Chunyi Peng

Utilization and fairness in spectrum assignment for opportunistic spectrum access

The Open Spectrum approach to spectrum access can achieve near-optimal utilization by allowing devices to sense and utilize available spectrum opportunistically. However, a naive distributed spectrum assignment can lead to significant interference between devices. In this paper, we define a general framework that defines the spectrum access problem for several definitions of overall system utility. By reducing the allocation problem to a variant of the graph coloring problem, we show that the global optimization problem is NP-hard, and provide a general approximation methodology through vertex labeling. We examine both a centralized strategy, where a central server calculates an allocation assignment based on global knowledge, and a distributed approach, where devices collaborate to negotiate local channel assignments towards global optimization. Our experimental results show that our allocation algorithms can dramatically reduce interference and improve throughput (as much as 12-fold). Further simulations show that our distributed algorithms generate allocation assignments similar in quality to our centralized algorithms using global knowledge, while incurring substantially less computational complexity in the process.

Collaboration and fairness in opportunistic spectrum access

The open spectrum approach to spectrum access can achieve near-optimal spectrum utilization by letting users sense and utilize available spectrum opportunistically. However, naive spectrum assignment can lead to significant interference. We propose a network controlled spectrum access scheme where users behave collaboratively to optimize spectrum allocation for the entire network. We develop a graph-theoretical model to characterize the spectrum access problem under a number of different optimization functions, and devise rules for users to utilize available spectrum while avoiding interference with their neighbors. Experimental results confirm that user collaboration yields significant benefits (as much as 50% improvement) in opportunistic spectrum access.

Traffic-driven power saving in operational 3G cellular networks

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.

A scalable micro wireless interconnect structure for CMPs

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 1000-core 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 wired mesh designs.

VDN: Virtual machine image distribution network for cloud data centers

Cloud computing centers face the key challenge of provisioning diverse virtual machine instances in an elastic and scalable manner. To address this challenge, we have performed an analysis of VM instance traces collected at six production data centers during four months. One key finding is that the number of instances created from the same VM image is relatively small at a given time and thus conventional file-based p2p sharing approaches may not be effective. Based on the understanding that different VM image files often have many common chunks of data, we propose a chunk-level Virtual machine image Distribution Network (VDN). Our distribution scheme takes advantage of the hierarchical network topology of data centers to reduce the VM instance provisioning time and also to minimize the overhead of maintaining chunk location information. Evaluation shows that VDN achieves as much as 30-80× speed up for large VM images under heavy traffic.

Point&Connect: intention-based device pairing for mobile phone users

Point&Connect (P&C) offers an intuitive and resilient device pairing solution on standard mobile phones. Its operation follows the simple sequence of point-andconnect: when a user plans to pair her mobile phone with another device nearby, she makes a simple hand gesture that points her phone towards the intended target. The system will capture the users gesture, understand the target selection intention, and complete the device pairing. P&C is intention-based, intuitive, and reduces user efforts in device pairing. The main technical challenge is to come up with a simple system technique to effectively capture and understand the intention of the user, and pick the right device among many others nearby. It should further work on any mobile phones or small devices without relying on infrastructure or special hardware. P&C meets this challenge with a novel collaborative scheme to measure maximum distance change based on acoustic signals. Using only a speaker and a microphone, P&C can be implemented solely in user-level software and work on COTS phones. P&C adds additional mechanisms to improve resiliency against imperfect user actions, acoustic disturbance, and even certain malicious attacks. We have implemented P&C in Windows Mobile phones and conducted extensive experimental evaluation, and showed that it is a cool and effective way to perform device pairing.

Ubiquitous keyboard for small mobile devices: harnessing multipath fading for fine-grained keystroke localization

A well-known bottleneck of contemporary mobile devices is the inefficient and error-prone touchscreen keyboard. In this paper, we propose UbiK, an alternative portable text-entry method that allows user to make keystrokes on conventional surfaces, e.g., wood desktop. UbiK enables text-input experience similar to that on a physical keyboard, but it only requires a keyboard outline printed on the surface or a piece of paper atop. The core idea is to leverage the microphone on a mobile device to accurately localize the keystrokes. To achieve fine-grained, centimeter scale granularity, UbiK extracts and optimizes the location-dependent multipath fading features from the audio signals, and takes advantage of the dual-microphone interface to improve signal diversity. We implement UbiK as an Android application. Our experiments demonstrate that UbiK is able to achieve above 95% of localization accuracy. Field trial involving first-time users shows that UbiK can significantly improve text-entry speed over current on-screen keyboards.

Enhancing reliability to boost the throughput over screen-camera links

With the rapid proliferation of camera-equipped smart devices (e.g., smartphones, pads, tablets), visible light communication (VLC) over screen-camera links emerges as a novel form of near-field communication. Such communication via smart devices is highly competitive for its user-friendliness, security, and infrastructure-less (i.e., no dependency on WiFi or cellular infrastructure). However, existing approaches mostly focus on improving the transmission speed and ignore the transmission reliability. Considering the interplay between the transmission speed and reliability towards effective end-to-end communication, in this paper, we aim to boost the throughput over screen-camera links by enhancing the transmission reliability. To this end, we propose RDCode, a robust dynamic barcode which enables a novel packet-frame-block structure. Based on the layered structure, we design different error correction schemes at three levels: intra-blocks, inter-blocks and inter-frames, in order to verify and recover the lost blocks and frames. Finally, we implement RDCode and experimentally show that RDCode reaches a high level of transmission reliability (e.g., reducing the error rate to 10%) and yields a at least doubled transmission rate, compared with the existing state-of-the-art approach COBRA.

Energy-based rate adaptation for 802.11n

Rate adaptation (RA) has been used to achieve high goodput. In this work, we explore to use RA for energy efficiency in 802.11n NICs. We show that current MIMO RA algorithms are not energy efficient for NICs despite ensuring high throughput. The fundamental problem is that, the high-throughput setting is not equivalent to the energy-efficient one. Marginal throughput gain may be realized at high energy cost. We propose EERA, an energy-based RA solution that trades off goodput for energy savings at NICs. Our experiments have confirmed its energy savings at NICs while keeping the cost at the device level and across clients acceptable.

Pharos: enable physical analytics through visible light based indoor localization

Indoor physical analytics calls for high-accuracy localization that existing indoor (e.g., WiFi-based) localization systems may not offer. By exploiting the ever increasingly wider adoption of LED lighting, in this paper, we study the problem of using visible LED lights for accurate localization. We identify the key challenges and tackle them through the design of Pharos. In particular, we establish and experimentally verify an optical channel model suitable for localization. We adopt BFSK and channel hopping to achieve reliable location beaconing from multiple, uncoordinated light sources over shared light medium. Preliminary evaluation shows that Pharos achieves the 90th percentile localization accuracy of 0.4m and 0.7m for two typical indoor environments. We believe visible light based localization holds the potential to significantly improve the position accuracy, despite few potential issues to be conquered in real deployment.