A New Type of Hexagonal Fault-Tolerant Clustering Algorithm

2014 ◽  
Vol 543-547 ◽  
pp. 1728-1733
Author(s):  
Jie Tian ◽  
Ming Yu Luo ◽  
Meng Yang Chen
Keyword(s):  
Fault Tolerance ◽  
Clustering Algorithm ◽  
Fault Tolerant ◽  
Middle Management ◽  
Clustering Algorithms ◽  
False Positives ◽  
Simulation Experiments ◽  
New Type ◽  
Save Energy

In view of the problem that present most clustering algorithms are given priority to save energy but ignoring fault tolerance, this paper puts forward a new kind of hexagonal fault-tolerant clustering algorithm (HFTC). By increasing the middle management node, which controls nodes rate of false positives and managements topology within the cluster, this algorithm completes nondestructive substitution between nodes. At the same time, the introduction of backup nodes, it also improves the networks fault tolerance. The simulation experiments show that HFTC can guarantee a high fault tolerance in networks, make the network to send more packets, and prolong the network life effectively.

An Energy-Efficient Layered Clustering Algorithm for Routing in Wireless Sensor Networks

2017 ◽  
Vol 8 (3) ◽  
pp. 43-66 ◽  
Author(s):  
Alphonse PJA ◽  
Sivaraj C ◽  
Janakiraman T N.
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Conservation ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Transmission Rate ◽  
Clustering Algorithms ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Simulation Experiments

Efficient energy management is a key issue in battery equipped wireless sensor networks (WSNs). The cluster based routing in WSNs is a prominent approach for energy conservation of the network which provides a hierarchical data collection mechanism. In order to maximize the energy conservation of sensor nodes, this paper proposes an Energy-efficient Layered Clustering Algorithm (ELCA) for routing in wireless sensor networks. ELCA constructs two layers of clusters to reduce the transmission rate and to balance the energy consumption of sensors. As early energy depletion of clusterheads (CHs) is a major limitation in clustering, this algorithm provides local remedy for energy suffering CHs through efficient CH substitution scheme. The performance of the proposed algorithm is analysed through extensive simulation experiments and verified by compared results with existing clustering algorithms.

Incorporating Constraints in System Modularization by Interactive Clustering of Design Structure Matrices

2016 ◽  
Author(s):  
Roozbeh Sanaei ◽  
Kevin N. Otto ◽  
Katja Hölttä-Otto ◽  
Kristin L. Wood
Keyword(s):  
Complex Systems ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Design Structure Matrix ◽  
Complex Products ◽  
Pressure Fields ◽  
Design Structure ◽  
Computational Capability ◽  
New Type ◽  
Interactive Clustering

Modularity is an approach to manage the design of complex systems by partitioning and assigning elements of a concept to simpler subsystems according to a planned architecture. Functional-flow heuristics suggest possible modules that have been demonstrated in past products, but using them still leaves it to the designer to choose which heuristics make sense in a certain architecture. This constitutes an opportunity for a designer to take other constraints and objectives into account. With large complex systems, the number of alternative groupings of elements into modular chunks becomes exponentially large and some form of automation would be beneficial to accomplish this task. Clustering algorithms using the design structure matrix (DSM) representation search the space of alternative relative positioning of elements and present one ideal outcome ordering which “optimizes” a modularity metric. Beyond the problems of lack of interactive exploration around the optimized result, such approaches also partition the elements in an unconstrained manner. Yet, typical complex products are subject to constraints which invalidate the unconstrained optimization. Such architectural partitioning constraints include those associated with external force fields including electric, magnetic, or pressure fields that constrain some functions to perform or not perform in different regions of the field. There are also supplier constraints where some components cannot be easily provided with others. Overall, it is difficult to simply embed all objectives of modular thinking into one metric to optimize. We develop a new type of interactive clustering algorithm approach considering multiple objectives and partitioning constraints. Partitioning options are offered to a designer interactively as a sequence of clustering choices between elements in the architecture. A designer can incorporate constraints that determine the compatibility or incompatibility of elements by choosing among alternative groupings progressively. Our aim is to combine computational capability of clustering algorithms with the flexibility of manual approaches. Through applying these algorithms to a MRI machine injector, we demonstrate the benefits of interactive cooperation between a designer and modularity algorithms, where constraints can be naturally considered.

