Varying Number Of Nodes Research Articles

Numerical integration of implicit functions for the initialization of the VOF function

A numerical method of initializing cell volume fraction demarcated by implicitly defined fluid interfaces is presented. Each cell of the computational domain is examined for the presence of the reference phase. When a cell is not full or empty, limits are found that allow volume fraction to be computed by numerical integration. The method enlists a number of algorithms including root finding and minimum search on an oriented segment, a preconditioned conjugate gradient minimum search on a cell face and a double Gauss–Legendre integration with a variable number of nodes, among others. Practical multi-phase fluid examples in two- and three-dimensions are presented to demonstrate the accuracy and robustness of the method.

A Hybrid Approach for Scheduling Virtual Machines in Private Clouds

Quality of Service (QoS) support in private clouds is a challenging process because of the limitations of available resources and the high rate of received jobs, which leads to an NP hard scheduling problem. In private clouds, resource owners are usually interested in maximizing their resource utilization and completion rates while minimizing the turnaround time of their jobs, which complicates the scheduling problem even more. Haizea is an eminent cloud scheduler that offers high performance in terms of job turnaround time and completion rate. However, Haizea, and cloud schedulers in general, suffer from low resource utlization. Additionally, cloud schedulers usually consider only end users’ demands, while providers’ demands are entirely neglected. This is because an infinite pool of resources is assumed, which is difficult to achieve and simply not true in private clouds. Conversely, Condor, the eminent High Throughput Computing (HTP) scheuler, is known for addressing these shortcomings by formulating owner's and user's requirements as a logical expression evaluated based on the context which result is high resource utilization. Unfortunatly, this comes with the price of long execution time. As each of Haizea and Condor has its own advantages and limitations, in this paper, we propose a hybrid Haizea and Condor approach (HHCS) which utilizes techniques from both schedulers in a way that maximizes their advantages and overcomes their limitations. The proposed approach has been tested thoroughly in a simulated private cloud environment under various numbers of nodes and jobs. Experimental results illustrated an enhanced performance in terms of resources utilization without compromising the job turnaround time or the job completion rate.

Performance Analysis of Cache Consistency Maintenance in Mobile Environment using Agent Technique

This paper illustrates three Agents Based Techniques namely, Thread Based Cache Consistency Model, Multiple Server Cache Consistency Model, and Cluster Based Cache Consistency Models used to solve the problems of cache consistency maintenance and also compared with existing method. The drawbacks of existing method are latency, excessive bandwidth wastage, query delay, server overloads as well as network traffic. In the Thread Based Cache Consistency Model, the log is maintained in both server and client, it is easy for server as well as client to make their data object reliable. Agents at server and client make an internal request response operation(s) to access or update data object. It is easy to update the cached data and as well to maintain consistency between client and server. The Multiple Server Cache Consistency Models where the node is designed as a middle server (master client cache) between server and clients, some of the client data cache is placed in a middle server. The middle server is near the client, as result the communication cost and energy consumption is comparatively less. It reduces server’s workload. The Cluster Based Cache Consistency Model designed as a Cluster head node between the server and the client using agent technique, effectively reduces the query latency. These three Agent Based Models are implemented in Ns2 and their performance was analysed and compared with existing method. Agent Based Technique resulted in better performance in relation to update delay, through various numbers of nodes and update rate.

Performance Analysis of Cache Consistency Maintenance in Mobile Environment using Agent Technique

This paper illustrates three Agents Based Techniques namely, Thread Based Cache Consistency Model, Multiple Server Cache Consistency Model, and Cluster Based Cache Consistency Models used to solve the problems of cache consistency maintenance and also compared with existing method. The drawbacks of existing method are latency, excessive bandwidth wastage, query delay, server overloads as well as network traffic. In the Thread Based Cache Consistency Model, the log is maintained in both server and client, it is easy for server as well as client to make their data object reliable. Agents at server and client make an internal request response operation(s) to access or update data object. It is easy to update the cached data and as well to maintain consistency between client and server. The Multiple Server Cache Consistency Models where the node is designed as a middle server (master client cache) between server and clients, some of the client data cache is placed in a middle server. The middle server is near the client, as result the communication cost and energy consumption is comparatively less. It reduces server’s workload. The Cluster Based Cache Consistency Model designed as a Cluster head node between the server and the client using agent technique, effectively reduces the query latency. These three Agent Based Models are implemented in Ns2 and their performance was analysed and compared with existing method. Agent Based Technique resulted in better performance in relation to update delay, through various numbers of nodes and update rate.

