Category Archives: Publications

Event Detection using Customer Care Calls (INFOCOM 2013)

Chen, Y., Lee, G. M., Duffield, N., Qiu, L., and Wang, J. (2013). Event Detection using Customer Care Calls. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM 2013), Turin, Italy.

  • Based on an industry collaboration with AT&T Labs – Research.
  • INFOCOM is a top-tier conference in the networking area (h5-index: 72)

Customer care calls serve as a direct channel for a service provider to learn feedbacks from their customers. They reveal details about the nature and impact of major events and problems observed by customers. By analyzing customer care calls, a service provider can detect important events to speed up problem resolution. However, automating event detection based on customer care calls poses several significant challenges. First, the relationship between customers’ calls and network events is blurred because customers respond to an event in different ways. Second, customer care calls can be labeled inconsistently across agents and across call centers, and a given event naturally gives rise to calls spanning a number of categories. Third, many important events cannot be detected by looking at calls in one category. How to aggregate calls from different categories for event detection is important but challenging. Lastly, customer care call records have high dimensions (e.g., thousands of categories in our dataset). In this paper, we propose a systematic method for detecting events in a major cellular network using customer care call data. It consists of three main components: (i) using a regression approach that exploits temporal stability and low-rank properties to automatically learn the relationship between customer calls and major events, (ii) reducing the number of unknowns by clustering call categories and using L 1 norm minimization to identify important categories, and (iii) employing multiple classifiers to enhance the robustness against noise and different response time. For the detected events, we leverage Twitter social media to summarize them and to locate the impacted regions. We show the effectiveness of our approach using data from a large cellular service provider in the US.

Improving the Interaction between Overlay Routing and Traffic Engineering (Networking 2008)

Lee, G. M., and Choi, T. (2008). Improving the Interaction between Overlay Routing and Traffic Engineering, In Proceedings of IFIP Networking Conference (Networking 2008), Singapore.

  • Networking is a premier conference in the networking area (h5-index: 23)

Overlay routing has been successful as an incremental method to improve Internet routing by allowing its own users to select their logical routing. In the meantime, traffic engineering (TE) is being used to reduce the whole network cost by adapting physical routing in response to varying traffic patterns. Previous studies [1,2] have shown that the interaction of the two network components can cause huge network cost increases and oscillations. In this paper, we improve the interaction between overlay routing and TE by modifying the objectives of both parties. For the overlay part, we propose TE-awareness which limits the selfishness by some bounds so that the action of overlay does not offensively affect TE’s optimization process. Then, we suggest COPE [3] as a strong candidate that achieves close-to-optimal performance for predicted traffic matrices and that handles unpredictable overlay traffic efficiently. With extensive simulation results, we show the proposed methods can significantly improve the interaction with lower network cost and smaller oscillation problems.

Designing an Incentive-Based Framework for Overlay Routing (Technical Report 2007)

Lee, G. M., Choi, T., and Zhang, Y. (2007). Designing an Incentive-Based Framework for Overlay Routing. UTCS Technical Report, January 2007.

Overlay routing becomes popular as an incremental mechanism to improve internet routing. So far, overlay nodes are always assumed to cooperate with each other. In this paper, we analyze overlay routing in a new viewpoint, in which the overlay nodes act independently to maximize their own payoff. We use a game-theoretic approach to analyze the transit traffic forwarding and realize that overlay nodes are not likely to cooperate with each other in our new scenario.

In order to stimulate the independent overlay nodes to cooperate with each other, we design and propose an incentive-based framework. We introduce three possible systems and evaluate them analytically. Among the candidates, we use simulation to verify the feasibility of our proposed framework generalized punish-and-reward system. The performance gets closer to social optimum as we increase the number of punishments. In addition, the system shows tolerance against impatient players.

On the Interactions of Overlay Routing (Master’s Thesis 2006)

Gene Moo Lee (2006). On the Interactions of Overlay Routing. Master’s Thesis, University of Texas at Austin, May 2006. [UT Library]

Overlay routing has been successful as an incremental method to improve the current Internet routing by allowing users to select the Internet paths by themselves. By its nature, overlay routing has selfish behavior, which makes an impact on the related components of Internet routing. In this thesis, we study three interactions related to overlay routing. First, overlay routing changes the traffic patterns observed by the network operating side, which uses traffic engineering techniques to cope with the dynamic traffic demands. We improve this vertical interaction between overlay routing and traffic engineering. Secondly, the performance of overlay routing may be affected by the action of other coexisting overlays. An initial result on the horizontal interaction among multiple overlays is given. Lastly, within a single overlay network, overlay nodes can be regarded as independent decision-makers, who act strategically to maximize individual gain. We design an incentive-based framework to achieve Pareto-optimality in the internal interaction of overlay routing.

Improving Sketch Reconstruction Accuracy Using Linear Least Square Method (IMC 2005)

Lee, G. M., Liu, H., Yoon, Y., and Zhang, Y. (2005). Improving Sketch Reconstruction Accuracy Using Linear Least Square Method, In Proceedings of Internet Measurement Conference (IMC 2005), Berkeley, California.

  • IMC is a premier conference in the network measurement area (h5-index: 37)

Sketch is a sublinear space data structure that allows one to approximately reconstruct the value associated with any given key in an input data stream. It is the basis for answering a number of fundamental queries on data streams, such as range queries, finding quantiles, frequent items, etc. In the networking context, sketch has been applied to identifying heavy hitters and changes, which is critical for traffic monitoring, accounting, and network anomaly detection.

In this paper, we propose a novel approach called lsquare to significantly improve the reconstruction accuracy of the sketch data structure. Given a sketch and a set of keys, we estimate the values associated with these keys by constructing a linear system and finding the optimal solution for the system using linear least squares method. We use a large amount of real Internet traffic data to evaluate lsquare against countmin, the state-of-the-art sketch scheme. Our results suggest that given the same memory requirement, lsquare achieves much better reconstruction accuracy than countmin. Alternatively, given the same reconstruction accuracy, lsquare requires significantly less memory. This clearly demonstrates the effectiveness of our approach.