Results 1  10
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31
Parameterized Complexity: Exponential SpeedUp for Planar Graph Problems
 in Electronic Colloquium on Computational Complexity (ECCC
, 2001
"... A parameterized problem is xed parameter tractable if it admits a solving algorithm whose running time on input instance (I; k) is f(k) jIj , where f is an arbitrary function depending only on k. Typically, f is some exponential function, e.g., f(k) = c k for constant c. We describe general techniqu ..."
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Cited by 60 (21 self)
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A parameterized problem is xed parameter tractable if it admits a solving algorithm whose running time on input instance (I; k) is f(k) jIj , where f is an arbitrary function depending only on k. Typically, f is some exponential function, e.g., f(k) = c k for constant c. We describe general techniques to obtain growth of the form f(k) = c p k for a large variety of planar graph problems. The key to this type of algorithm is what we call the "Layerwise Separation Property" of a planar graph problem. Problems having this property include planar vertex cover, planar independent set, and planar dominating set.
One for the price of two: A unified approach for approximating covering problems
, 1998
"... We present a simple and unified approach for developing and analyzing approximation algorithms for covering problems. We illustrate this on approximation algorithms for the following problems: Vertex Cover, Set Cover, Feedback Vertex Set, Generalized Steiner Forest and related problems. The main id ..."
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Cited by 57 (14 self)
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We present a simple and unified approach for developing and analyzing approximation algorithms for covering problems. We illustrate this on approximation algorithms for the following problems: Vertex Cover, Set Cover, Feedback Vertex Set, Generalized Steiner Forest and related problems. The main idea can be phrased as follows: iteratively, pay two dollars (at most) to reduce the total optimum by one dollar (at least), so the rate of payment is no more than twice the rate of the optimum reduction. This implies a total payment (i.e., approximation cost) ~ twice the optimum cost. Our main contribution is based on a formal definition for covering problems, which includes all the above fundamental problems and others. We further extend the Bafna, Berman and Fujito LocalRatio theorem. This extension eventually yields a short generic rapproximation algorithm which can generate most known approximation algorithms for most covering problems. Another extension of the LocalRatio theorem to randomized algorithms gives a simple proof of Pitt's randomized approximation for Vertex Cover. Using this approach, we develop a modified greedy algorithm, which for Vertex Cover, gives an expected performance ratio <= 2.
Graph separators: a parameterized view
 Journal of Computer and System Sciences
, 2001
"... Graph separation is a wellknown tool to make (hard) graph problems accessible to a divide and conquer approach. We show how to use graph separator theorems in combination with (linear) problem kernels in order to develop xed parameter algorithms for many wellknown NPhard (planar) graph problems. ..."
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Cited by 29 (13 self)
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Graph separation is a wellknown tool to make (hard) graph problems accessible to a divide and conquer approach. We show how to use graph separator theorems in combination with (linear) problem kernels in order to develop xed parameter algorithms for many wellknown NPhard (planar) graph problems. We coin the key notion of glueable select&verify graph problems and derive from that a prospective way to easily check whether a planar graph problem will allow for a xed parameter algorithm of running time c p
A betterthangreedy approximation algorithm for the minimum set cover problem
 SIAM J. Comput
, 2006
"... set cover problem ..."
Designing Distributed Diagnosers for Complex Continuous Systems
, 2008
"... Wear and tear from sustained operations cause systems to degrade and develop faults. Online fault diagnosis schemes are necessary to ensure safe operation and avoid catastrophic situations, but centralized diagnosis approaches have large memory and communication requirements, scale poorly, and creat ..."
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Cited by 11 (8 self)
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Wear and tear from sustained operations cause systems to degrade and develop faults. Online fault diagnosis schemes are necessary to ensure safe operation and avoid catastrophic situations, but centralized diagnosis approaches have large memory and communication requirements, scale poorly, and create single points of failure. To overcome these problems, we propose an online, distributed, modelbased diagnosis scheme for isolating abrupt faults in large continuous systems. This paper presents two algorithms for designing the local diagnosers and analyzes their time and space complexity. The first algorithm assumes the subsystem structure is known and constructs a local diagnoser for each subsystem. The second algorithm creates a partition structure and local diagnosers simultaneously. We demonstrate the effectiveness of our approach by applying it to
On the Dual Representation of Nonbinary Semiringbased CSPs
 Proceedings SOFT2000 (2000
, 2000
"... It is well known that any nonbinary CSP can be reformulated as a binary CSP. In this paper we show that the same translation methods can be applied in the soft constraints framework. We observe that any nonbinary soft constraint CSP can be reformulated as a problem with only binary and unary c ..."