Lag-based effective connectivity applied to fMRI: A simulation study highlighting dependence on experimental parameters and formulation

A vast repertoire of methods is currently available to study effective brain connectivity based on neuroimaging data, among which lag-based measures can be distinguished. Although several studies have previously assessed the performance of such measures, their validity in different conditions remains unclear. In the current study, several lag-based effective connectivity measures are tested and benchmarked using simulated fMRI data, conceived to reflect a broad range of different situations with practical interest. The main goal is two-fold: 1) to provide a thorough overview of lag-based effective connectivity measures, and 2) to assess their performance in specific experimental conditions, thereby providing guidance for future effective connectivity studies involving fMRI. We focus on well-known lag-based measures, cover existing improvements and alternative formulations in some cases: Granger causality (GC), Geweke's Granger causality (GGC), directed transfer function (DTF), partial directed coherence (PDC), phase slope index (PSI), and transfer entropy (TE). Benchmarking consists in identifying causal relations in local field potential (LFP) networks that have their output convolved with a canonical hemodynamic response function (HRF) with varying node number, topology, coupling strength, neuronal delay, repetition time (TR), signal-to-noise ratio (SNR) and HRF variability. In a first set of simulations, we cover all possible combinations of discretized values of the previous variables, for networks with 2 and 3 nodes, and find that the measure with best performance (time-domain Granger Causality) is able to detect neuronal delays of a few hundreds of milliseconds with TRs between 0.25 and 2s and neuronal delays below 100ms for TRs that are also below 100ms, with more than 80% accuracy in realistic conditions. For networks with more than 3 nodes, we find that the number of nodes and the density of causal links degrade sensitivity, especially if the number of observations does not compensate for the increase in nodes, and that clustered networks can be more easily identified. In conclusion, this study argues in favor of the applicability of lag-based measures in the context of fMRI, provided that a stringent set of experimental specifications is met and that the chosen measure is applied with full knowledge of its limitations and specific constraints.

Analysis and Optimization of Max Flow Min-cut

Today we are working with the networks all around and that’s why it becomes very important to find the effective flow of the commodity within that network. This paper aims to provide an analysis of the best known algorithm for calculating maximum flow of any network and to propose an approximate algorithm, which can solve the same problem with lesser complexity, desirably lesser than the complexity of the known Stoer-Wagner algorithm. This paper addresses this problem with a new approach, which uses upper bound values of each node in the network.Results are compared with fixed number of nodes and variable number of nodes in the network. Moreover networks with variable densities are also considered. Results are obtained by programming the both algorithms in C++.Unix scripts are also used for formatting the results.

Application of Artificial Neural Networks for Optimization of Preparation of Insulin Nanoparticles Composed of Quaternized Aromatic Derivatives of Chitosan

The aim of this research was to develop an artificial neural network (ANN) in order to design a nanoparticulate oral drug delivery system for insulin. The pH of polymer solution (X1), concentration ratio of polymer/insulin (X2) and polymer type (X3) in 3 level including methylated N-(4-N,N- dimethyl aminobenzyl) chitosan, methylated N-(4-pyridinyl) chitosan, and methylated N-(benzyl) chitosan are considered as the input values and the particle size, zeta potential, PdI, and entrapment efficiency (EE %) as output data. ANNs are employed to generate the best model to determining the relationships between input and response values. In this research, a multi-layer percepteron with different topologies has been tested in order to define the one with the best accuracy and performance. The optimization was used by minimizing the error between the predicted and observed values. Three training algorithms (Levenberg-Marquardt (LM), Bayesian-Regularization (BR), and Gradient Descent (GD)) were employed to train ANNs with various numbers of nodes, hidden layers and transfer functions by random selection. The accuracy of prediction data were assayed by the mean squared error (MSE).The ability of all algorithms was in the order: BR>LM>GD. Thus, BR was selected as the best algorithm.

