the available buffer space but also on the application read-rate at the receiver. We show, using NS2 simulations, that AFC can provide considerable performance benefits over classical TCP flow control.

ViFi: virtualizing WLAN using commodity hardware

We consider an architecture in which the same WiFi infrastructure can be dynamically shared among multiple operators. Our system, ViFi, virtualizes WLAN resources, allowing for controlled sharing of both the uplink and downlink bandwidth. ViFi operates with stock 802.11 clients, and can be implemented entirely as a software add-on for commodity 802.11 APs. ViFi puts users (customers) of different operators in separate groups, each creating a virtual WLAN. ViFi guarantees proportional fair share of channel access time at group level, and isolates traffic between groups. The key technical contribution of ViFi is a useful form of virtualization without requiring changes to the underlying WiFi protocol.

ViFi: Virtualizing WLAN using Commodity Hardware

We consider an architecture in which the same WiFi infrastructure can be dynamically shared among multiple operators. Our system, ViFi, virtualizes WLAN resources, allowing for controlled sharing of both the uplink and downlink bandwidth. ViFi operates with stock 802.11 clients, and can be implemented entirely as a software add-on for commodity 802.11 APs. ViFi puts users (customers) of different operators in separate groups, each creating a virtual WLAN. ViFi guarantees proportional fair share of channel access time at group level, and isolates traffic between groups. The key technical contribution of ViFi is a useful form of virtualization without requiring changes to the underlying WiFi protocol.

Pulsar: improving throughput estimation in enterprise LTE small cells

With the great success of LTE(-A) outdoor, LTE-based small cell technology has become popular and is penetrating indoor enterprise environment, co-existing with WiFi networks, to provide better user experience or Quality-of-Experience (QoE). However, accurate estimation of LTE links is challenging and critical to continue providing QoE for many enterprise applications (e.g., video/audio) and services (network selection). While prior work on LTE link throughput estimation depends mostly on a single factor (e.g., link rate), we argue that it needs to consider more factors to improve the estimation to meet increasing demands on QoE. In this paper, we propose a new metric, called Pulsar (Per-user LTE ShAre of Resources), that estimates per flow throughput in LTE networks by leveraging both underlying channel information and application traffic characteristics. Our extensive evaluation study through ns-3 shows that Pulsar reduces the estimation error more than 92%, compared to prior work, in various scenarios, while keeping estimation overhead low.

A super-aggregation strategy for multi-homed mobile hosts with heterogeneous wireless interfaces

Most mobile devices today are equipped with multiple and heterogeneous wireless interfaces. In this paper we ask the following question: What is the best approach to leverage the multiple interfaces available at a mobile device in terms of the performance delivered to the user? In answering the question we argue that simple “bandwidth aggregation” approaches do not provide any meaningful benefits when the multiple interfaces used have highly disparate bandwidths as is true in many practical environments. We then present super-aggregation, a set of mechanisms that in tandem use the multiple interfaces intelligently and in the process is able to achieve a performance that is “better than the sum of throughputs” achievable through each of the interfaces individually. We prototype super-aggregation on both a laptop and the Google Android mobile phone and demonstrate the significant (up to 3

Poster: Observe. Patternize. Mimic. : Leveraging Patterns in Mobile-User Behavior for Enterprise Applications

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