16166828
Maximal lifetime scheduling for K to 1 sensor-target surveillance networks
This paper addresses the maximal lifetime scheduling for k to 1 sensor-target surveillance networks. Given a set of sensors and targets in Euclidean plane, a sensor can watch only one target at a time and a target should be watched by k sensors (k ≥ 2) at anytime. Our task is to schedule sensors to watch targets, such that the lifetime of the surveillance system is maximized, where the lifetime is the duration that all targets are watched. We propose an optimal solution to find the target watching schedule for sensors that achieves the maximal lifetime. This is the first time in the literature that this scheduling problem of sensor surveillance systems has been formulated and the optimal solution has been found. Our solution consists of three steps: (1) computing the maximal lifetime of the surveillance system and a workload matrix by using linear programming techniques; (2) decomposing the workload matrix into a sequence of schedule matrices by extending the Hall's theory, to achieve the maximal lifetime; (3) obtaining a target watching timetable for each sensor based on the schedule matrices. The time complexity of our optimal method is O(m2n3), where m, n are the number of targets and the number of sensors, respectively. We illustrate our optimal method by a numeric example and experiments in the end.
893749
A Distributed and Efficient Flooding Scheme Using 1-Hop Information in Mobile Ad Hoc Networks
Flooding is one of the most fundamental operations in mobile ad hoc networks. Traditional implementation of flooding suffers from the problems of excessive redundancy of messages, resource contention, and signal collision. This causes high protocol overhead and interference with the existing traffic in the networks. Some efficient flooding algorithms were proposed to avoid these problems. However, these algorithms either perform poorly in reducing redundant transmissions or require each node to maintain 2-hop (or more) neighbors information. In the paper, we study the sufficient and necessary condition of 100 percent deliverability for flooding schemes that are based on only 1-hop neighbors information. We further propose an efficient flooding algorithm that achieves the local optimality in two senses: 1) the number of forwarding nodes in each step is minimal and 2) the time complexity for computing forwarding nodes is the lowest, which is O(nlogn), where n is the number of neighbors of a node. Extensive simulations have been conducted and simulation results have shown the excellent performance of our algorithm
6771108
Fault-Tolerant Relay Node Placement in Wireless Sensor Networks
The paper addresses the relay node placement problem in two-tiered wireless sensor networks. Given a set of sensor nodes in an Euclidean plane, our objective is to place minimum number of relay nodes to forward data packets from sensor nodes to the sink, such that: 1 the network is connected, 2 the network is 2-connected. For case one, we propose a 6+e-approximation algorithm for any e>0 with polynomial running time when e is fixed. For case two, we propose two approximation algorithms with 24+e and 6/T+12+e, respectively, where T is the ratio of the number of relay nodes placed in case one to the number of sensors.
13122574
Bandwidth guaranteed call admission in TDMA/CDMA ad hoc wireless networks
This paper first studied the timeslot assignment problem in time division multiple access/code division multiple access (TDMA/CDMA) wireless ad hoc networks. Given a path P, we prove that a timeslot assignment providing one unit of bandwidth on P can be found in O(|P|) time if such an assignment exists. The results have been extended to the case that P can provide two units of bandwidth. Based on the timeslot assignment for the special cases, an efficient slot assignment algorithm with O(|P|^2k) is proposed for general cases, where k is the number of slots in a TDMA frame. Then, the timeslot assignment algorithm is integrated into a quality of service (QoS) call admission scheme for QoS call requests. Extensive simulations are conducted and the results have demonstrated the superior performance of our method.
140126207
Energy Efficient Broadcast Routing in Static Ad Hoc Wireless Networks
In this paper, we discuss energy efficient broadcast in ad hoc wireless networks. The problem of our concern is: given an ad hoc wireless network, find a broadcast tree such that the energy cost of the broadcast tree is minimized. Each node in the network is assumed to have a fixed level of transmission power. We first prove that the problem is NP-hard and propose three heuristic algorithms, namely, shortest path tree heuristic, greedy heuristic, and node weighted Steiner tree-based heuristic, which are centralized algorithms. The approximation ratio of the node weighted Steiner tree-based heuristic is proven to be (1 + 2 ln(n - 1)). Extensive simulations have been conducted and the results have demonstrated the efficiency of the proposed algorithms.
