Intelligent Secured Two-Way Image Transmission Using Corvus Corone Module over WSN

Wireless Personal Communications - Two-way image communication in a wireless channel needs to be viable with channel properties such as transfer speed, energy-effective, time usage, and security...     

FSCVG: A Fuzzy Semi-Distributed Clustering Using Virtual Grids in WSN

Wireless Personal Communications - Wireless sensor network comprises of tiny devices which are powered by limited energy resources. Therefore, providing methods to reduce energy consumption is...     

Load Balanced Clustering Based on Imperialist Competitive Algorithm in Wireless Sensor Networks

Wireless Personal Communications - Energy consumption is one of the most serious issues in designing Wireless Sensor Networks (WSNs) for maximizing its lifetime and stability. Clustering is...     

A Location-less Energy Efficient Algorithm for Load Balanced Clustering in Wireless Sensor Networks

One of the biggest challenges in Wireless Sensor Networks (WSNs) is to efficiently utilise the limited energy available in the network. In most cases, the energy units of sensors cannot be replaced or replenished. Therefore, the need for energy efficient and robust algorithms for load balancing in WSNs is ever present. This need is even more pronounced in the case of cluster-based WSNs, where the Cluster Head (CH) gathers data from its member nodes and transmits this data to the base station or sink. In this paper, we propose a location independent algorithm to cluster the sensor nodes under gateways, as CHs into well defined, load balanced clusters. The location-less aspect also avoids the energy loss in running GPS modules. Simulations of the proposed algorithm are performed and compared with a few existing algorithms. The results show that the proposed algorithm shows better performance under different evaluation metrics such as average energy consumed by sensor nodes vs number of rounds, number of active sensors vs number of rounds, first gateway die and half of the gateways die.

     

Multiple Parameter Based Energy Balanced and Optimized Clustering for WSN to Enhance the Lifetime Using MADM Approaches

Wireless Personal Communications - Efficient utilization of power has recently emerged as a critical issue in sensor networks that is addressed by efficient clustering techniques. In WSN,...     

Anomaly Detection System in Cloud Environment Using Fuzzy Clustering Based ANN

Cloud computing affords lot of resources and computing facilities through Internet. Cloud systems attract many users with its desirable features. In spite of them, Cloud systems may experience severe security issues. Thus, it is essential to create an Intrusion Detection System (IDS) to detect both insider and outsider attacks with high detection accuracy in cloud environment. This work proposes an anomaly detection system at the hypervisor layer named Hypervisor Detector that uses a hybrid algorithm which is a mixture of Fuzzy C-Means clustering algorithm and Artificial Neural Network (FCM-ANN) to improve the accuracy of the detection system. The proposed system is implemented and compared with Naïve Bayes classifier and Classic ANN algorithm. The DARPA’s KDD cup dataset 1999 is used for experiments. Based on extensive theoretical and performance analysis, it is evident that the proposed system is able to detect the anomalies with high detection accuracy and low false alarm rate even for low frequent attacks thereby outperforming Naïve Bayes classifier and Classic ANN.     

一种改进的模糊核聚类红外图像分割算法

针对模糊核聚类对红外图像分割存在的不足,提出了一种改进的模糊核聚类红外图像分割算法.首先在模糊核聚类的基础上引入了隶属度和空间约束关系,有效抑制了野点;然后定义了像素对类别的认同度指数和类别对像素的排斥性度量,并将之引入到隶属度函数中,判断像素的分类合理性,提高聚类的精度,更好地分割目标和背景区域,保护目标的完整性和精确性.实验结果表明,与传统的模糊聚类分割结果相比,该算法能准确完整地分割出目标,防止背景像素和野值点对目标区域的干扰,获得良好的分割效果.     

基于最近邻聚类学习算法的模糊业务量预测器

本文根据模糊逻辑系统中的万能逼近定理,提出一个采用最近邻聚类学习长法的模糊业务量逼近器／预测器,通过对自回归（ＡＲ）过程及ＭＰＥＧ业务量的预测,了该逼近器／预测器的准确性和对业务量特性的适应性,最后讨论了该预测器在动态带宽分配中的应用。     

Highly Secured Cluster Based WSN Using Novel FCM and Enhanced ECC-ElGamal Encryption in IoT

Wireless Personal Communications - The wireless sensor networks WSN is the most substantial network utilized in the IoT based applications. The WSN consists of various sensor nodes used for the...     

