The use of smartphones as voice recorders has made it easy to record audios as proof of conversations, but sharing of such audio evidence incurs speech and voice privacy risks. However, protecting speech/voice privacy without losing audio authenticity is challenging. The conventional post-process redaction and voice conversion of audio recordings, which invalidate their original signatures, make the audio unverifiable and prone to tampering. In this paper, we present Overo, an audio recording/sharing solution that supports privacy processing without losing audio authenticity. Overo records a realtime audio stream in the standard AAC-encoded format and allows privacy post-processing prior to sharing of audios while keeping their original signatures valid (even after the post redaction and voice conversion), guaranteeing no tampering since the time of their recording. Therefore, users can post-process their recordings to desired levels of privacy on speech (what content to redact) and speakers (whose voice to disguise) at the time of audio release, and still prove their authenticity. Overo is readily implementable in today's commodity smartphones. Our prototype on iPhones/Android phones demonstrates the production of AAC-compliant, tamperproof, and self-authenticating audios with speech/voice privacy protected based on users' post-recording decisions.

With various IoT cameras today, sharing of their video evidences, while benefiting the public, threatens the privacy of individuals in the footage. However, protecting visual privacy without losing video authenticity is challenging. The conventional post-process blurring would open the door for posterior fabrication, whereas the realtime blurring results in poor quality, low-frame-rate videos due to the limited processing power of commodity cameras. This paper presents Pinto, a software-based solution for producing privacy-protected, forgery-proof, and high-frame-rate videos using low-end IoT cameras. Pinto records a realtime video stream at a fast rate and allows post-processing for privacy protection prior to sharing of videos while keeping their original, realtime signatures valid even after the post blurring, guaranteeing no content forgery since the time of their recording. Pinto is readily implementable in today's commodity cameras. Our prototype on three different embedded devices, each deployed in a specific application context---on-site, vehicular, and aerial surveillance---demonstrates the production of privacy-protected, forgery-proof videos with frame rates of 17--24 fps, comparable to those of HD videos.

Base station (BS) networks in 3G cellular infrastructure do not consume energy in proportion to their carried traffic load. Our measurements show that the 3G traffic exhibits high fluctuations both in time and over space, thus incurring energy waste. In this paper, we propose Green base station networks (GreenBSN) to approximate network-wide energy proportionality using non-load-adaptive BSes. The instrument is a traffic-driven approach. By leveraging the inherent temporal-spatial traffic dynamics and node deployment heterogeneity, we power off under-utilized BSes under light traffic. Our evaluation on four regional 3G networks shows that GreenBSN yields up to 53 percent energy savings in dense large cities and 23 percent in sparsely deployed regions.

This work experimentally studies the energy consumption of multiple-antenna MIMO 802.11 devices. Our measurements reveal an increase in power consumption and speed with the number of antennas. State of the art proposals have limitations to save energy in MIMO 802.11 networks. First, they focus on either maximizing speed or minimizing power consumption. Second, they only seek to minimize energy for the receiver side of mobile devices. As a result, they present limitations to utilize MIMO speed gains and to save energy in MIMO 802.11 infrastructure. To this end, we design Collaborative MIMO Energy Save (CMES), which seeks to identify the transmitter-receiver most energy efficient antenna setting, at runtime. Our experiments with commodity MIMO 802.11n testbeds confirm that CMES can provide energy savings in real scenarios.

Rate adaptation is a mechanism unspecified by the IEEE 802.11 standards, yet critical to the system performance by exploiting the multirate capability at the physical layer. In this paper, we conduct a systematic experimental study on rate adaptation over 802.11 wireless networks. Our key contributions are as follows: First, we present a critique on popular design guidelines adopted by many practical algorithms and we uncover their limitations. Our study reveals that these seemingly correct guidelines can be misleading in practice, thus incurring significant performance penalty in certain scenarios. Second, we study the short-term channel dynamics and explore how they guide rate adaptation. To this end, we design and implement a new History-Aware Robust Rate Adaptation Algorithm (HA-RRAA). HA-RRAA uses short-term loss ratio to opportunistically guide its rate change decisions, a cost-effective adaptive RTS filter to prevent collision losses from triggering rate decrease and an adaptive time window to limit transmissions at high loss rates. Our extensive experiments show that HA-RRAA outperforms popular algorithms in all tested scenarios, with goodput gains up to 51.9 percent in field trials.

