Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1195
Parallel DBSCAN Clustering Algorithm Using Hadoop Map-reduce Framework for Spatial Data
Статья научная
Data clustering is the first step for future applications of big data analysis. It is a driving model for Artificial Intelligence and Machine Learning architectures. Processing large volumes of data in faster mode is a big challenge in these applications. which requires fast and efficient algorithms for handling big data. Parallel clustering algorithms are one promising design, which increases the speed of handling such big data. In this paper, a parallel algorithm for clustering a spatial dataset called the P-DBSCAN algorithm is implemented using Hadoop map-reduce framework. This research paper signifies the improvement for data clustering in data analytic applications. The new P-DBSCAN algorithm is executed over generated dataset. The result of this parallel algorithm is compared with existing DBSCAN algorithm to show improvement of runtime performance. This work offers an increase in the performance of execution time. In addition, the outcome of P-DBSCAN shows how to resolve the scalability problem of a large data set.
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Parallel Implementation of Color Based Image Retrieval Using CUDA on the GPU
Статья научная
Most image processing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In huge image databases, image processing takes very long time for run on a single core processor because of single thread execution of algorithms. Graphical Processors Units (GPU) is more common in most image processing applications due to multithread execution of algorithms, programmability and low cost. In this paper we implement color based image retrieval system in parallel using Compute Unified Device Architecture (CUDA) programming model to run on GPU. The main goal of this research work is to parallelize the process of color based image retrieval through color moments; also whole process is much faster than normal. Our work uses extensive usage of highly multithreaded architecture of multi-cored GPU. An efficient use of shared memory is needed to optimize parallel reduction in CUDA. We evaluated the retrieval of the proposed technique using Recall, Precision, and Average Precision measures. Experimental results showed that parallel implementation led to an average speed up of 6.305×over the serial implementation when running on a NVIDIA GPU GeForce 610M. The average Precision and the average Recall of presented method are 53.84% and 55.00% respectively.
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Parallel bat algorithm using mapreduce model
Статья научная
Bat Algorithm is among the most popular meta-heuristic algorithms for optimization. Traditional bat algorithm work on sequential approach which is not scalable for optimization problems involving large search space, huge fitness computation and having large number of dimensions E.g. stock market strategies therefore parallelizing meta-heuristics to run on parallel machines to reduce runtime is required. In this paper, we propose two parallel variants of Bat Algorithm (BA) using MapReduce parallel programming model proposed by Google and have used these two variants for solving the Software development effort optimization problem. The experiment is conducted using Apache Hadoop implementation of MapReduce on a cluster of 6 machines. These variants can be used to solve various complex optimization problems by simply adding more hardware resources to the cluster and without changing the proposed variant code.
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Parkinson's Brain Disease Prediction Using Big Data Analytics
Статья научная
In healthcare industries, the demand for maintaining large amount of patients' data is steadily growing due to rising population which has resulted in the increase of details about clinical and laboratory tests, imaging, prescription and medication. These data can be called "Big Data", because of their size, complexity and diversity. Big data analytics aims at improving patient care and identifying preventive measures proactively. To save lives and recommend life style changes for a peaceful and healthier life at low costs. The proposed predictive analytics framework is a combination of Decision Tree, Support Vector Machine and Artificial Neural Network which is used to gain insights from patients. Parkinson's disease voice dataset from UCI Machine learning repository is used as input. The experimental results show that early detection of disease will facilitate clinical monitoring of elderly people and increase the chances of their life span and improved lifestyle to lead peaceful life.
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Performance Analysis in Bigdata
Статья научная
Big data technologies like Hadoop, NoSQL, Messaging Queues etc. helps in BigData analytics, drive business growth and to take right decisions in time. These Big Data environments are very dynamic and complex; they require performance validation, root cause analysis, and tuning to ensure success. In this paper we talk about how we can analyse and test the performance of these systems. We present the important factors in a big data that are primary candidates for performance testing like data ingestion capacity and throughput, data processing capacity, simulation of expected usage, map reduce jobs and so on and suggest measures to improve performance of bigdata.