11860267
On optimal placement of relay nodes for reliable connectivity in wireless sensor networks
The paper addresses the relay node placement problem in two-tiered wireless sensor networks. Given a set of sensor nodes in Euclidean plane, our objective is to place minimum number of relay nodes to forward data packets from sensor nodes to the sink, such that: 1) the network is connected, 2) the network is 2-connected. For case one, we propose a (6+ε)-approximation algorithm for any ε > 0 with polynomial running time when ε is fixed. For case two, we propose two approximation algorithms with (24+ε) and (6/T+12+ε), respectively, where T is the ratio of the number of relay nodes placed in case one to the number of sensors. We further extend the results to the cases where communication radiuses of sensor nodes and relay nodes are different from each other.
17242334
Incremental Feature Selection
Feature selection is a problem of finding relevant features. When the number of features of a dataset is large and its number of patterns is huge, an effective method of feature selection can help in dimensionality reduction. An incremental probabilistic algorithm is designed and implemented as an alternative to the exhaustive and heuristic approaches. Theoretical analysis is given to support the idea of the probabilistic algorithm in finding an optimal or near-optimal subset of features. Experimental results suggest that (1) the probabilistic algorithm is effective in obtaining optimal/suboptimal feature subsets; (2) its incremental version expedites feature selection further when the number of patterns is large and can scale up without sacrificing the quality of selected features.
16781216
Fast hierarchical clustering and its validation
Clustering is the task of grouping similar objects into clusters. A prominent and useful class of algorithm is hierarchical agglomerative clustering (HAC) which iteratively agglomerates the closest pair until all data points belong to one cluster. It outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the dataset. However, HAC methods have several drawbacks: (1) high time and memory complexities for clustering, and (2) inefficient and inaccurate cluster validation. In this paper we show that these drawbacks can be alleviated by closely studying the dendrogram. Empirical study shows that most HAC algorithms follow a trend where, except for a number of top levels of the dendrogram, all lower levels agglomerate clusters which are very small in size and close in proximity to other clusters. Methods are proposed that exploit this characteristic to reduce the time and memory complexities significantly and to make validation very efficient and accurate. Analyses and experiments show the effectiveness of the proposed method.
11098583
Neighborhood unions and cyclability of graphs
A graph G is said to be cyclable if for each orientation G of G, there exists a set S of vertices such that reversing all the arcs of G with one end in S results in a hamiltonian digraph. Let G be a 3-connected graph of order n ≥ 36. In this paper, we show that if for any three independent vertices x1, x2 and x3, |N(x1) ∪ N(x2)| + |N(x2) ∪ N(x3)| + |N(x3) ∪ N(x1)| ≥ 2n+1, then G is cyclable.
17890414
Identifying significant genes from microarray data
Microarray technology is a recent development in experimental molecular biology which can produce quantitative expression measurements for thousands of genes in a single, cellular mRNA sample. These many gene expression measurements form a composite profile of the sample, which can be used to differentiate samples from different classes such as tissue types or treatments. However, for the gene expression profile data obtained in a specific comparison, most likely only some of the genes will, be differentially expressed between the classes, while many other genes have similar expression levels. Selecting a list of informative differential genes from these data is important for microarray data analysis. In this paper, we describe a framework for selecting informative genes, called ranking and combination analysis (RAC), which combines various existing informative gene selection methods. We conducted experiments using three data sets and six existing feature selection methods. The results show that the RAC framework is a robust and efficient approach to identify informative gene for microarray data. The combination approach on two selecting methods almost always performed better than the less efficient individual, and in many cases, better than both. More significantly, when considering all three data sets together, the combination approach, on average, outperforms each individual feature selection method. All of these indicate that RCA might be a viable and feasible approach for the microarray gene expression analysis.
40070319
A Distributed Hierarchical Clustering System for Web Mining
This paper proposes a novel method of distributed hierarchical clustering for Web mining. The method is closely related to our early work of Self-Generated Neural Networks (SGNN), which is in turn based on both self-organizing neural network and concept formation. The complexity of the algorithm is at most O(MNlogN). With the distributed implementation the method can be easily scaled up. The method is independent of the order the web documents presented. The method produces a natural conceptual hierarchy but not a binary tree. The method can include multimedia information into the same cluster hierarchy. A visualization mechanism has been developed for the clustering method and it shows the cluster hierarchy generated by the method has very high quality. The clustering process is fully automatic, and no human intervention is required. A clustering system has been built based on the proposed method, which can be used to automatically generate multimedia search engines, web directories, decision-making assistance systems, knowledge management systems, and personalized knowledge portals.