Parallel Training of An Improved Neural Network for Text Categorization

This paper studies parallel training of an improved neural network for text categorization. With the explosive growth on the amount of digital information available on the Internet, text categorization problem has become more and more important, especially when millions of mobile devices are now connecting to the Internet. Improved back-propagation neural network (IBPNN) is an efficient approach for classification problems which overcomes the limitations of traditional BPNN. In this paper, we utilize parallel computing to speedup the neural network training process of IBPNN. The parallel IBNPP algorithm for text categorization is implemented on a Sun Cluster with 34 nodes (processors). The communication time and speedup for the parallel IBPNN versus various number of nodes are studied. Experiments are conducted on various data sets and the results show that the parallel IBPNN together with SVD technique achieves fast computational speed and high text categorization correctness.

A Novel Cross-Layer Network Architecture and Its Performance Analysis Using Mobile Ad Hoc Network Routing Protocol

 Abstract—In this work a novel cross layer architecture is proposed for dynamic selection of routing protocol in Mobile Ad Hoc Network (MANET). Switching function is designed based on Quality of Service parameters and performance of proposed cross layer architecture is evaluated over quality of service parameters. Three routing protocols: Ad-Hoc On Demand Distance Vector (AODV), Destination Sequenced Distance Vector (DSDV) and Dynamic Source Routing (DSR) with variable number of nodes are used for performance analysis of proposed cross layer network architecture.

Reliability Analysisof Route RedundancyModel for EnergyEfficient Node Disjoint Multipath RoutinginWireless Sensor Networks

Theobjectiveofevery sensornodeinasensornetworkistosendthesenseddatainthephenomenatothesinknode. Manyrouting protocols select an optimal path to increase the network lifetime in sensor networks. The consumption bythe nodes along this optimal path is high, thereby causing their early death. In the multipath routing, path reliability ishigh, becauseoftheavailabilityof alternatepathstotheoptimalpaths.Thiswork proposesa theoreticalframework to study the reliability analysis of route redundancy model for node disjoint multipath networks in wireless sensor networks. The reliability of route redundancyin single path and multiple paths with varied number of nodes and its probability values are discussed.

Successful Transmission Rate of Mobile Terminals with Agents in Segmented Ad Hoc Network

Mobile Wireless Ad-Hoc Network (MANET) is a special kind of network, where all of the nodes move in time. Random movement is the commonly used to model the mobility in this network. Beside as a host, each node is intended to help relaying packets of neighboring nodes using multi-hop routing mechanism in order to solve problem of dead communication. In recent years, a variety of routing protocols have been proposed specially to accommodate this environment followed with its performance evaluations, likes DSDV, DSR, AODV, and extension OSPF. Researches in this network are mostly simulation based. Research efforts haven't focused much in evaluating network performance when applied to variable number of nodes that involving agents and distributed over several network areas. The paper performed simulations using MANET simulator, which carried out based on the extension OSPF routing protocol. The modification of OSPF protocol had intended to suit the OSPF standard mechanisms for operating with high performance over wireless networks characterized by a broadcast-based transmission medium, in which the physical layer connectivity is not fully meshed. Extensive simulation scenarios have been conducted in the simulator with various numbers of nodes, random and uniform movement direction, and different agent’s quantity with different size of network areas. In the performance evaluation of successful transmission (data) packets, the OSPF protocol with throughput weighted metric will be tested under different combination conditions of scenarios.