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Performance Analysis of 802.16 (WIMAX) Networks under Various Routing Protocols and Traffic Loads
Статья научная
The selection of an appropriate routing protocol is a key issue when designing a scalable and efficient wireless networks. In this paper, we investigate different routing protocols and evaluate their performances on 802.16 WiMAX networks. Further, we present a comparison between 802.16 and 802.11 ad hoc networks based on the performances of various rerouting protocols. The simulation results show that the table driven DSDV protocol has the best performance in terms of the delivery fraction which outperforms the rest of the protocols. In addition, we also assert from the experiments that packet delay experienced by DSDV protocol is very high. Hence, there should be a tradeoff between various performance parameters when using the DSDV protocol in 802.16 networks.
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Статья научная
Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis have recently attracted the researchers’ interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks, support vector machine, and so on. MDLP is less complex compared to other methods and does not suffer from local optima. However, sometimes classification becomes infeasible due to insufficient data in databases such as in the case of an Internet Service Provider (ISP) small and medium-sized market considered in this research. This study proposes a fuzzy Delphi method to select and gather required data. The results show that the performance of MDLP is better than other methods with respect to correct classification, at least for small and medium-sized datasets.
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Performance Analysis of MANET Routing Protocols in Different Mobility Models
Статья научная
A mobile ad-hoc network (MANET) is basically called as a network without any central administration or fixed infrastructure. It consists of a number of mobile nodes that use to send data packets through a wireless medium. There is always a need of a good routing protocol in order to establish the connection between mobile nodes since they possess the property of dynamic changing topology. Further, in all the existing routing protocols, mobility of a node has always been one of the important characteristics in determining the overall performance of the ad hoc network. Thus, it is essential to know about various mobility models and their effect on the routing protocols. In this paper, we have made an attempt to compare different mobility models and provide an overview of their current research status. The main focus is on Random Mobility Models and Group Mobility Models. Firstly, we present a survey of the characteristics, drawbacks and research challenges of mobility modeling. At the last we present simulation results that illustrate the importance of choosing a mobility model in the simulation of an ad hoc network protocol. Also, we illustrate how the performance results of an ad hoc network protocol drastically change as a result of changing the mobility model simulated.
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Performance Analysis of Most Common Encryption Algorithms on Different Web Browsers
Статья научная
The hacking is the greatest problem in the wireless local area network (WLAN). Many algorithms like DES, 3DES, AES,UMARAM, RC6 and UR5 have been used to prevent the outside attacks to eavesdrop or prevent the data to be transferred to the end-user correctly. We have proposed a Web programming language to be analyzed with five Web browsers in term of their performances to process the encryption of the programming language’s script with the Web browsers. This is followed by conducting tests simulation in order to obtain the best encryption algorithm versus Web browser. The results of the experimental analysis are presented in the form of graphs. We finally conclude on the findings that different algorithms perform differently to different Web browsers like Internet Explorer, Mozilla Firefox, Opera and Netscape Navigator. Hence, we now determine which algorithm works best and most compatible with which Web browser. A comparison has been conducted for those encryption algorithms at different settings for each algorithm such as encryption/decryption speed in the different web Browsers. Experimental results are given to demonstrate the effectiveness of each algorithm.
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Performance Analysis of Resampling Techniques on Class Imbalance Issue in Software Defect Prediction
Статья научная
Predicting the defects at early stage of software development life cycle can improve the quality of end product at lower cost. Machine learning techniques have been proved to be an effective way for software defect prediction however an imbalance dataset of software defects is the main issue of lower and biased performance of classifiers. This issue can be resolved by applying the re-sampling methods on software defect dataset before the classification process. This research analyzes the performance of three widely used resampling techniques on class imbalance issue for software defect prediction. The resampling techniques include: “Random Under Sampling”, “Random Over Sampling” and “Synthetic Minority Oversampling Technique (SMOTE)”. For experiments, 12 publically available cleaned NASA MDP datasets are used with 10 widely used supervised machine learning classifiers. The performance is evaluated through various measures including: F-measure, Accuracy, MCC and ROC. According to results, most of the classifiers performed better with “Random Over Sampling” technique in many datasets.
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Performance Analysis of Software Effort Estimation Models Using Neural Networks
Статья научная
Software Effort estimation involves the estimation of effort required to develop software. Cost overrun, schedule overrun occur in the software development due to the wrong estimate made during the initial stage of software development. Proper estimation is very essential for successful completion of software development. Lot of estimation techniques available to estimate the effort in which neural network based estimation technique play a prominent role. Back propagation Network is the most widely used architecture. ELMAN neural network a recurrent type network can be used on par with Back propagation Network. For a good predictor system the difference between estimated effort and actual effort should be as low as possible. Data from historic project of NASA is used for training and testing. The experimental Results confirm that Back propagation algorithm is efficient than Elman neural network.
