clustering of mobile nodes among separate domains has been proposed as an efficient approach to mimic the operation of the fixed infrastructure and manage the resources in multi-hop networks. In this paper, it was ana...
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ISBN:
(纸本)9781424457953
clustering of mobile nodes among separate domains has been proposed as an efficient approach to mimic the operation of the fixed infrastructure and manage the resources in multi-hop networks. In this paper, it was analyzed a weight-based clustering algorithm. This algorithm is called Enhanced Performance clustering algorithm (EPCA). It selects clusterhead according to its weight computed by combining a set of system parameters and defines new mechanisms as cluster division, merging diminution and extension. EPCA was simulated and tested in real conditions in a campus environment.
The watershed algorithm is an important technique for image segmentation which converts the gray-level image to a segmented image. We propose a watershed algorithm based on the mean value, the standard deviation of th...
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The watershed algorithm is an important technique for image segmentation which converts the gray-level image to a segmented image. We propose a watershed algorithm based on the mean value, the standard deviation of the histogram and the PSNR within a sub-interval, a novel recursive algorithm for deriving clustered images that is also used to increase the quality of an image. The clustered images using the watershed algorithm produce close results to that of the original image. (C) 2010 Published by Elsevier Ltd
Wireless sensor networks have gained abundant interest due to their potential wide range of applications. Reliability of deployed wireless sensor network is defined by covered area of alive nodes and redundancy of dat...
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ISBN:
(纸本)9783319164861;9783319164854
Wireless sensor networks have gained abundant interest due to their potential wide range of applications. Reliability of deployed wireless sensor network is defined by covered area of alive nodes and redundancy of data. Redundancy in data occurs because of overlapped sensed area. An initial reliable wireless sensor network switches to unreliable state because nodes perish in the field randomly. Consequently, the quality of data starts diminishing. It is imperative to know when the network will switch to unreliable state from reliable state so that proper action can be conducted in the field. Work of this paper analyzes and compares analytical and simulation modeling for reliability state of wireless sensor network. Multi-objective genetic algorithm based method is operated for analytical modeling which determines minimum number of nodes (randomly) that covers almost complete area while having required minimum overlapped area. clustering algorithm, LEACH, is implemented in NS-2 for simulation modeling. Comparative results of analytical and simulation modeling are different because of their different nature but both highlights that reliability of wireless sensor network is salient.
In this paper, we propose a novel unsupervised evolutionary clustering algorithm for mixed type data, evolutionary k-prototype algorithm (EKP). As a partitional clustering algorithm, k-prototype (KP) algorithm is a we...
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ISBN:
(纸本)9781424481262
In this paper, we propose a novel unsupervised evolutionary clustering algorithm for mixed type data, evolutionary k-prototype algorithm (EKP). As a partitional clustering algorithm, k-prototype (KP) algorithm is a well-known one for mixed type data. However, it is sensitive to initialization and converges to local optimum easily. Global searching ability is one of the most important advantages of evolutionary algorithm (EA), so an EA framework is introduced to help KP overcome its flaws. In this study, KP is applied as a local search strategy, and runs under the control of the EA framework. Experiments on synthetic and real-life datasets show that EKP is more robust and generates much better results than KP for mixed type data.
The paper discusses the batch incremental clustering algorithm in the apllication for Coke Oven Intelligent Control. By analyzing new data by bulk incremental clustering algorithm, the fuzzy control rule base will be ...
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ISBN:
(纸本)9781424458479
The paper discusses the batch incremental clustering algorithm in the apllication for Coke Oven Intelligent Control. By analyzing new data by bulk incremental clustering algorithm, the fuzzy control rule base will be updated. And then, the simulating models for gas collector pressure system and its control system is established under the condition of software MATLAB. The simulating result with the control effect of the fuzzy control rules gotten by experience induction is compared, which proves the method to be rational and feasible.
Motivated by recent developments in wireless sensor networks (WSNs), we present several efficient clustering algorithms for maximizing the lifetime of WSNs, i.e., the duration till a certain percentage of the nodes di...
