arXiv subjects

Mung Chiang

Publications and source records attributed to Mung Chiang.

At least 73 records · Page 4Linked to original sources

arXiv2015

RAPTOR: Routing Attacks on Privacy in Tor

The Tor network is a widely used system for anonymous communication. However, Tor is known to be vulnerable to attackers who can observe traffic at both ends of the communication path. In this paper, we show that prior attacks are just the tip of the iceberg. We present a suite of new attacks, called Raptor, that can be launched by Autonomous Systems (ASes) to compromise user anonymity. First, AS-level adversaries can exploit the asymmetric nature of Internet routing to increase the chance of observing at least one direction of user traffic at both ends of the communication. Second, AS-level adversaries can exploit natural churn in Internet routing to lie on the BGP paths for more users over time. Third, strategic adversaries can manipulate Internet routing via BGP hijacks (to discover the users using specific Tor guard nodes) and interceptions (to perform traffic analysis). We demonstrate the feasibility of Raptor attacks by analyzing historical BGP data and Traceroute data as well as performing real-world attacks on the live Tor network, while ensuring that we do not harm real users. In addition, we outline the design of two monitoring frameworks to counter these attacks: BGP monitoring to detect control-plane attacks, and Traceroute monitoring to detect data-plane anomalies. Overall, our work motivates the design of anonymity systems that are aware of the dynamics of Internet routing.

cs.NI↗

arXiv2014

Stock Market Prediction from WSJ: Text Mining via Sparse Matrix Factorization

We revisit the problem of predicting directional movements of stock prices based on news articles: here our algorithm uses daily articles from The Wall Street Journal to predict the closing stock prices on the same day. We propose a unified latent space model to characterize the "co-movements" between stock prices and news articles. Unlike many existing approaches, our new model is able to simultaneously leverage the correlations: (a) among stock prices, (b) among news articles, and (c) between stock prices and news articles. Thus, our model is able to make daily predictions on more than 500 stocks (most of which are not even mentioned in any news article) while having low complexity. We carry out extensive backtesting on trading strategies based on our algorithm. The result shows that our model has substantially better accuracy rate (55.7%) compared to many widely used algorithms. The return (56%) and Sharpe ratio due to a trading strategy based on our model are also much higher than baseline indices.

cs.LG↗

arXiv2013

Mind Your Own Bandwidth: An Edge Solution to Peak-hour Broadband Congestion

Motivated by recent increases in network traffic, we propose a decentralized network edge-based solution to peak-hour broadband congestion that incentivizes users to moderate their bandwidth demands to their actual needs. Our solution is centered on smart home gateways that allocate bandwidth in a two-level hierarchy: first, a gateway purchases guaranteed bandwidth from the Internet Service Provider (ISP) with virtual credits. It then self-limits its bandwidth usage and distributes the bandwidth among its apps and devices according to their relative priorities. To this end, we design a credit allocation and redistribution mechanism for the first level, and implement our gateways on commodity wireless routers for the second level. We demonstrate our system's effectiveness and practicality with theoretical analysis, simulations and experiments on real traffic. Compared to a baseline equal sharing algorithm, our solution significantly improves users' overall satisfaction and yields a fair allocation of bandwidth across users.

cs.NI↗

arXiv2013

Learning about social learning in MOOCs: From statistical analysis to generative model

We study user behavior in the courses offered by a major Massive Online Open Course (MOOC) provider during the summer of 2013. Since social learning is a key element of scalable education in MOOCs and is done via online discussion forums, our main focus is in understanding forum activities. Two salient features of MOOC forum activities drive our research: 1. High decline rate: for all courses studied, the volume of discussions in the forum declines continuously throughout the duration of the course. 2. High-volume, noisy discussions: at least 30% of the courses produce new discussion threads at rates that are infeasible for students or teaching staff to read through. Furthermore, a substantial portion of the discussions are not directly course-related. We investigate factors that correlate with the decline of activity in the online discussion forums and find effective strategies to classify threads and rank their relevance. Specifically, we use linear regression models to analyze the time series of the count data for the forum activities and make a number of observations, e.g., the teaching staff's active participation in the discussion increases the discussion volume but does not slow down the decline rate. We then propose a unified generative model for the discussion threads, which allows us both to choose efficient thread classifiers and design an effective algorithm for ranking thread relevance. Our ranking algorithm is further compared against two baseline algorithms, using human evaluation from Amazon Mechanical Turk. The authors on this paper are listed in alphabetical order. For media and press coverage, please refer to us collectively, as "researchers from the EDGE Lab at Princeton University, together with collaborators at Boston University and Microsoft Corporation."