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Performance Analysis of Spatial Reused Bandwidth Reservation in Ad Hoc Networks
Статья научная
In this paper, an approach for spatial reused bandwidth reservation in ad hoc networks is proposed. Resource reservation in wireless networks is an essential component that is needed to support multimedia and real-time applications, such as audio/video conferencing. On the other hand, directional antenna technology provides the capability for considerable increase in spatial reuse, which increases the efficiency of communication. In our approach for spatial reused bandwidth reservation, the source node tries to discover multiple node-disjoint paths that are capable of satisfing the desired Quality of Service (QoS) requirement in ad hoc networks using directional antennas. The simulation result shows the performance of this spatial reused bandwidth reservation approach. There is a significant gain in the performance with a decrease in the number of paths, as well as an increase in the percentage of successfully received data packets and reservation success rate.
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Статья научная
The research activities in mobile computing and wireless networks strongly indicates that mobile computers and their wireless communication links will be an integral part of the current internet works. Communication over wireless links is characterised by limited bandwidth, high latency, high bit-error rates and temporary disconnections. Most often, networks with wireless links and mobile hosts incur significant losses due to handoff. It is also most important that in wireless environment TCP (transmission control protocol) causes degraded end-to-end performance. In this paper, we tried to give solutions to these problems. We adopt a new method to improve the end-to-end reliable transport performance in mobile wireless environment by incorporating changes to network-layer at the base station and mobile host and preserve end-to-end semantics of TCP. The methodology employs NDG (normalised delay gradient) loss-predictor function to determine congestion losses from that of transmission loss. The sender window can adjust its size depending on the loss information. If the loss is due to congestion, congestion control algorithm is invoked to decrease the flow rate. If the loss is due to handoff (transmission loss), immediate-recovery algorithm is invoked to recover the losses caused by the sender TCP. Stochastic equations are used to analyse, i) arrival rate handoff calls, ii) blocking probability of handoff request, iii) distinguish packet loss due to congestion or handoff, iv) dynamics of sender window, v) queue length at the ingress point of the BS router , vi) throughput, and vii) the losses due to congestion and handoff blocking. Our results provide better way understanding the problem of calls drop due to handoff, and providing most accurate solutions for mobile wireless system.
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Performance Analysis on Throughput in 4G Network in Digital Environment with SISO Technique
Статья научная
The development of the 4G or the Long Term Evolution (LTE) is working at a very fast pace. The 4G system invention had very high prospective and goals compared to 3G. It was already thought that the system should be more competitive and secure based. Every wireless connection would be IP oriented. 4G is on its phase in improving the Quality of Service (QOS). This paper shows the comparison of the throughput delivered by the different modulation techniques which have been proposed to be used. Also comparison has been made with the different Extended Channel Models. Figures and graphs have been put forward to show the performance by the throughput delivered in digital environment and RF technology.
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Performance Comparison of Various Diversity Techniques using Matlab Simulation
Статья научная
Due to the time-varying nature of the wireless channel and presence of limited resources for the signal transmission, which faces various detrimental effects such as path-loss, delay spread, Doppler spread, shadowing and interference make it very difficult to achieve sufficient data rates. To combat the effect of multi-path fading in the wireless communication system, the diversity combining mechanism has been introduced. In this paper, we have developed an algorithm for the performance evaluation of various spatial diversity combing techniques by using Matlab simulation. The developed new algorithm combine all three diversity techniques such as maximal ratio combining (MRC), selection combining (SC) and equal gain combing (EGC) techniques The combined diversity techniques algorithm computes and compares the MRC, SC, and EGC combing techniques theoretically by using the Matlab simulation.