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Motivated by recent developments in wireless sensor networks (WSNs), we present several efficient clustering algorithms for maximizing the lifetime of WSNs, i.e., the duration till a certain percentage of the nodes die. Specifically, an optimization algorithm is proposed for maximizing the lifetime of a single-cluster network, followed by an extension to handle multi-cluster networks. Then we study the joint problem of prolonging network lifetime by introducing energy-harvesting (EH) nodes. An algorithm is proposed for maximizing the network lifetime where EH nodes serve as dedicated relay nodes for cluster heads (CHs). Theoretical analysis and extensive simulation results show that the proposed algorithms can achieve optimal or suboptimal solutions efficiently, and therefore help provide useful benchmarks for various centralized and distributed clustering scheme designs. (C) 2013 Elsevier B.V. All rights reserved.
As one of the new self-organizing and self-configuration broadband networks, wireless mesh networks are being increasingly attractive. In order to solve the load balancing problem in wireless mesh networks, this paper...
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As one of the new self-organizing and self-configuration broadband networks, wireless mesh networks are being increasingly attractive. In order to solve the load balancing problem in wireless mesh networks, this paper proposes a novel multi-path routing algorithm based on clustering (Cluster_MMesh) for wireless mesh networks. In the clustering stage, on the basis of the maximum connectivity clustering algorithm and k-hop clustering algorithm, according to the idea of maximum connectivity, a new concept of node connectivity degree is proposed in this paper, which can make the selection of cluster head more simple and reasonable. While clustering, the node which has less expected load in the candidate border gateway node set will be selected as the border gateway node. In the multi-path routing establishment stage, we use the intra-clustering multi-path routing algorithm and inter-clustering multi-path routing algorithm to establish multi-path routing from the source node to the destination node. At last, in the traffic allocation stage, we will use the virtual disjoint multi-path model (Vdmp) to allocate the network traffic. Simulation results show that the Cluster_MMesh routing algorithm can help increase the packet delivery rate, reduce the average end to end delay, and improve the network performance.
A method of reconfigurable manufacturing cells regarding process route as the basic clustering particle is proposed according to the similarity of production process after analyzing the relationship of parts,process r...
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A method of reconfigurable manufacturing cells regarding process route as the basic clustering particle is proposed according to the similarity of production process after analyzing the relationship of parts,process routes and manufacturing *** and manufacturing resources were reconfigured automatically into logic manufacturing cells by mapping to process routes clusters, which are clustered firstly.A reconfigurable manufacturing cell of clustering algorithm based on entropy is presented considering process routes clustering in view of entropy. Though this method a process route is regarded as a spatial data point and its character is described by manufacturing ***,an example was given to validate the effectiveness of this algorithm.
A method of reconfigurable manufacturing cells regarding process route as the basic clustering particle is proposed according to the similarity of production process after analyzing the relationship of parts, process ...
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A method of reconfigurable manufacturing cells regarding process route as the basic clustering particle is proposed according to the similarity of production process after analyzing the relationship of parts, process routes and manufacturing resources. Parts and manufacturing resources were reconfigured automatically into logic manufacturing cells by mapping to process routes clusters, which are clustered firstly. A reconfigurable manufacturing cell of clustering algorithm based on entropy is presented considering process routes clustering in view of entropy. Though this method a process route is regarded as a spatial data point and its character is described by manufacturing resources. Finally, an example was given to validate the effectiveness of this algorithm.
clustering is an important research area for mobile ad hoc network and wireless sensor networks, because clustering makes it possible to guarantee basic levels of system performance, such as throughput and delay, in a...
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clustering is an important research area for mobile ad hoc network and wireless sensor networks, because clustering makes it possible to guarantee basic levels of system performance, such as throughput and delay, in a large ad hoc or wireless sensor network. In the research filed of wireless sensor network, more attention has been paid to design energy efficient clustering schemes to save every possible bit of energy. This paper proposes an energy efficient clustering algorithm for dynamic wireless sensor network. The proposed algorithm elects the nodes that have more energy and less mobility as cluster heads and constantly monitors cluster head's residual energy. If the energy fell lower than the Off-duty Threshold, the reclustering operation will be triggered. Simulation results show that the proposed algorithm outperforms the Weight clustering algorithm.
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