TV Whitespaces, recently opened up by the Federal Communications Commission (FCC) for unlicensed use, are seen as a potential cellular offload and/or standalone mechanism, especially in dense metros where the demand for throughput is high. In this paper, we use real data collected from whitespaces databases to empirically demonstrate features unique to whitespaces-power-spectrum tradeoff and spatial variation in spectrum availability. From this study, we conclude the need for whitespaces-specific adaptations to cellular networks so as to be able to extract maximum throughput and guarantee reliability. To tackle the effects of the power-spectrum tradeoff, we propose a novel base-station design that specifically uses low-power transmitters as a means to maximize throughput. This design co-locates and networks together many low-powered mode-I devices to act as a multiple-antenna array. We estimate the size of the array required to meet typical rate targets, and show that the array design significantly outperforms traditional designs in terms of throughput for a given cost. We then turn our attention to spatial variability and study its impact on the problem of locating base stations in a whitespaces network. Here, we propose spectrum-aware placement algorithms for whitespaces, which account for this spatial variability along with key parameters like user density. We show that such algorithms clearly outperform traditional placement algorithms and improve network coverage in this band.

We design and implement a novel system called Async, which enables a mobile network operator (MNO) to efficiently manage the growth of mobile data by leveraging the delay-elastic nature of certain applications and the price-sensitive nature of certain users. Specifically, Async introduces an alternate “asynchronous” content-delivery paradigm for heavy content (e.g., videos), and facilitates an MNO to negotiate with users a delay in delivery in exchange for appropriate incentives. The MNO uses the negotiated delays to actively manage Async flows to reduce congestion and improve the quality-of-experience (QoE) of both delayed and regular flows. We show that in comparison to state-of-the-art, Async's network-based flow management enhances QoE for more than 30% of the regular flows, with up to 60% improvement in per-flow QoE metric, while still meeting the negotiated delivery times of 95% of the delayed flows. Async also lowers the delivery times of delayed flows by ∼67% and significantly increases robustness to traffic unpredictability. Our design is robust to disconnections and does not require any modifications to existing network infrastructure and protocols. Our prototype deployment (using Apache's mod_proxy and an Android app) on live networks confirms Async's efficacy in meeting EDTs for diverse deployment scenarios.

In this work, we demonstrate the design and implementation of a novel system called Async, which enables a mobile network operator (MNO) to efficiently manage the growth of mobile data. For this, we enable an opportunistic delivery model for the MNOs by leveraging the delay-elastic nature of certain applications such as video downloads, and the price-sensitive nature of certain users. Specifically, in Async, we enable an alternate content delivery paradigm that facilitates an MNO to control when, and at what price, the content is delivered to the users. In our system, users can select a price and expected delivery time (or EDT) option from a multitude of choices. We develop a prototype of such a system by extending Apache's mod_proxy module and by developing a service on the Android platform without requiring any modifications to existing network infrastructure or protocols. We demonstrate two applications using such a service: (1) download of large files, e.g., software updates, movie files, and (2) an educational App that downloads educational content on mobile devices.

The Wireless Network Cloud (WNC) [1] is a novel network architecture where wireless base-stations are implemented as software modules and multiple base-stations are consolidated to a single centralized computing platform. Due to the time-varying and random nature of base-station traffic, consolidation leads to multiplexing of statistically-varying basestation loads on a common hardware platform. In turn, this can lead to significant hardware reduction in the consolidated platform when compared to the distributed network. This paper represents the first analysis of such consolidation gain. Through traffic simulation experiments, we quantify the extent and variation of this multiplexing gain in a WiMAX base-station network in different traffic conditions. We show experimentally, that the obtained gain increases linearly with network size (number of base-stations). Further, we also show that the consolidation gain is higher when the consolidated base-stations face higher traffic intensity.

TV Whitespaces, recently opened up by the FCC for unlicensed use by wireless devices, are seen as a potential cellular offload solution, especially in dense metros. However, under the new database-driven guidelines, there are typically very few whitespace bands available in such dense metros to a high-powered fixed device, which plays the role of a cellular base station in whitespaces. To address the lack of degrees-of-freedom (DoF) with this traditional architecture of one high-powered serving device, we propose a novel base station design that co-locates and networks together many low-powered devices to act as a multiple-antenna array. Lower-powered whitespace devices have access to more spectral DoF, a property that is unique to whitespaces. In the first part of the paper, we solve an array design problem where we estimate the size of the array required to meet long-term (worst-case) throughput targets. Using extensive simulations, we show that by effectively exploiting both spatial and spectral DoF, the array design outperforms the traditional design in most network conditions. Specifically, the proposed design can support throughputs of the order of a WiMAX cell running applications such as high-definition television. In the second part of the paper, we turn our attention to the operational aspects of such a design. Recognizing that the proposed array can potentially contain hundreds of elements, we propose a dynamic ON-OFF power control algorithm that operates in conjunction with the MaxWeight data scheduling algorithm and responds to the current network state - queues and channels - of the system, thus making the system power-efficient.

The Hopper-Blum (HB) protocol, which uses noised linear parities of a shared key for authentication, has been proposed for light-weight applications such as RFID. Recently, algorithms for decoding linear codes have been specially designed for use in passive attacks on the HB protocol. These linear coding attacks have resulted in the need for long keys in the HB protocol, making the protocol too complex for RFID in some cases. In this work, we propose the NLHB protocol, which is a non-linear variant of the HB protocol. The non-linearity is such that passive attacks on the NLHB protocol continue to be provably hard by reduction. However, the linear coding attacks cannot be directly adapted to the proposed NLHB protocol because of the non-linearity. Hence, smaller key sizes appear to be sufficient in the NLHB protocol for the same level of security as the HB protocol. We construct specific instances of the NLHB protocol and show that they can be significantly less complex for implementation than the HB protocol, in spite of the non-linearity. Further, we propose an extension, called the NLHB+ protocol, that is provably secure against a class of active attack models.