Cheng-Lin Tsao

Securing Wireless Data Networks against Eavesdropping using Smart Antennas

In this paper, we focus on securing communication over wireless data networks from malicious eavesdroppers, using smart antennas. While conventional cryptography based approaches focus on hiding the meaning of the information being communicated from the eavesdropper, we consider a complimentary class of strategies that limit knowledge of the existence of the information from the eavesdropper. We profile the performance achievable using simple beamforming strategies using a newly defined metric called exposure region. We then present three strategies within the context of an approach called virtual arrays of physical arrays to significantly improve the exposure region performance of a wireless LAN environment. Using simulations and analysis, we validate and evaluate the proposed strategies.

SmartVNC: an effective remote computing solution for smartphones

While a remote computing solution such as VNC is an effective technology for PC users to access a remote computer, it is not as effective while being used from smartphones. In this paper, we propose techniques to improve remote computing from smartphones that help deliver near-PC level experience to users. We introduce a key building block called smart-macros that have the robustness of application macros but at the same time possess the generality of raw macros. Using smart-macros we design and prototype SmartVNC, a remote computing solution for smartphones. We show using experimental studies and a trace based analysis of real user activity, that SmartVNC can improve user experience considerably.

Aegis: physical space security for wireless networks with smart antennas

In this paper, we focus on securing communication over wireless data networks from malicious eavesdroppers by using smart antennas. While conventional cryptography-based approaches focus on hiding the meaning of the information being communicated from the eavesdropper, we consider a complimentary class of strategies that limit knowledge of the existence of the information from the eavesdropper. We profile the performance achievable with simple beamforming strategies using a newly defined metric called exposure region. We then present three strategies within the context of an approach called Aegis, which uses virtual arrays of physical arrays to significantly improve the exposure region performance of a wireless LAN environment. Using simulations, analysis, and field trials, we validate and evaluate the proposed strategies.

VoIP over Wi-Fi Networks: Performance Analysis and Acceleration Algorithms

The expected VoIP call capacity in a one hop IEEE 802.11b network with G.711 voice codec is about 85 simultaneous calls, but the actual observed capacity is only 5 calls even at the highest data rate and under zero loss conditions. In this paper we analyze the reasons behind this inferior performance of VoIP traffic. We also present algorithms at the medium access control layer to improve the observed call capacity. Using ns-2 based simulations, we evaluate the algorithms and show that performance improvements of more than 300% can be achieved. Finally, using a testbed implementation of one of the proposed algorithms, we show its feasibilty in real world VoIP implementations.

Improving VoIP call capacity over IEEE 802.11 networks

The expected VoIP call capacity in a one hop IEEE 802.11b network with G.711 voice codec is about 85 simultaneous calls, but the actual observed capacity is only 5 calls even at the highest data rate and under zero loss conditions. In this paper we analyze the reasons behind this inferior performance of VoIP traffic. We also present algorithms at the medium access control layer to improve the observed call capacity. Finally, using ns-2 based simulations, we evaluate the algorithms and show that performance improvements of up to 300% can be achieved.

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

\times

On effectively exploiting multiple wireless interfaces in mobile hosts

× throughput) performance improvements it provides in real-world experiments. We conduct both theoretical analysis and extensive experiments to show that super-aggregation is able to improve throughput beyond the sum of the parts under most of the cases.