In this paper, we use real experiments to study multiple-input-multiple-output (MIMO) 802.11n rate adaptation (RA) on a programmable access point (AP) platform. Our case study shows that existing RA solutions offer much lower throughput than even a fixed-rate scheme. It is proven that all such algorithms are MIMO-mode oblivious; they do not differentiate spatial diversity and spatial multiplexing modes. We first design MiRA, a novel MIMO RA scheme that zigzags between intra- and inter-MIMO modes to address MIMO 802.11n dynamics. Second, we examine a window-based RA solution, which runs an independent RA in each MIMO mode in parallel and a signal-to-noise ratio (SNR)-based MIMO RA that differentiates modes using SNR measurements. Our experiments show that MIMO-mode aware designs outperform MIMO-mode oblivious RAs in various settings, with goodput gains up to 73.5% in field trials.

We study the problem of scalable monitoring of operational 3G wireless networks. Threshold-based performance monitoring in large 3G networks is very challenging for two main factors: large network scale and dynamics in both time and spatial domains. A fine-grained threshold setting (e.g., perlocation hourly) incurs prohibitively high management complexity, while a single static threshold fails to capture the network dynamics, thus resulting in unacceptably poor alarm quality (up to 70% false/miss alarm rates). In this paper, we propose a scalable monitoring solution, called threshold-compression that can characterize the location- and time-specific threshold trend of each individual network element (NE) with minimal threshold setting. The main insight is to identify groups of NEs with similar threshold behaviors across location and time dimensions, forming spatial-temporal clusters to reduce the number of thresholds while maintaining acceptable alarm accuracy in a large-scale 3G network. Our evaluations based on the operational experience on a commercial 3G network have demonstrated the effectiveness of the proposed solution. We are able to reduce the threshold setting up to 90% with less than 10% false/miss alarms.

eXpressive Internet Architecture (XIA) [1] is an architecture that natively supports multiple communication types and allows networks to evolve their abstractions and functionality to accommodate new styles of communication over time. XIA embeds an elegant mechanism for handling unforeseen communication types for legacy routers.

This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques on the 3GPP Long-Term Evolution (LTE) downlink. We impose the LTE MIMO constraint of selecting only one MIMO mode (spatial multiplexing or transmit diversity) per user per transmission time interval (TTI). First, we address the optimal MIMO mode selection (multiplexing or diversity) per user in each TTI in order to maximize the proportional fair (PF) criterion adapted to the additional frequency and spatial domains. We prove that both single-user (SU-) and multi-user (MU-) MIMO FDPS problems under the LTE requirement are NP-hard. We therefore develop two types of approximation algorithms (ones with full channel feedback and the others with partial channel feedback), all of which guarantee provable performance bounds for both SU- and MU-MIMO cases. Based on 3GPP LTE system model simulations, our approximation algorithms that take into account both spatial and frequency diversity gains outperform the exact algorithms that do not exploit the potential spatial diversity gain. Moreover, the approximation algorithms with partial channel feedback achieve comparable performance (with only 1-6 percent performance degradation) to the ones with full channel feedback, while significantly reducing the channel feedback overhead by nearly 50 percent.

We study the challenging problem of strategic content placement in a dynamic MANET. Existing content placement techniques cannot cope with such network dynamics since they are designed for fixed networks. Opportunistic caching approaches are insufficient as they do not actively manage contents for certain goals. In this paper, we present a novel content management approach called LACMA, which leverages the location information available to mobile devices via GPS. The main idea of LACMA is to bind data to geographic location (as opposed to network nodes). This location-based strategy decouples the content placement problem from the changing network topology, and allows us to design an optimization framework even in a dynamic MANET environment. We present key components of LACMA used for strategic content placement and content-location binding (through proactive content push). We evaluate LACMA and compare its performance with existing caching schemes and show that LACMA considerably outperforms existing schemes over a wide range of scenarios.

Base stations (BSes) in the 3G cellular network are not energy proportional with respect to their carried traffic load. Our mea- surements show that 3G traffic exhibits high fluctuations both in time and over space, thus incurring energy waste. In this paper, we propose a profile-based approach to green cellular infrastruc- ture. We profile BS traffic and approximate network-wide energy proportionality using non-load-adaptive BSes. The instrument is to leverage temporal-spatial traffic diversity and node deployment heterogeneity, and power off under-utilized BSes under light traf- fic. Our evaluation on four regional 3G networks shows that this simple scheme yields up to 53% energy savings in a dense large city and 23% in a sparse, mid-sized city.

