Wireless sensor network (WSN) is combination of tiny sensors made up with MEMS technology and has important applications such as target tracking and environmental monitoring. In recent times WSNs becomes more attracti...
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Wireless sensor network (WSN) is combination of tiny sensors made up with MEMS technology and has important applications such as target tracking and environmental monitoring. In recent times WSNs becomes more attractive because of their sensing ability, low cost, self-organizing nature in different environments. In this paper we have discussed two existing techniques for data communication such as Normal technique and Distance and Density Based Cluster Selection algorithm (DDCSA) and we find that these two techniques are not optimal enough to save energy in a network. In DDCSA protocols there is a problem of cluster breaking and lot of energy is consumed to reforming clusters. In this paper we enhance the Distance and Density Based Cluster Selection Algorithm (DDCSA) using Geographical Forwarding with Face Routing Technique. Simulation Results shows that our Enhanced DDCSA performs better than DDCSA & Normal technique and gives better results in term of Energy spent, Average delay and Packet delivery ratio.
The acceptable consistent matrix is one of the important issue in comparison matrix to confirm the rational of decision maker opinion. This paper presents a method using ant colony optimization(ACO) to solve the incon...
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The acceptable consistent matrix is one of the important issue in comparison matrix to confirm the rational of decision maker opinion. This paper presents a method using ant colony optimization(ACO) to solve the inconsistent comparison matrix to obtain the best consistent ratio(CR), named ACSICR. This method aims to enhance the CR by fractioning the original element to several candidates element to substitute. To evaluate the performance, the ACSICR is tested on some inconsistent comparison matrices. The experimental results have shown that the proposed algorithm is able to decrease the consistent ratio significantly.
The main focus of this work is the effort to minimize the power consumption on mobile devices such as notebooks, netbooks, tablets, tablets, smartphones, etc. by adjusting the transmission power of the wireless card, ...
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The main focus of this work is the effort to minimize the power consumption on mobile devices such as notebooks, netbooks, tablets, tablets, smartphones, etc. by adjusting the transmission power of the wireless card, thus extending the battery life. In order to achieve that, we provide a mechanism (which we call Signal Adaptation Mechanism - SAM) that optimizes the power depending on the quality of the connection. This mechanism measures the quality of the transmission and adjusts the transmission power accordingly, by utilizing an expanded array of metrics along the Received Signal Strength Indicator (RSSI), for more accurate estimation. It also aims at easy implementation on various wireless adapters. In order to evaluate, fine-tune and improve the mechanism, a list of experiments has been performed. These experiments were conducted on a real (as opposed to simulated) ad-hoc network, where the nodes of the networks followed varying moving patterns.
Image registration technique has played a major role due to the use of data from different medical imaging modalities in which your main goal is to find anatomical and/or functional matches in two or more images. SIFT...
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ISBN:
(纸本)9781467397964
Image registration technique has played a major role due to the use of data from different medical imaging modalities in which your main goal is to find anatomical and/or functional matches in two or more images. SIFT algorithm was used to extract a set of descriptors in IVUS images of two different pullbacks and to determine the number of common features between each pair of images. Similarity map was created to establish correspondences between two PCI images. Our method, with saltatory condition, was proved be a good choice in the experiments and in the real case, showing great stability in the establishment of correspondences and reducing overall time used for the diagnosis and/or monitor the development of coronary heart disease.
In Mobile Ad hoc Networks (MANET), mobile nodes are organized randomly without any fix access point. Due to the limited bandwidth and dynamic topology of nodes, the network congestion occurs. Congestion control is the...
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ISBN:
(纸本)9781479936984
In Mobile Ad hoc Networks (MANET), mobile nodes are organized randomly without any fix access point. Due to the limited bandwidth and dynamic topology of nodes, the network congestion occurs. Congestion control is the main problem in ad-hoc networks. Congestion control is associated to controlling traffic incoming into a telecommunication network. The end-to-end Transmission Control Protocol (TCP) performance degrades rapidly with increase load in number of hops. This is one of the biggest problems of TCP over wireless networks. In this research work, we proposed to develop the Effective TCP Congestion Control AODV routing which consists of congestion monitoring on the basis of queue length and rate control. The overall congestion status is measured in congestion monitoring. In route establishment, we propose congestion control in the particular channel, queue length of packet, traffic rate based overall congestion standard, packet loss rate and packet dropping ratio to monitor the congestion status. Based on the congestion standard, the congestion less based routing is established to reduce the packet loss, high overhead, long delay in the network. By extensive simulation, the proposed scheme achieves better throughput, packet delivery ratio, low end-to-end delay and overhead than the normal TCP based AODV routing.