cs.SI↗

arXiv2013

A Survey of Smart Data Pricing: Past Proposals, Current Plans, and Future Trends

Traditionally, network operators have used simple flat-rate broadband data plans for both wired and wireless network access. But today, with the popularity of mobile devices and exponential growth of apps, videos, and clouds, service providers are gradually moving towards more sophisticated pricing schemes. This decade will therefore likely witness a major change in the ways in which network resources are managed, and the role of economics in allocating these resources. This survey reviews some of the well-known past broadband pricing proposals (both static and dynamic), including their current realizations in various consumer data plans around the world, and discusses several research problems and open questions. By exploring the benefits and challenges of pricing data, this paper attempts to facilitate both the industrial and the academic communities' efforts in understanding the existing literature, recognizing new trends, and shaping an appropriate and timely research agenda.

cs.NI↗

arXiv2012

Making 802.11 DCF Optimal: Design, Implementation, and Evaluation

This paper proposes a new protocol called Optimal DCF (O-DCF). Inspired by a sequence of analytic results, O-DCF modifies the rule of adapting CSMA parameters, such as backoff time and transmission length, based on a function of the demand-supply differential of link capacity captured by the local queue length. Unlike clean-slate design, O-DCF is fully compatible with 802.11 hardware, so that it can be easily implemented only with a simple device driver update. Through extensive simulations and real experiments with a 16-node wireless network testbed, we evaluate the performance of O-DCF and show that it achieves near-optimality, and outperforms other competitive ones, such as 802.11 DCF, optimal CSMA, and DiffQ in a wide range of scenarios.

cs.NI↗

arXiv2012

Why Watching Movie Tweets Won't Tell the Whole Story?

Data from Online Social Networks (OSNs) are providing analysts with an unprecedented access to public opinion on elections, news, movies etc. However, caution must be taken to determine whether and how much of the opinion extracted from OSN user data is indeed reflective of the opinion of the larger online population. In this work we study this issue in the context of movie reviews on Twitter and compare the opinion of Twitter users with that of the online population of IMDb and Rotten Tomatoes. We introduce new metrics to show that the Twitter users can be characteristically different from general users, both in their rating and their relative preference for Oscar-nominated and non-nominated movies. Additionally, we investigate whether such data can truly predict a movie's box-office success.

cs.SI↗

arXiv2011

Globally Optimal Distributed Power Control for Nonconcave Utility Maximization

Transmit power control in wireless networks has long been recognized as an effective mechanism to mitigate co-channel interference. Due to the highly non-convex nature, optimal power control is known to be difficult to achieve if a system utility is to be maximized. To date, there does not yet exist a distributed power control algorithm that maximizes any form of system utility, despite the importance of distributed implementation for the wireless infrastructureless networks such as ad hoc and sensor networks. This paper fills this gap by developing a Gibbs Sampling based Asynchronous distributed power control algorithm (referred to as GLAD). The proposed algorithm quickly converges to the global optimal solution regardless of the concavity, continuity, differentiability and monotonicity of the utility function. Same as other existing distributed power control algorithms, GLAD requires extensive message passing among all users in the network, which leads to high signaling overhead and high processing complexity. To address this issue, this paper further proposes a variant of the GLAD algorithm, referred to as I-GLAD, where the prefix "I" stands for infrequent message passing. The convergence of I-GLAD can be proved regardless of the reduction in the message passing rate. To further reduce the processing complexity at each transmitter, we develop an enhanced version of I-GLAD, referred to as NI-GLAD, where only the control messages from the neighboring links are processed. Our simulation results show that I-GLAD approximately converges to the global optimal solution regardless of the type of the system utility function. Meanwhile, the optimality of the solution obtained by NI-GLAD depends on the selection of the neighborhood size.