Proposed Energy Efficient Algorithm for Clustering and Routing in WSN

Wireless Personal Communications - Clustering in WSN recently become big challenge and attracts many researches. Clustering is a way of grouping sensor nodes into clusters with CH responsible to...     

MCPCN: Multi-hop Clustering Protocol Using Cache Nodes in WSN

Wireless Personal Communications - Wireless Sensor Networks (WSN) are becoming an imminent result for industrialization, tracking and various other applications. Sensor nodes are deployed in the...     

Fuzzy Genetic Elliptic Curve Diffie Hellman Algorithm for Secured Communication in Networks

Wireless Personal Communications - More computations have to be done through less powerful mobile devices which includes ultra modern wearables. The huge overhead lies in the processing of the...     

基于模糊分组和监督聚类的RBF回归性能改进

为了提高RBF回归建模的精度,该文提出了一种基于模糊分组和监督聚类的RBF回归建模的新方法。基本思想是：首先利用监督聚类将训练样本模糊划分为若干子集,然后分别针对各个子集的样本分布情况进行RBF回归建模,最后利用加权组合得到最终的输出。实验表明,该方法对于目标模型的局部细节具有更好的逼近精度。     

On Balanced Clustering (Indices,Models, Examples)

Journal of Communications Technology and Electronics - The paper describes and approach to balanced clustering problems. The list of balanced structures includes balanced partitioning of a set,...     

An Energy Efficient Routing Algorithm for WSNs Using Intelligent Fuzzy Rules in Precision Agriculture

Wireless Personal Communications - Many agricultural activities can be highly enhanced by using sensor networks and data mining techniques. One of these activities is the regulation of the quantity...     

Improved K-Means Based Q Learning Algorithm for Optimal Clustering and Node Balancing in WSN

Wireless Personal Communications - A wireless sensor network is a potential technique which is most suitable for continuous monitoring applications where the human intervention is not possible. It...     

遗传模糊聚类算法在数据关联中的应用

针对传统数据关联算法存在计算量偏大或关联精度不高的问题,提出了一种利用遗传模糊聚类策略来求解数据关联问题的算法。该算法将多传感器多目标的数据关联问题看作是一类约束条件下的组合优化问题,先通过对同一时刻不同传感器提供的量测按照其相似性用遗传算法进行模糊聚类,再用聚类后的等效量测对各目标的状态进行估计。聚类方式的改进不仅增加了算法的局部寻优能力,有效地减少了计算的复杂度,而且还具备一定的野值剔除能力。仿真结果表明该算法关联精度较高,计算量适中,具有一定的工程应用价值。     

Proposing an Energy-Aware Routing Protocol by Using Fish Swarm Optimization Algorithm in WSN (Wireless Sensor Networks)

Wireless Personal Communications - Former developments and advances in micro-electro-mechanical systems have made it possible to produce and use tiny battery-powered nodes in wireless...     

A Novel Energy-Aware Clustering Method via Lion Pride Optimizer Algorithm (LPO) and Fuzzy Logic in Wireless Sensor Networks (WSNs)

Wireless Personal Communications - Recent technological advances and developments in the field of communication information systems, especially in microelectro mechanical systems have provided the...     

Mobility-Aware and Load Balancing Based Clustering Algorithm for Energy Conservation in MANET

Mobile ad hoc network (MANET) is one of wireless communication network architecture that has received a lot of attention. MANET is characterized by dynamic network topology and limited energy. With mobility-aware and load balancing based clustering algorithm (MLCA), this paper proposes a new topology management strategy to conserve energy. Performance simulation results show that the proposed MLCA strategy can balances the traffic load inside the whole network, so as to prolong the network lifetime, meanly, at the same time, achieve higher throughput ratio and network stability.