Showing papers by "Samir R. Das published in 2016"

KLEIN: A Minimally Disruptive Design for an Elastic Cellular Core

Abstract: Today's cellular core, which connects the radio access network to the Internet, relies on fixed hardware appliances placed at a few dedicated locations and uses relatively static routing policies. As such, today's core design has key limitations---it induces inefficient provisioning tradeoffs and is poorly equipped to handle overload, failure scenarios, and diverse application requirements. To address these limitations, ongoing efforts envision "clean slate" solutions that depart from cellular standards and routing protocols; e.g., via programmable switches at base stations and per-flow SDN-like orchestration. The driving question of this work is to ask if a clean-slate redesign is necessary and if not, how can we design a flexible cellular core that is minimally disruptive. We propose KLEIN, a design that stays within the confines of current cellular standards and addresses the above limitations by combining network functions virtualization with smart resource management. We address key challenges w.r.t. scalability and responsiveness in realizing KLEIN via backwards-compatible orchestration mechanisms. Our evaluations through data-driven simulations and real prototype experiments using OpenAirInterface show that KLEIN can scale to billions of devices and is close to optimal for wide variety of traffic and deployment parameters.

Design and evaluation of a foveated video streaming service for commodity client devices

Abstract: Humans see only a tiny region at the center of their visual field with the highest visual acuity, a behavior known as foveation. Visual acuity reduces drastically towards the visual periphery. 'Foveated' video coding/compression techniques exploit this non-uniformity to gain significant efficiency by compressing more in the periphery and less in the center. We propose a practical and scalable method to use such a technique for video streaming service over the Internet. The essential idea is to use a commodity webcam on the user side to provide real-time gaze feedback to the server with the server sending appropriately coded video to the client player. We develop a multi-resolution video coding approach that is scalable in that it is possible to pre-code the video in a small number of copies for a given set of resolutions. The coding approach is designed to match the error performance of an eye tracker built using commodity webcams. We demonstrate that the technique is energy efficient and thus usable in mobile devices. We develop a methodology for performance evaluation of such a system when network budgets may vary and video quality may fluctuate. Finally, we present a comprehensive user study that demonstrates a bandwidth reduction of a factor of 2 for the same user satisfaction.

Benchmarking resource usage for spectrum sensing on commodity mobile devices

Abstract: Effective management of various white space spectra may require spectrum sensing at finer spatial granularity than is feasible with expensive laboratory-grade spectrum sensors. To enable this, we envision a future where commodity mobile devices would be capable of spectrum sensing as needed, possibly via crowd-sourcing. However, since mobile devices are resource limited, understanding their resource usage in this set up is important, specifically in terms of overall latency and energy usage. In this work, we carry out a comprehensive performance benchmarking study using 4 different USB-powered software radios and 2 common smartphone/ embedded computers as mobile spectrum sensing platforms. The study evaluates latency and energy usage using a suite of commonly used sensing algorithms specifically targeting TV white space spectrum. The study shows that latency due to sensing and computation and related energy usage are both modest.

ExBox: Experience Management Middlebox for Wireless Networks

Abstract: Enterprise wireless networks face significant challenges to deliver Quality-of-Experience (QoE) with the variety of mobile applications. One of the fundamental challenges is that the traditional definition of network capacity (often defined as throughput capacity) is not sufficient to reflect applications' requirements in wireless networks. In this paper, we propose to rethink the network capacity of wireless networks to better incorporate QoE. Specifically, we first propose a novel concept of an Experiential Capacity Region (ExCR) for wireless networks. ExCR is defined as a set of simultaneous application flows whose QoE requirements can be satisfied by the network. Next, we present the infrastructure based ExBox system that measures per-application QoE metrics and determines the ExCR for wireless networks to better serve a set of mobile application flows. In its core, ExBox employs light-weight machine learning techniques that are tailored for dynamic wireless environments. Through both large-scale simulations and extensive real-life experiments on WiFi and LTE networks, we show that ExBox delivers QoE in admission control decision with a precision of ≈ 0.8 - 0.9, even when clients experience diverse channel quality. Moreover, ExBox quickly adapts to changing network environments without much overhead.

LTE-Xtend: scalable support of M2M devices in cellular packet core

Abstract: M2M (machine-to-machine) communications are bringing new challenges in the cellular networks as billions of such devices will need to be supported but at a fraction of the cost of today's smartphones. Analysis shows that while many of these devices generate little data load on the network, their control signaling load and memory/CPU resource consumption due to tunnel maintenance in the cellular core could still be significant. To address this scalability issue, we propose a modified packet core architecture for LTE networks called LTE-Xtend that customizes control message handling and tunnel management for M2M traffic. Evaluations using OpenAirInterface demonstrates significant scalability benefits in using LTE-Xtend.

Analog front end design for tags in backscatter-based tag-to-tag communication networks

Abstract: Backscatter-based tag-to-tag communication (BBTT) is a paradigm wherein radio-less devices communicate with each other by using purely passive backscatter modulation. This allows for highly inexpensive and low power devices. Traditional backscattering devices like RFID tags are designed to communicate directly with an active reader leading to a centralized framework centered on the reader. Under a BBTT network, the tags talk to each other using backscattering in the presence of an external excitation signal, which can come from multiple sources (e.g., dedicated exciters, WiFi access points, TV towers, or cell phone towers). The two main components that determine the range and robustness of a passive tag-to-tag link are the power harvesting and demodulation circuit blocks in the analog front end (AFE). In this paper, we investigate the design constraints, optimization goals, and tradeoffs in the design of the AFE for BBTT tags. We first analyze the BBTT link theoretically and then verify the predicted optimal AFE parameters by simulations.

Designing a Cloud-Based Infrastructure for Spectrum Sensing: A Case Study for Indoor Spaces

Abstract: We argue that spectrum sensing on mobile clients will be both necessary and feasible if we wish to manage the white space spectrum optimally in indoor spaces. We demonstrate the necessity with a set of empirical measurements showing the need for fine grained sensing. We demonstrate the feasibility by building a spectrum sensing infrastructure that collects measurements from sensing devices to analyze and better use spectrum resources. The infrastructure consists of mobile spectrum sensors that are built using DTV receiver dongles interfaced with Android-based mobile devices and a cloud-based central server to manage such sensing devices. We also show results about resource consumption (energy, network overhead) involved in operating such sensors. The vision is ultimately creating a system where mobile devices perform part-time spectrum sensing in a coordinated fashion under the control of a central spectrum manager. We lay out the research challenges based on our initial prototyping and benchmarking experience.

TopoMan: Global Network Visibility in the Presence of Middleboxes (A Graybox Approach)

Abstract: Software Defined Networks (SDN) provide vital benefits to network administrators by offering global visibility and network-wide control over the switching infrastructure of the network. It is rather much difficult to obtain the same benefits in the presence of middleboxes (MBs), due to (i) lack of a proper topology discovery mechanism in environments with a mix of forwarding devices and middleboxes. (ii) lack of generic APIs to abstract and gain control on these rigid and heterogeneous third-party middleboxes (iii) lack of a generic network infrastructure framework to monitor and verify any specific device or path connectivity status in the network. These limitations make automation of network operations such as, network-wide monitoring, policy enforcement and rule-placement much difficult to handle. Hence, there is a greater urge even from middlebox vendors, to better handle the control and visibility aspects of the network in presence of middleboxes. In this paper, we propose a Unified network infrastructure framework for gaining global network visibility, by discovering the network topology in the presence of middleboxes, along with a framework to support the end-to-end path connectivity verification, independent of SDN. We have also addressed security aspects and provided necessary APIs to support our framework.