cs.NI↗

arXiv2009

An Axiomatic Theory of Fairness in Network Resource Allocation

We present a set of five axioms for fairness measures in resource allocation. A family of fairness measures satisfying the axioms is constructed. Well-known notions such as alpha-fairness, Jain's index, and entropy are shown to be special cases. Properties of fairness measures satisfying the axioms are proven, including Schur-concavity. Among the engineering implications is a generalized Jain's index that tunes the resolution of the fairness measure, a new understanding of alpha-fair utility functions, and an interpretation of "larger alpha is more fair". We also construct an alternative set of four axioms to capture efficiency objectives and feasibility constraints.

cs.NI↗

arXiv2009

A Cut-off Phenomenon in Location Based Random Access Games with Imperfect Information

This paper analyzes the behavior of selfish transmitters under imperfect location information. The scenario considered is that of a wireless network consisting of selfish nodes that are randomly distributed over the network domain according to a known probability distribution, and that are interested in communicating with a common sink node using common radio resources. In this scenario, the wireless nodes do not know the exact locations of their competitors but rather have belief distributions about these locations. Firstly, properties of the packet success probability curve as a function of the node-sink separation are obtained for such networks. Secondly, a monotonicity property for the best-response strategies of selfish nodes is identified. That is, for any given strategies of competitors of a node, there exists a critical node-sink separation for this node such that its best-response is to transmit when its distance to the sink node is smaller than this critical threshold, and to back off otherwise. Finally, necessary and sufficient conditions for a given strategy profile to be a Nash equilibrium are provided.

cs.IT↗

arXiv2009

Convergence and Tradeoff of Utility-Optimal CSMA

It has been recently suggested that in wireless networks, CSMA-based distributed MAC algorithms could achieve optimal utility without any message passing. We present the first proof of convergence of such adaptive CSMA algorithms towards an arbitrarily tight approximation of utility-optimizing schedule. We also briefly discuss the tradeoff between optimality at equilibrium and short-term fairness practically achieved by such algorithms.

cs.IT↗

arXiv2008

Expected Message Delivery Time for Small-world Networks in the Continuum Limit

Small-world networks are networks in which the graphical diameter of the network is as small as the diameter of random graphs but whose nodes are highly clustered when compared with the ones in a random graph. Examples of small-world networks abound in sociology, biology, neuroscience and physics as well as in human-made networks. This paper analyzes the average delivery time of messages in dense small-world networks constructed on a plane. Iterative equations for the average message delivery time in these networks are provided for the situation in which nodes employ a simple greedy geographic routing algorithm. It is shown that two network nodes communicate with each other only through their short-range contacts, and that the average message delivery time rises linearly if the separation between them is small. On the other hand, if their separation increases, the average message delivery time rapidly saturates to a constant value and stays almost the same for all large values of their separation.

cs.IT↗

arXiv2008

On the Asymptotic Behavior of Selfish Transmitters Sharing a Common Channel

This paper analyzes the asymptotic behavior of a multiple-access network comprising a large number of selfish transmitters competing for access to a common wireless communication channel, and having different utility functions for determining their strategies. A necessary and sufficient condition is given for the total number of packet arrivals from selfish transmitters to converge in distribution. The asymptotic packet arrival distribution at Nash equilibrium is shown to be a mixture of a Poisson distribution and finitely many Bernoulli distributions.

cs.IT↗

arXiv2008

Auction-based Resource Allocation for Multi-relay Asynchronous Cooperative Networks

Resource allocation is considered for cooperative transmissions in multiple-relay wireless networks. Two auction mechanisms, SNR auctions and power auctions, are proposed to distributively coordinate the allocation of power among multiple relays. In the SNR auction, a user chooses the relay with the lowest weighted price. In the power auction, a user may choose to use multiple relays simultaneously, depending on the network topology and the relays' prices. Sufficient conditions for the existence (in both auctions) and uniqueness (in the SNR auction) of the Nash equilibrium are given. The fairness of the SNR auction and efficiency of the power auction are further discussed. It is also proven that users can achieve the unique Nash equilibrium distributively via best response updates in a completely asynchronous manner.

cs.IT↗

arXiv2007

Auction-Based Distributed Resource Allocation for Cooperation Transmission in Wireless Networks

