Yuanzhu Peter Chen

Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks

We present a series of approximation algorithms for finding a smallweakly-connected dominating set (WCDS) in a given graph to be usedin clustering mobile ad hoc networks. The structure of a graph canbe simplified using WCDSs and made more succinct for routing in adhoc networks. The theoretical performance ratio of these algorithmsis O(ln Δ) compared to the minimum size WCDS, whereΔ is the maximum degree of the input graph. The first twoalgorithms are based on the centralized approximation algorithms ofGuha and Khuller cite guha-khuller-1998 for finding small connecteddominating sets (CDSs). The main contribution of this work is acompletely distributed algorithm for finding small WCDSs and theperformance of this algorithm is shown to be very close to that ofthe centralized approach. Comparisons between our work and someprevious work (CDS-based) are also given in terms of the size ofresultant dominating sets and graph connectivity degradation.

User comments for news recommendation in forum-based social media

News recommendation and user interaction are important features in many Web-based news services. The former helps users identify the most relevant news for further information. The latter enables collaborated information sharing among users with their comments following news postings. This research is intended to marry these two features together for an adaptive recommender system that utilizes reader comments to refine the recommendation of news in accordance with the evolving topic. This then turns the traditional push-data type of news recommendation to discussion moderator that can intelligently assist online forums. In addition, to alleviate the problem of recommending essentially identical articles, the relationship (duplicate, generalization, or specialization) between recommended news articles and the original posting is investigated. Our experiments indicate that our proposed solutions provide an improved news recommendation service in forum-based social media.

A ZONAL ALGORITHM FOR CLUSTERING AN HOC NETWORKS

A Mobile Ad Hoc Network (MANET) is an infrastructureless wireless network that can support highly dynamic mobile units. The multi-hop feature of a MANET suggests the use of clustering to simplify routing. Graph domination can be used in defining clusters in MANETs. A variant of dominating set which is more suitable for clustering MANETs is the weakly-connected dominating set. A cluster is defined to be the set of vertices dominated by a particular vertex in the dominating set. As it is NP-complete to determine whether a given graph has a weakly-connected dominating set of a particular size, we present a zonal distributed algorithm for finding small weakly-connected dominating sets. In this new approach, we divide the graph into regions, construct a weakly-connected dominating set for each region, and make adjustments along the borders of the regions to produce a weakly-connected dominating set of the entire graph. We present experimental evidence that this zonal algorithm has similar performance to and provides better cluster connectivity than previous algorithms.

Energy-Efficient Data Aggregation Hierarchy for Wireless Sensor Networks

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, is often aggregated (or compressed). This compression is done by a subset of the sensors called aggregators. Since sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, we first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS). Then, we generalize it to an aggregation hierarchy and extend EPAS to a Hierarchical Energy-Efficient Protocol for Aggregator Selection (hEPAS). We derive the optimal number of aggregators with generalized compression and power-consumption models, and present fully distributed algorithms for aggregator deployment. Simulation results show that our algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols, and are thus applicable to a broad spectrum of application environments.

MAC-layer proactive mixing for network coding in multi-hop wireless networks

Network coding is a recent research topic in wireless networking. By combining multiple packets in a single broadcast transmission, network coding can greatly improve the capacity of multi-hop wireless networks. Packet mixing, when applied with traditional routing, can only be performed at the junctions of the paths determined by the routing module. This limits significantly the coding opportunities in the network. This paper presents a novel MAC-layer mixing method, named BEND, which proactively seizes opportunities for coding. Without relying on fixed forwarders, BEND allows each node in the neighborhood to be a potential coder and forwarder and coordinates their packet transmissions for higher coding gain. By taking advantage of redundant copies of a packet in the neighborhood coding repository, the number of mixing points, and thus the coding opportunities, can be significantly increased. This high coding gain is verified by our simulation studies.

An information-gain approach to detecting three-way epistatic interactions in genetic association studies

Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies. Objectives In this study, we propose a fast, non-parametric, and model-free measure for three-way epistasis. Methods Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way epistasis. Results Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies.

Maintaining weakly-connected dominating sets for clustering ad hoc networks

An ad hoc network is a multihop wireless communication network supporting mobile users. Network performance degradation is a major problem as the network becomes larger. Clustering is an approach to simplify the network structure and thus alleviate the scalability problem. One method that has been proposed to form clusters is to use weakly-connected dominating sets [Y.P. Chen, A.L. Liestman, Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks, in: The Third ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc02), 2002, pp. 165-172; Y.P. Chen, A.L. Liestman, A zonal algorithm for clustering ad hoc networks, International Journal of Foundations of Computer Science 14(2) (2003) 305-322]. Here, we present a zonal distributed algorithm to maintain weakly-connected dominating sets as the network structure changes. When the zones are small, the algorithm is essentially localized; when the zones are large, it behaves more globally. The size of the weakly-connected dominating set obtained also varies depending on the choice of zone size, with larger zones generally resulting in smaller weakly-connected dominating sets. Experiments provide evidence that this maintenance algorithm keeps the size of the weakly-connected dominating set approximately the same as its initial size and does not compromise the network connectivity.

Link-layer-and-above diversity in multihop wireless networks

The instability of wireless channels was a haunting issue in communications until recent exploration in utilizing variation. The same transmission might present significantly, and usually independently, different reception quality when broadcast to receivers at different locations. In addition, the same stationary receiver might experience drastic fluctuation over time as well. The combination of link-quality variation with the broadcasting nature of the wireless channel itself disclosed a direction in the research of wireless networking, namely, the utilization of diversity. In this article, we summarize the causes of channel diversity in wireless communications, and how it is perceived in different layers of multihop wireless networks. To promote new research innovations in this area, we concentrate on link-layer diversity and speculate on the challenges and potential of diversity schemes at the network layer.

Network Coding via Opportunistic Forwarding in Wireless Mesh Networks

Network coding has been used to increase transportation capabilities in wireless mesh networks. In mesh networks, the coding opportunities depend on the co-location of multiple traffic flows. With fixed routes given by a routing protocol, the coding opportunities are limited. This paper presents a new protocol called BEND, which combines the features of network coding and opportunistic forwarding in 802.11-based mesh networks to create more coding opportunities in the network. Taking advantage of redundancy of packets among the forwarder candidates, our protocol bends the routes locally and dynamically to attain better coding opportunities. This higher coding gain is verified using a network simulator.

Personalized text snippet extraction using statistical language models

In knowledge discovery in a text database, extracting and returning a subset of information highly relevant to a users query is a critical task. In a broader sense, this is essentially identification of certain personalized patterns that drives such applications as Web search engine construction, customized text summarization and automated question answering. A related problem of text snippet extraction has been previously studied in information retrieval. In these studies, common strategies for extracting and presenting text snippets to meet user needs either process document fragments that have been delimitated a priori or use a sliding window of a fixed size to highlight the results. In this work, we argue that text snippet extraction can be generalized if the users intention is better utilized. It overcomes the rigidness of existing approaches by dynamically returning more flexible start-end positions of text snippets, which are also semantically more coherent. This is achieved by constructing and using statistical language models which effectively capture the commonalities between a document and the user intention. Experiments indicate that our proposed solutions provide effective personalized information extraction services.