Recent work has proposed an enhancement of Formal Concept Analysis (FCA) in a tunable, hybrid formal context including both numerical and nominal data [1]. This work introduces FCknn, that is a granular knn classifier...
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Recent work has proposed an enhancement of Formal Concept Analysis (FCA) in a tunable, hybrid formal context including both numerical and nominal data [1]. This work introduces FCknn, that is a granular knn classifier based on hybrid concepts, whose effectiveness is demonstrated on benchmark datasets from the literature including both numerical and nominal data. Preliminary experimental results compare well with the results by alternative classifiers from the literature. Formal concepts are interpreted as descriptive decision-making knowledge (rules) induced from the data.
This paper deals with the problem of sum rate maximization for a multiuser orthogonal frequency-division multiple access channel with secrecy rate constraints. We consider the case of a multiple-antenna base station (...
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This paper deals with the problem of sum rate maximization for a multiuser orthogonal frequency-division multiple access channel with secrecy rate constraints. We consider the case of a multiple-antenna base station (BS) and several single-antenna downlink receivers; a single secure user, a single eavesdropper and several normal users (without secrecy requirements). The eavesdropper intends to wiretap the message of the secure user and the BS aims to protect its transmission by appropriately scheduling normal users and enforcing spatial multiplexing between them and the secure user. A frequency (subchannel) and power allocation problem that aims to maximize the sum rate of the normal users, while a secrecy rate constraint is ensured for the secure user, is formulated. The resulting resource allocation problem is non-convex. Based on the dual problem and some well-defined transformations, we provide an iterative resource allocation algorithm with linear complexity with respect to the number of normal users and subchannels. In addition, two low-complexity solutions that are based on the decoupling of the subchannel and the power allocation subproblems, are investigated. Numerical results are provided to illustrate the performance of all the proposed solutions.
As computing becomes ubiquitous, researchers and engineers aim to exploit the potential of the pervasive systems in order to introduce new types of services and address inveterate and emerging problems. This process w...
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As computing becomes ubiquitous, researchers and engineers aim to exploit the potential of the pervasive systems in order to introduce new types of services and address inveterate and emerging problems. This process will, eventually, lead us to the era of urban computing and the Internet of Things; the ultimate goal being to improve our quality of life. But these concepts typically require direct and constant interaction of computing systems with the physical world in order to be realized, which inevitably leads to the introduction of a range of safety and privacy issues that must be addressed. One such important aspect is the fine-grained control of access to the resources of these pervasive embedded systems, in a secure and scalable manner. This paper presents an implementation of such a secure policy-based access control scheme, focusing on the use of well-established, standardized technologies and considering the potential resource-constraints of the target heterogeneous embedded devices. The proposed framework adopts a DPWS-compliant approach for smart devices and introduces XACML-based access control mechanisms. The proof-of-concept implementation is presented in detail, along with a performance evaluation on typical embedded platforms.
An efficient parallel implementation of the recently proposed Slackmin classification algorithm that minimizes the mean squared slack variables energy is proposed in this paper. The efficacy of the resulted scheme is ...
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An efficient parallel implementation of the recently proposed Slackmin classification algorithm that minimizes the mean squared slack variables energy is proposed in this paper. The efficacy of the resulted scheme is demonstrated both in terms of accuracy and computation speed. The parallelization of the Slackmin algorithm is achieved in the framework of GPU programming. Based on this framework the “cuLSlackmin” algorithm for linear problems was implemented, by using the CUDA C/C++ programming model and proposed herein. The introduced parallel algorithm is making use of the advantages imposed by the GPU architecture and achieves high classification rates in a short computation time. A set of experiments with some UCI datasets have shown the high performance of the cuLSlackmin algorithm compared to the Slackmin, LIBSVM and GPULIBSVM algorithms. The high performance of cuLSlackmin algorithm makes it appropriate for big data classification problems.
Femtocells provide an attractive solution to locally improve the data rates and the coverage of future mobile networks including 5G. However, nearby non-subscribed users may experience severe interference. Hybrid acce...
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ISBN:
(纸本)9781479958641
Femtocells provide an attractive solution to locally improve the data rates and the coverage of future mobile networks including 5G. However, nearby non-subscribed users may experience severe interference. Hybrid access operation allows femtocells to serve non-subscribers by allowing them access to part of the spectrum. In this work, we propose a distributed process that allows the hybrid femtocell to defines the spectrum access for the two types of users. The mechanism takes into account the prior condition of the users and tries to minimize the femtocell's impact to the rest of the network. We also introduce a power control mechanism within clusters of femtocells. The mechanism relieves the femtocell operating in hybrid access mode and its subscribed users, by coordinating accordingly the nearby femtocells' transmission.
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