Chen-Nee Chuah

Bio: Chen-Nee Chuah is an academic researcher from University of California, Davis. The author has contributed to research in topics: Wireless network & Network management. The author has an hindex of 45, co-authored 228 publications receiving 9415 citations. Previous affiliations of Chen-Nee Chuah include Sprint Corporation & University of California, Berkeley.

Capacity scaling in MIMO wireless systems under correlated fading

Abstract: Previous studies have shown that single-user systems employing n-element antenna arrays at both the transmitter and the receiver can achieve a capacity proportional to n, assuming independent Rayleigh fading between antenna pairs. We explore the capacity of dual-antenna-array systems under correlated fading via theoretical analysis and ray-tracing simulations. We derive and compare expressions for the asymptotic growth rate of capacity with n antennas for both independent and correlated fading cases; the latter is derived under some assumptions about the scaling of the fading correlation structure. In both cases, the theoretic capacity growth is linear in n but the growth rate is 10-20% smaller in the presence of correlated fading. We analyze our assumption of separable transmit/receive correlations via simulations based on a ray-tracing propagation model. Results show that empirical capacities converge to the limit capacity predicted from our asymptotic theory even at moderate n = 16. We present results for both the cases when the transmitter does and does not know the channel realization.

FIREMAN: a toolkit for firewall modeling and analysis

Abstract: Security concerns are becoming increasingly critical in networked systems. Firewalls provide important defense for network security. However, misconfigurations in firewalls are very common and significantly weaken the desired security. This paper introduces FIREMAN, a static analysis toolkit for firewall modeling and analysis. By treating firewall configurations as specialized programs, FIREMAN applies static analysis techniques to check misconfigurations, such as policy violations, inconsistencies, and inefficiencies, in individual firewalls as well as among distributed firewalls. FIREMAN performs symbolic model checking of the firewall configurations for all possible IP packets and along all possible data paths. It is both sound and complete because of the finite state nature of firewall configurations. FIREMAN is implemented by modeling firewall rules using binary decision diagrams (BDDs), which have been used successfully in hardware verification and model checking. We have experimented with FIREMAN and used it to uncover several real misconfigurations in enterprise networks, some of which have been subsequently confirmed and corrected by the administrators of these networks.

Characterization of failures in an IP backbone

Abstract: We analyze IS-IS routing updates from sprint's IP network to characterize failures that affect IP connectivity. Failures are first classified based on probable causes such as maintenance activities, router-related and optical layer problems. Key temporal and spatial characteristics of each class are analyzed and, when appropriate, parameterized using well-known distributions. Our results indicate that 20% of all failures is due to planned maintenance activities. Of the unplanned failures, almost 30% are shared by multiple links and can be attributed to router-related and optical equipment-related problems, while 70% affect a single link at a time. Our classification of failures according to different causes reveals the nature and extent of failures in today's IP backbones. Furthermore, our characterization of the different classes can be used to develop a probabilistic failure model, which is important for various traffic engineering problems.

Knowledge-based opportunistic forwarding in vehicular wireless ad hoc networks

Abstract: When highly mobile nodes are interconnected via wireless links, the resulting network can be used as a transit network to connect other disjoint ad-hoc networks. In this paper, we compare five different opportunistic forwarding schemes, which vary in their overhead, their success rate, and the amount of knowledge about neighboring nodes that they require. In particular, we present the MoVe algorithm, which uses velocity information to make intelligent opportunistic forwarding decisions. Using auxiliary information to make forwarding decisions provides a reasonable trade-off between resource overhead and performance.

Characterization of failures in an operational IP backbone network

Abstract: As the Internet evolves into a ubiquitous communication infrastructure and supports increasingly important services, its dependability in the presence of various failures becomes critical. In this paper, we analyze IS-IS routing updates from the Sprint IP backbone network to characterize failures that affect IP connectivity. Failures are first classified based on patterns observed at the IP-layer; in some cases, it is possible to further infer their probable causes, such as maintenance activities, router-related and optical layer problems. Key temporal and spatial characteristics of each class are analyzed and, when appropriate, parameterized using well-known distributions. Our results indicate that 20% of all failures happen during a period of scheduled maintenance activities. Of the unplanned failures, almost 30% are shared by multiple links and are most likely due to router-related and optical equipment-related problems, respectively, while 70% affect a single link at a time. Our classification of failures reveals the nature and extent of failures in the Sprint IP backbone. Furthermore, our characterization of the different classes provides a probabilistic failure model, which can be used to generate realistic failure scenarios, as input to various network design and traffic engineering problems.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Fading correlation and its effect on the capacity of multielement antenna systems

Abstract: We investigate the effects of fading correlations in multielement antenna (MEA) communication systems. Pioneering studies showed that if the fades connecting pairs of transmit and receive antenna elements are independently, identically distributed, MEAs offer a large increase in capacity compared to single-antenna systems. An MEA system can be described in terms of spatial eigenmodes, which are single-input single-output subchannels. The channel capacity of an MEA is the sum of capacities of these subchannels. We show that the fading correlation affects the MEA capacity by modifying the distributions of the gains of these subchannels. The fading correlation depends on the physical parameters of MEA and the scatterer characteristics. In this paper, to characterize the fading correlation, we employ an abstract model, which is appropriate for modeling narrow-band Rayleigh fading in fixed wireless systems.