New Fault-Tolerant Hierarchical Routing Protocol for WSNs

2012 ◽  
Vol 433-440 ◽  
pp. 3223-3229
Author(s):  
Davood Keykhosravi ◽  
Ali Hosseinalipour
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
High Performance ◽  
Clustering Algorithm ◽  
Fault Tolerant ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Geographical Position

Clustering in wireless sensor networks is one of the crucial methods for increasing of network lifetime. There are many algorithms for clustering. One of the cluster based algorithm in wireless sensor networks is LEACH algorithm. In this paper we proposed a new clustering method for increasing of network lifetime. In proposed method Clustering is done symmetrically and the best node with respect to remained energy and distance of other nodes in comparing with each that selected as a cluster head. Although in this protocol we didn’t use GPS but we could find geographical position nodes so easily. However, failures in higher level of hierarchy e.g. cluster-head cause more damage to the system because they also limit accessibility to the nodes that are under their supervision. In this paper we propose an efficient mechanism to recover sensors from a failed cluster. In this performance of the proposed algorithm via computer simulation was evaluated and compared with other clustering algorithms. The simulation results show the high performance of the proposed clustering algorithm.

scholarly journals A job checkpointing system for computational grids

2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Mohammed Amoon
Keyword(s):  
Fault Tolerance ◽  
Failure Rate ◽  
Failure Time ◽  
Fault Tolerant ◽  
Turnaround Time ◽  
Computational Grids ◽  
Simulation Experiments ◽  
Geographically Distributed ◽  
Grid Load ◽  
Grid Resources

AbstractFault tolerance is an important property in computational grids since the resources are geographically distributed. Job checkpointing is one of the most common utilized techniques for providing fault tolerance in computational grids. The efficiency of checkpointing depends on the choice of the checkpoint interval. Inappropriate checkpointing interval can delay job execution. In this paper, a fault-tolerant scheduling system based on checkpointing technique is presented and evaluated. When scheduling a job, the system uses both average failure time and failure rate of grid resources combined with resources response time to generate scheduling decisions. The system uses the failure rate of the assigned resources to calculate the checkpoint interval for each job. Extensive simulation experiments are conducted to quantify the performance of the proposed system. Experiments have shown that the proposed system can considerably improve throughput, turnaround time, grid load and failure tendency of computational grids.

EEA

2018 ◽  
Vol 7 (2) ◽  
pp. 19-37 ◽  
Author(s):  
Hassan El Alami ◽  
Abdellah Najid
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Data Communication ◽  
High Energy ◽  
Hierarchical Design ◽  
Communication Task ◽  
Save Energy ◽  
High Energy Consumption ◽  
Communication Path

The data communication task, in wireless sensor networks (WSNs), is a major issue of high energy consumption. A hierarchical design based on a clustering algorithm is one of the approaches to manage the data communication and save energy in WSNs. However, most of the previous approaches based on clustering algorithms have not considered the length of the data communication path, which is a direct relation to energy consumption in WSNs. In this article, a novel scheme of a clustering algorithm has been proposed for reducing the data communication distance in WSNs. Hierarchical routing protocols were implemented for homogeneous and heterogeneous networks. The results show that the proposed scheme is more efficient than other protocols.