Cooperative transmission can greatly improve communication system performance by taking advantage of the broadcast nature of wireless channels. Most previous work on resource allocation for cooperation transmission is based on centralized control. In this paper, we propose two share auction mechanisms, the SNR auction and the power auction, to distributively coordinate the resource allocation among users. We prove the existence, uniqueness and effectiveness of the auction results. In particular, the SNR auction leads to a fair resource allocation among users, and the power auction achieves a solution that is close to the efficient allocation.

cs.IT↗

arXiv2007

Optimal Power Allocation for Distributed Detection over MIMO Channels in Wireless Sensor Networks

In distributed detection systems with wireless sensor networks, the communication between sensors and a fusion center is not perfect due to interference and limited transmitter power at the sensors to combat noise at the fusion center's receiver. The problem of optimizing detection performance with such imperfect communication brings a new challenge to distributed detection. In this paper, sensors are assumed to have independent but nonidentically distributed observations, and a multi-input/multi-output (MIMO) channel model is included to account for imperfect communication between the sensors and the fusion center. The J-divergence between the distributions of the detection statistic under different hypotheses is used as a performance criterion in order to provide a tractable analysis. Optimizing the performance (in terms of the J-divergence) with individual and total transmitter power constraints on the sensors is studied, and the corresponding power allocation scheme is provided. It is interesting to see that the proposed power allocation is a tradeoff between two factors, the communication channel quality and the local decision quality. For the case with orthogonal channels under certain conditions, the power allocation can be solved by a weighted water-filling algorithm. Simulations show that, to achieve the same performance, the proposed power allocation in certain cases only consumes as little as 25 percent of the total power used by an equal power allocation scheme.

cs.IT↗

arXiv2006

Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio UWB Systems

The problem of choosing the optimal multipath components to be employed at a minimum mean square error (MMSE) selective Rake receiver is considered for an impulse radio ultra-wideband system. First, the optimal finger selection problem is formulated as an integer programming problem with a non-convex objective function. Then, the objective function is approximated by a convex function and the integer programming problem is solved by means of constraint relaxation techniques. The proposed algorithms are suboptimal due to the approximate objective function and the constraint relaxation steps. However, they perform better than the conventional finger selection algorithm, which is suboptimal since it ignores the correlation between multipath components, and they can get quite close to the optimal scheme that cannot be implemented in practice due to its complexity. In addition to the convex relaxation techniques, a genetic algorithm (GA) based approach is proposed, which does not need any approximations or integer relaxations. This iterative algorithm is based on the direct evaluation of the objective function, and can achieve near-optimal performance with a reasonable number of iterations. Simulation results are presented to compare the performance of the proposed finger selection algorithms with that of the conventional and the optimal schemes.

cs.IT↗

arXiv2005

A Game-Theoretic Approach to Energy-Efficient Power Control in Multi-Carrier CDMA Systems

A game-theoretic model for studying power control in multi-carrier CDMA systems is proposed. Power control is modeled as a non-cooperative game in which each user decides how much power to transmit over each carrier to maximize its own utility. The utility function considered here measures the number of reliable bits transmitted over all the carriers per Joule of energy consumed and is particularly suitable for networks where energy efficiency is important. The multi-dimensional nature of users' strategies and the non-quasiconcavity of the utility function make the multi-carrier problem much more challenging than the single-carrier or throughput-based-utility case. It is shown that, for all linear receivers including the matched filter, the decorrelator, and the minimum-mean-square-error (MMSE) detector, a user's utility is maximized when the user transmits only on its "best" carrier. This is the carrier that requires the least amount of power to achieve a particular target signal-to-interference-plus-noise ratio (SINR) at the output of the receiver. The existence and uniqueness of Nash equilibrium for the proposed power control game are studied. In particular, conditions are given that must be satisfied by the channel gains for a Nash equilibrium to exist, and the distribution of the users among the carriers at equilibrium is also characterized. In addition, an iterative and distributed algorithm for reaching the equilibrium (when it exists) is presented. It is shown that the proposed approach results in significant improvements in the total utility achieved at equilibrium compared to a single-carrier system and also to a multi-carrier system in which each user maximizes its utility over each carrier independently.

cs.IT↗