Threshold-based performance monitoring in large 3G networks is very challenging for two main factors: large network scale and dynamics in both time and spatial domains. There exists a fundamental tradeoff between the size of threshold settings and the alarm quality. In this paper, we propose a scalable monitoring solution, called threshold-compression that characterizes the tradeoff via intelligent threshold aggregation. The main insight behind our solution is to identify groups of network elements with similar threshold behaviors across location and time dimensions, thus forming spatial-temporal clusters and generating the associated compressed thresholds within the optimization framework. Our evaluations on a commercial 3G network have demonstrated the effectiveness of our threshold-compression solution, e.g., threshold setting reduction up to 90% within 10% false/miss alarms.

This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques on the 3GPP long term evolution (LTE) downlink. We impose the LTE MIMO constraint of selecting only one MIMO mode (spatial multiplexing or transmit diversity) per user per transmission time interval (TTI). First, we address the optimal MIMO mode selection (multiplexing or diversity) per user in each TTI in order to maximize the proportional fair (PF) criterion extended to frequency and spatial domains. We prove that the SU-MIMO (single-user MIMO) FDPS problem under the LTE requirement is NP-hard and therefore, we develop two approximation algorithms (one with full channel feedback and the other with partial channel feedback) with provable performance bounds. Based on 3GPP LTE system model simulations, the approximation algorithm with partial channel feedback is shown to have comparable performance to the one with full channel feedback, while significantly reducing the channel feedback overhead by nearly 50%.

With the power consumption issue of mobile handset taken into account, single-carrier FDMA (SC-FDMA) has been selected for 3GPP long-term evolution (LTE) uplink multiple access scheme. Like in OFDMA downlink, it enables multiple users to be served simultaneously in uplink as well. However, its single carrier property requires that all the subcarriers allocated to a single user must be contiguous in frequency within each time slot. This contiguous allocation constraint limits the scheduling flexibility, and frequency-domain packet scheduling algorithms in such system need to incorporate this constraint while trying to maximize their own scheduling objectives. In this paper we explore this fundamental problem of LTE SC-FDMA uplink scheduling by adopting the conventional time-domain proportional fair algorithm to maximize its objective (i.e. proportional fair criteria) in the frequency-domain setting. We show the NP-hardness of the frequency-domain scheduling problem under this contiguous allocation constraint and present a set of practical algorithms fine tuned to this problem. We demonstrate that competitive performance can be achieved in terms of system throughput as well as fairness perspective, which is evaluated using 3GPP LTE system model simulations.

This paper describes an unconventional way to apply wireless networking in emerging technologies. It makes the case for using a two-tier hybrid wireless/wired architecture to interconnect hundreds to thousands of cores in chip multiprocessors (CMPs), where current interconnect technologies face severe scaling limitations in excessive latency, long wiring, and complex layout. We propose a recursive wireless interconnect structure called the WCube that features a single transmit antenna and multiple receive antennas at each micro wireless router and offers scalable performance in terms of latency and connectivity. We show the feasibility to build miniature on-chip antennas, and simple transmitters and receivers that operate at 100 − 500 GHz sub-terahertz frequency bands. We also devise new two-tier wormhole based routing algorithms that are deadlock free and ensure a minimum-latency route on a 1000core on-chip interconnect network. Our simulations show that our protocol suite can reduce the observed latency by 20 % to 45%, and consumes power that is comparable to or less than current 2-D wiredmeshdesigns.

Vehicular ad hoc networks (VANETs) are envisioned to provide us with numerous interesting services in the near future. One of the most promising applications is the dissemination of commercial advertisements via car-to-car communication. However, due to non-cooperative behavior of selfish nodes or even malicious ones in the real-world scenario, such vehicular advertisement system cannot be realized unless proper incentives and security mechanisms are taken into consideration. This paper presents Signature-Seeking Drive (SSD), a secure incentive framework for commercial ad dissemination in VANETs. Unlike currently proposed incentive systems, SSD does not rely on tamper-proof hardware or game theoretic approaches, but leverages a PKI (Public Key Infrastructure) to provide secure incentives for cooperative nodes. With a set of ad dissemination designs proposed, we demonstrate that our SSD is robust in both incentive and security perspectives.