Method Based on Knowledge Modules of Hydraulic Fault and it’s Application

2011 ◽  
Vol 186 ◽  
pp. 66-70 ◽  
Author(s):  
Jin Yu ◽  
Shao Hua Chen ◽  
Guo Qin Huang
Keyword(s):  
Fault Tolerance ◽  
Hydraulic System ◽  
Fault Tolerant ◽  
Engineering Application ◽  
Electrical Signal ◽  
Power Stage ◽  
Hydraulic Signal ◽  
New Type ◽  
Novel Method ◽  
Fault Information

According to various problems by using traditional redundant fault-tolerance technology and information fault-tolerant technology, a novel method of knowledge modules of hydraulic fault (KMHF) was proposed in this paper. The principle of the method was that new type of fluid information expression units were designed to perceive and process the fault information of the system, then the information was expressed as mechanical signal, hydraulic signal or electrical signal, which could be used to implement fault tolerance at power stage. The engineering application of the method of KMHF can solve the problems of the whole fault tolerance in the hydraulic system, moreover, with it the structure of hydraulic system can be greatly simplified.

EEA

2020 ◽  
pp. 735-752
Author(s):  
Hassan El Alami ◽  
Abdellah Najid
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Data Communication ◽  
High Energy ◽  
Direct Relation ◽  
Communication Task ◽  
Save Energy ◽  
High Energy Consumption ◽  
Communication Path

The data communication task, in wireless sensor networks (WSNs), is a major issue of high energy consumption. A hierarchical design based on a clustering algorithm is one of the approaches to manage the data communication and save energy in WSNs. However, most of the previous approaches based on clustering algorithms have not considered the length of the data communication path, which is a direct relation to energy consumption in WSNs. In this article, a novel scheme of a clustering algorithm has been proposed for reducing the data communication distance in WSNs. Hierarchical routing protocols were implemented for homogeneous and heterogeneous networks. The results show that the proposed scheme is more efficient than other protocols.

An Artificial Immune Based Incremental Data Clustering Algorithm

2012 ◽  
Vol 256-259 ◽  
pp. 2935-2938
Author(s):  
Xin Xiao
Keyword(s):  
Data Clustering ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Initial Response ◽  
Secondary Response ◽  
Data Sets ◽  
Artificial Immune ◽  
Simulation Experiments ◽  
Resource Limited ◽  
Improved Function

An improved resource limited artificial immune algorithm is proposed, which is applied to the incremental data clustering. The algorithm adopts an improved function of stimulation level, allowing the system to distributing resources more reasonably. And the algorithm introduces the immune response model, simulating the initial response and the secondary response. Through simulation experiments on the UCI data sets, and comparison with the artificial immune based influential incremental clustering algorithms, it shows that the algorithm is effective, can extract data characteristics, and increases the clustering accuracy and data compression rate.

Handling WSD using Hierarchical Clustering Algorithm with sentences

2018 ◽  
pp. 83-88
Author(s):  
Mohana Priya K ◽  
Pooja Ragavi S ◽  
Krishna Priya G
Keyword(s):  
Hierarchical Clustering ◽  
Similarity Measure ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Cosine Similarity Measure ◽  
Hierarchical Clustering Algorithm ◽  
Multiple Levels ◽  
Pos Tagger ◽  
Sentence Clustering ◽  
The Right

Clustering is the process of grouping objects into subsets that have meaning in the context of a particular problem. It does not rely on predefined classes. It is referred to as an unsupervised learning method because no information is provided about the "right answer" for any of the objects. Many clustering algorithms have been proposed and are used based on different applications. Sentence clustering is one of best clustering technique. Hierarchical Clustering Algorithm is applied for multiple levels for accuracy. For tagging purpose POS tagger, porter stemmer is used. WordNet dictionary is utilized for determining the similarity by invoking the Jiang Conrath and Cosine similarity measure. Grouping is performed with respect to the highest similarity measure value with a mean threshold. This paper incorporates many parameters for finding similarity between words. In order to identify the disambiguated words, the sense identification is performed for the adjectives and comparison is performed. semcor and machine learning datasets are employed. On comparing with previous results for WSD, our work has improvised a lot which gives a percentage of 91.2%

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