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Cited by 10 (2 self)
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It is well known that any nonbinary CSP can be reformulated as a binary CSP. In this paper we show that the same translation methods can be applied in the soft constraints framework. We observe that any nonbinary soft constraint CSP can be reformulated as a problem with only binary and unary constraints. Interestingly, the translation leads to binary constraints that are hard (define conditions of mandatory satisfaction) and unary constraints that are soft (define a preference criterion among the set of solutions). We elaborate our observation in the semiringbased framework.
uCast: Unified Connectionless Multicast for Energy Efficient Content Distribution in Sensor Networks
"... Abstract — In this paper, we present uCast, a novel multicast protocol for energy efficient content distribution in sensor networks. We design uCast to support a large number of multicast sessions, especially when the number of destinations in a session is small. In uCast, we do not keep any state i ..."
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Cited by 9 (1 self)
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Abstract — In this paper, we present uCast, a novel multicast protocol for energy efficient content distribution in sensor networks. We design uCast to support a large number of multicast sessions, especially when the number of destinations in a session is small. In uCast, we do not keep any state information relevant to ongoing multicast deliveries at intermediate nodes. Rather, we directly encode the multicast information in the packet headers, and parse these headers at intermediate nodes using the scoreboard algorithm as proposed in this paper. We demonstrate that 1) uCast is powerful enough to support multiple addressing and unicast routing schemes and 2) uCast is robust, efficient and scalable in the face of changes in network topology, such as those introduced by energy conservation protocols. We systematically evaluate the performance of uCast through simulations, compare it with other stateoftheart protocols, and collect preliminary data from a running system based on the Berkeley motes platform. Index Terms — Sensor networks, multicast, content distribution. I.
uSense: A Unified Asymmetric Sensing Coverage Architecture for Wireless Sensor Networks
 In ICDCS ’07
, 2007
"... Abstract — As a key approach to achieve energy efficiency in sensor networks, sensing coverage has been studied extensively. Researchers have designed many coverage protocols to provide various kinds of service guarantees on the network lifetime, coverage ratio and detection delay. While these proto ..."
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Cited by 8 (4 self)
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Abstract — As a key approach to achieve energy efficiency in sensor networks, sensing coverage has been studied extensively. Researchers have designed many coverage protocols to provide various kinds of service guarantees on the network lifetime, coverage ratio and detection delay. While these protocols are effective, they are not flexible enough to meet multiple design goals simultaneously. In this paper, we propose a Unified Sensing Coverage Architecture, called uSense, which features three novel ideas: Asymmetric Architecture, Generic Switching and Global Scheduling. We propose asymmetric architecture based on the conceptual separation of switching from scheduling. Switching is efficiently supported in sensor nodes, while scheduling is done in a separated computational entity, where multiple scheduling algorithms are supported. As an instance, we propose a twolevel global coverage algorithm, called uScan. At the first level, coverage is scheduled to activate different portions of an area. We propose an optimal scheduling algorithm to minimize area breach. At the second level, sets of nodes are selected to cover active portions. Importantly, we show the feasibility to obtain optimal setcover results in linear time if the layout of areas satisfies certain conditions. We evaluate our architecture with a network of 30 MicaZ motes, an extensive simulation with 10,000 nodes, as well as theoretical analysis. The results indicate that uSense is a promising architecture to support flexible and efficient coverage in sensor networks. I.
Designing distributed diagnosers for complex physical systems
 in Proceedings of the 16th International Workshop on Principles of Diagnosis (DX 05
, 2005
"... Online diagnosis methods require large computationally expensive diagnosis tasks to be decomposed into sets of smaller tasks so that time and space complexity constraints are not violated. This paper defines the distributed diagnosis problem in the Transcend qualitative diagnosis framework, and then ..."
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Cited by 7 (3 self)
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Online diagnosis methods require large computationally expensive diagnosis tasks to be decomposed into sets of smaller tasks so that time and space complexity constraints are not violated. This paper defines the distributed diagnosis problem in the Transcend qualitative diagnosis framework, and then develops heuristic algorithms for generating a set of local diagnosers that solve the global diagnosis problem without a coordinator. Two versions of the algorithm are discussed. The time complexity and optimality of these algorithms are compared and validated through experimental results. 1
Hyperrectanglebased discriminative data generalization and applications in data mining
, 2007
"... The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as humancomprehensible patterns from which endusers can gain intuitions and insights. Axisparallel hyperrectangles provide interpretable generalizations for multidimensional data points ..."
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Cited by 5 (2 self)
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The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as humancomprehensible patterns from which endusers can gain intuitions and insights. Axisparallel hyperrectangles provide interpretable generalizations for multidimensional data points with numerical attributes. In this dissertation, we study the fundamental problem of rectanglebased discriminative data generalization in the context of several useful data mining applications: cluster description, rule learning, and Nearest Rectangle classification. Clustering is one of the most important data mining tasks. However, most clustering methods output sets of points as clusters and do not generalize them into interpretable patterns. We perform a systematic study of cluster description, where we propose novel description formats leading to enhanced expressive power and introduce novel description problems specifying different tradeoffs between interpretability and accuracy. We also present efficient heuristic algorithms for the introduced problems in the proposed formats. Ifthen rules are