Simulation based Performance Comparison of AODV, FSR and ZRP Routing Protocols in MANET

Mobile Ad hoc NETwork (MANET) is a collection of mobile nodes that are arbitrarily located so that the interconnections between nodes are dynamically changing. In MANET mobile nodes forms a temporary network without the use of any existing network infrastructure or centralized administration. A routing protocol is used to find routes between mobile nodes to facilitate communication within the network. The main goal of such an ad hoc network routing protocol is to establish correct and efficient route between a pair of mobile nodes so that messages delivered within the active route timeout interval. Route should be discovered and maintained with a minimum of overhead and bandwidth consumption. This paper presents performance evaluation of three different routing protocols i.e. Ad hoc OnDemand Distance Vector (AODV), Fisheye State Routing (FSR) and Zone Routing Protocol (ZRP) in variable pause times and variable number of nodes. We have used random waypoint mobility model to design the network and performed simulations by using QualNet version 5.0 Simulator [1] from Scalable Networks. Performance of AODV, FSR and ZRP is evaluated based on Average end-to-end delay, Packet delivery ratio, Throughput and Average Jitter.

BER Analysis for Distributed Beamforming With Phase Errors

The probability of error for distributed transmit beamforming with phase errors is not available in closed form in the literature. This paper presents an investigation into the bit error ratio (BER) of distributed transmit beamforming with phase errors for equal power transmission in wireless sensor networks. We derive two distinct formulas to approximate the error probability performance for binary phase-shift keying (BPSK) over Rayleigh fading channels that correspond to small numbers of nodes (e.g., N ≤ 10) and large numbers of nodes (e.g., N ≥ 20), respectively. Simulation results show a good match with the analytical results. The effects of the phase errors on the beamforming performance are examined for various numbers of nodes and different levels of total transmit power.

Adaptive meshing and analysis using transitional quadrilateral and hexahedral elements

In adaptive finite element analysis, h-type refinement can be achieved basically in two ways: (i) small elements are connected directly to large elements with full compatibility at element interfaces and (ii) transitional elements are employed to link up elements of different sizes. While there is no difficulty in generating gradation triangular and tetrahedral meshes, generation of quadrilateral and hexahedral meshes of varying element sizes without severe element distortion proved to be a formidable task. The use of transitional elements allows meshes to be refined without element distortion, and the price that we have to pay is to develop general and efficient transitional elements in two and three dimensions. Transition elements, which satisfy the patch test, can be formulated by means of the enhanced assumed strain (EAS) method, which are in general more efficient than the incompatible elements. Alternatively, in this paper, we try to develop a series of versatile transition elements based on the hybrid stress approach. Direct designing stress fields for transition elements is just too complicated and especially impractical for 3D transition hexahedral elements. However, we found that the same stress field could be used for transition elements with variable number of nodes. By means of elimination and through numerical studies on some benchmark problems, 7- and 24-mode stress fields are adopted, respectively for 2D quadrilateral and 3D hexahedral hybrid stress transition elements. Strategy for generating refinement transition element meshes will be discussed, and the size of elements generated by the 1-irregular mesh restriction is compared with the predicted element size. The comparison shows that the meshing strategy employed in this study can effectively lead to an optimal mesh whose solution error is smaller than the prescribed one.

Destabilization of Terrorist Networks through Argument Driven Hypothesis Model

Social network analysis has been used for quite some time to analyze and understand the behavior of nodes in the network. Theses nodes could be individuals or group of persons, events or organizations etc. In fact these nodes could be any thing importantly, these nodes propagate and obviously have attributes. In this paper a very novel and absolutely new approach to SNA is presented, for locating the important key players in the network. The system also predicts a path comprising of selected nodes which shows the vulnerability of the network and if the path along with these nodes is removed it can reduce/destabilize or even destroy the structure of the network. The paper provides comparative results for a couple of random networks with various numbers of nodes and connections. In addition to these example networks it performs a case study of the nine eleven, 62 node networks (by Valdis E. Krebs) to predict a path for its destabilization. This network is selected to benchmark our proposed model framework. The results obtained with various network analysis shows that it works better than other analysis measures for example based on degree, betweeness and closeness etc.