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Performance Evaluation of AODV, LHC-AODV, OLSR, UL-OLSR, DSDV Routing Protocols
Статья научная
Mobile ad hoc networks are type of wireless networks in which any kind of infrastructure is not used, i.e. there are no infrastructures such as routers or switches or anything else on the network that can be used to support the network structure and the nodes has mobility. The routing is particularly a challenging task in MANETs that selecting paths in a network along which to send network traffic. In this paper, the performance analysis is carried out on Ad-hoc On-demand Distance Vector (AODV), Limited Hop Count AODV (LHC-AODV), Optimized Link State Routing (OLSR), Unnecessary Loop OLSR (UL-OLSR) and Destination Sequenced Distance Vector (DSDV) protocols using NS2 simulator. The delay, throughput, and packet delivery ratio are the three common measures used for the comparison of the performance of above protocols.
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Performance Evaluation of I.T Project Management in Developing Countries
Статья научная
In recent past, IT industry has seen massive growth. However it is not much mature in developing countries, facing many challenges particularly in project management. As a result performance of IT industry is not up to the mark and unable to provide professional support as compared to internationally recognized standards to public and private sector organizations. There are many challenges such as shortage of skilled and experienced human resources and high employee turnover. Tough and competitive market condition requires the product to be extremely good in performance, timeline and accuracy. Effective project management and collaborative efforts of the Government and IT professionals can make highly successful market for IT projects. Success rate of private sector organizations is high as compared to public sector organizations in developing countries like Pakistan. In this research we have explored the performance of IT project management in public and private sector organizations of developing countries focusing Pakistan, to find out the reasons of project failure and success in both public and private sector organizations.
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Performance Evaluation of Index Schemes for Semantic Cache
Статья научная
In last decade of computing, a growing popularity for semantic cache schemes has been observed. Numerous techniques have been proposed for improved performance of semantic cache. Semantic cache is aimed towards reducing the network traffic load with the ability to address some queries without contacting the server. Semantic cache overcomes the limitations of previous page-caching and tuple-cache techniques. A prime concern of semantic cache includes query processing (query response-time) and cache management. The efficiency of semantic cache can be improved by using semantic indexing sachems. Semantic indexing sachems are segment based and hierarchical semantic indexing scheme. Both these sachems can improve the efficiency of query processing and cache management. In this paper, we have performed the evaluation of index schemes for Semantic Cache through the experimental study. Evaluations of these schemes are available in literature but experimental study is not available. Through this experiment, we have highlighted which technique is most suited in what kind of scenario.
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Статья научная
Nowadays, there are several models of computer systems finding their ways into various offices, houses, organizations as well as remote locations. Any slight malfunction of the computer system’s components could lead to loss of vital data and information. One of the sources of computer system malfunction is overheating of the electronic components. A common method of cooling a computer system is the use of cooling fan(s). Therefore, it is essential to have an appropriate control mechanism for the operation of computer system’s cooling fan in order to save energy, and prevent overheating. Failure to adopt a well designed and efficient performance controller could lead to the malfunction of a computer system. Presently, most controllers in computer systems are pulse width modulation based. That is, they make use of pulses in form of digits, 0 and 1. It was observed that inherent noise is still prevalent in the operation of computer system. Also, eventual breakdown of components is common. A new approach is therefore investigated through the use of fuzzy logic to serve as a base or platform to build an intelligent controller using a set of well defined rules to guide its operational performance. Mamdani-type fuzzy inference system and Sugeno-type fuzzy inference system were used with two input sets each and a single output function each. Simulation was carried out in MATLAB R2007a platform and operational performances of the two approaches were compared. Simulated results of the performances of the Mamdani-type fuzzy inference system based controller and the Sugeno-type fuzzy inference system based controller are presented accordingly.
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Performance Evaluation of Photovoltaic Models Based on a Solar Model Tester
Статья научная
The performances of 130 W (Solara PV) and 100 W (Sunworth PV) solar modules are evaluated using a single diode equivalent circuit. The equivalent circuit is able to simulate both the I–V and P–V characteristic curves, and is used to study the effect of the operating temperature, diode ideality factor, series resistance, and solar irradiance level on the model performance. The results of the PV characteristics curves are compared with the parameters from the manufacturing companies for each model. Afterwards, the Solara PV model is tested under different irradiance levels. The relationship between the model power versus its current under different irradiance levels is plotted, such that if the solar power meter (pyrheliometer) does not exist, the irradiance-current (G–I) curve can be used to measure solar radiation power without using the solar power meter. The measurement is achieved by moving the solar panel by a certain angle toward the solar radiation, and then measuring the corresponding current.
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