Single hidden layer artificial neural network models versus multiple linear regression model in forecasting the time series of total ozone

Present paper endeavors to develop predictive artificial neural network model for forecasting the mean monthly total ozone concentration over Arosa, Switzerland. Single hidden layer neural network models with variable number of nodes have been developed and their performances have been evaluated using the method of least squares and error estimation. Their performances have been compared with multiple linear regression model. Ultimately, single-hidden-layer model with 8 hidden nodes have been identified as the best predictive model.

Breast cancer survival according to number of nodes removed.

Results from randomized trials indicate a 5.4% survival advantage associated with axillary dissection. To gain insight on survival outcomes when less than an axillary dissection is performed, we performed a retrospective analysis to determine survival outcome for node-negative and node-positive breast cancer patients when a variable number of nodes were excised. The data analyzed in this paper are from the Surveillance, Epidemiology, and End Results (SEER) database, from which 72,102 patients were selected whose breast cancer had been diagnosed in 1988 or later and who were aged 40-79 years at diagnosis, had a single primary lesion, and had 0 to 3 positive lymph nodes. Cases were separated into age groups (40 to 49 and 50 to 79 years), and node-negative cases were separated from those with one to three positive nodes. This analysis indicates that even when all regional lymph nodes are pathologically negative, the number of nodes removed is associated with survival. In the group of breast cancer patients who had one to three pathologically positive nodes, as with the node-negative group, the higher the number of nodes removed, the greater the survival. The hazard rate for death in the node-negative group was roughly 5% less for each additional five nodes removed. For the node-positive group, the hazard rate for death was between 8% and 9% less for each additional five nodes removed. This retrospective study supports the notion that removal of regional nodes, even when such nodes are interpreted as pathologically negative, is important for the long-term survival of breast cancer patients.

Dynamic simulation of a tethered satellite system using finite elements and fuzzy sets

Dynamic simulations are performed for the NASA planned propulsive small expendable deployer system (ProSEDS) space tether mission using two finite element analysis codes. The first is a specialized code for simulating tethered space systems. The second is an in-house flexible multibody dynamics code adapted herein for modeling tethered satellites. The simulation of the ProSEDS mission is divided into two operations: a tether deployment operation and an electrodynamic operation. The specialized code uses a fixed number of nodes and finite elements in simulating the deployment operation, while the in-house code uses a variable number of nodes and elements. The application of each approach is discussed. A fuzzy-set technique is used in conjunction with the two codes to assess the effect of parameter variations on the deployment and electrodynamic operation of the ProSEDS tether. Detailed numerical simulations reveal that the deployment operation is not sensitive to variations in material parameters, but is sensitive to variations in the initial tether ejection momentum and to controller parameters. The electrodynamic operation is found to be highly sensitive to variations in earth's magnetic field and, to a lesser extent, variations in material and plasma parameters.

Persistent reservation protocol for variable-length messages in WDM-based local networks

The author proposes a persistent reservation protocol in a wavelength division multiplexing (WDM)-based local network using a passive star topology. With this protocol, once a node reserves a data channel, the node persistently uses the channel until its message is completely transmitted. Therefore, the protocol needs only one tuning time for a node to begin to transmit its message, which reduces deterioration of throughput due to tuning overhead. The proposed protocol can efficiently support variable-length messages. The network can accommodate a variable number of nodes and can operate independently of any change of the number of nodes. Hence, any ‘new’ node can join the network at anytime without network re-initialisation. Moreover, with the protocol, data channel and destination conflicts can be avoided. Throughput–delay characteristics are analysed with a finite population model, and are verified by simulation results.

A BEM FORMULATION FOR EVALUATING CONDUCTIVE HEAT TRANSFER RATES IN PARTICULATE SYSTEMS

A formulation based on the boundary-element method (BEM) to solve the conductive heat transfer problem between a particle and an adjacent heat exchange surface or between two particles is presented. This simple geometric configuration corresponds to a unit cell representing the thermal behavior near the wall or in the bulk of fixed and fluidized beds. The BEM is formulated by employing a variable number of nodes defined by the same quadrature points on which the integral coefficients of the influence matrix are evaluated. It is shown that this is a very efficient choice as compared to standard BEM formulations.