Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1203
An Efficient Diffusion Load Balancing Algorithm in Distributed System
Статья научная
In distributed computing system some nodes are very fast and some are slow and during the computation many fast nodes become idle or under loaded while the slow nodes become over loaded due to the uneven distribution of load in the system. In distributed system, the most common important factor is the information collection about loads on different nodes. The success of load balancing algorithm depends on how quickly the information about the load in the system is collected by a node willing to transfer or accept load. In this paper we have shown that the number of communication overheads depends on the number of overloaded nodes present in the domain of an under loaded nodes and vice-versa. We have also shown that communication overhead for load balancing is always fairly less than KN but in worst case our algorithm’s complexity becomes equal to KN.
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An Efficient Dimension Reduction Quantization Scheme for Speech Vocal Parameters
Статья научная
To achieve good reconstruction speech quality in a very low bit rate speech codecs, an efficient dimension reduction quantization scheme for the linear spectrum pair (LSP) parameters is proposed based on compressed sensing (CS). In the encoder, the LSP parameters extracted from consecutive speech frames are shaped into a high dimensional vector, and then the dimension of the vector is reduced by CS to produce a low dimensional measurement vector, the measurements are quantized using the split vector quantizer. In the decoder, according to the quantized measurements, the original LSP vector is reconstructed by the orthogonal matching pursuit method. Experimental results show that the scheme is more efficient than that of conventional matrix quantization scheme, the average spectral distortion reduction of up to 0.23dB is achieved in the DFT transform domain. Moreover, in the approximate KLT transform domain, this scheme can obtain transparent quality at 5 bits/frame with drastic bits reduction compared to other methods.
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An Efficient Distributed Power Control in Cognitive Radio Networks
Статья научная
In cognitive radio networks, when primary users (PUs) do not use a shared frequency band, secondary users (SUs) are allowed to use that frequency band. However, when SU using frequency band and reclaiming PU also wants to use this band, there are two solutions: SU jumps to another existing spectrum band or stays in the same frequency band and changes its power so that interference in the reclaiming PUs does not exceed a threshold. Since the first solution interrupts the SUs' work, the second solution is more appropriate. Therefore, power control in cognitive networks is absolutely significant which should receive more attention. In the previous work (TPC-CBS) [2], TPC algorithm has been used for power control. The drawback of this algorithm is fixed target SIRs. In other words, while using this algorithm, all the users having enough sources or extra sources reach the same target SIR, which is not desirable. Therefore, in this paper, we are going to solve it by means of the proposed algorithm called "An Efficient Distributed Power Control Algorithm for Cognitive Networks (EDPC)". By the proposed algorithm, when a user has a bad channel, its SIR sets to the minimum target SIR and, when it has a good channel, its SIR will be more than the minimum value. Moreover, by means of fuzzy logic systems (FLS), the value of interference on reclaiming PU caused by SUs is checked in each iteration and power level of SUs is decreased if this value exceeds a threshold. Simulation results show that using our proposed algorithm not only allows SUs and PUs use frequency band simultaneously, but also enhances throughput significantly in comparison with the previous approaches (TPC-CBS).
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An Efficient Framework for Creating Twitter Mart on a Hybrid Cloud
Статья научная
The contemporary era of technological quest is buzzing with two words - Big Data and Cloud Computing. Digital data is growing rapidly from Gigabytes (GBs), terabytes (TBs) to Petabytes (PBs), and thereby burgeoning data management challenges. Social networking sites like Twitter, Facebook, Google+ etc generate huge data chunks on daily basis. Among them, twitter masks as the largest source of publicly available mammoth data chunks intended for various objectives of research and development. In order to further research in this fast emerging area of managing Big Data, we propose a novel framework for doing analysis on Big Data and show its implementation by creating a ‘Twitter Mart’ which is a compilation of subject specific tweets that address some of the challenges for industries engaged in analyzing subject specific data. In this paper, we adduce algorithms and an holistic model that aids in effective stockpiling and retrieving data in an efficient manner.
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Статья научная
This paper focuses on an empirical hand gesture recognition system in the domain of image processing and machine learning. The hand gesture is probably the most intuitive and frequently used mode of nonverbal communication in human society. The paper analyzes the efficiency of the Histogram of Oriented Gradients (HOG) as the feature descriptor and Support Vector Machine (SVM) as the classification model in case of gesture recognition. There are three stages of the recognition procedure namely image binarization, feature extraction, and classification. The findings of the paper show that the model classifies hand gestures for the given dataset with satisfactory efficiency. The outcome of this work can be further utilized in practical fields of real-world applications dealing with non-verbal communication.
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An Efficient Graph-Coloring Algorithm for Processor Allocation
Статья научная
This paper develops an efficient exact graph-coloring algorithm based on Maximum Independent Set (MIS) for allocating processors in distributed systems. This technique represents the allocated processors in specific time in a fully connected graph and prevents each processor in multiprocessor system to be assigned to more than one process at a time. This research uses a sequential technique to distribute processes among processors. Moreover, the proposed method has been constructed by modifying the FMIS algorithm. The proposed algorithm has been programmed in Visual C++ and implemented on an Intel core i7. The experiments show that the proposed algorithm gets better performance in terms of CPU utilization, and minimum time for of graph coloring, comparing with the latest FMIS algorithm. The proposed algorithm can be developed to detect defected processor in the system.
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An Efficient IBE Scheme using IFP and DDLP
Статья научная
In 1984, Shamir introduced the concept of an identity-based encryption. In this system, each user needs to visit a private key generation (PKG) and identify him- self before joining a communication network. Once a user is accepted, the PKG will provide him with a secret key. In this way, if a user wants to communicate with others, he only needs to know the “identity” of his communication partner and the public key of the PKG. There is no public file required in this system. However, Shamir did not succeed in constructing an identity based encryption, but only in constructing an identity-based signature (IBS) scheme. In this paper, we propose an identity based encryption (IBE) based on the factorization problem (IFP) and double discrete logarithm problem (DDLP) and we consider the security against a conspiracy of some entities in the proposed system and show the possibility of establishing a more secure system.
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Статья научная
In recent days, the smart city project has been emerging concept all over the world. In this process, the proper communication between the sensors and the smart devices, and identification of optimal path between sensors and mutation sensors in large geographical area is very difficult. The main objective has been considered to overcome the drawbacks as mentioned above. The proposed algorithm is efficient to provide integrated communication of IoT-based ubiquitous networking (UBN) devices to improve in large geographically distributed area. The data storage capacity and accuracy of sensors and smart devices are enhanced using the proposed algorithm. The communication latency and data pre-processing of IoT-based UBN nodes deployed in smart cities are reduced. The proposed algorithm also analyses the performance of IoT-based UBN nodes by considering geographical testbeds that represent a smart city scenario. The analysis and comparison are carried out by considering the heuristic parameters. The proposed algorithm will also optimize the communication latency and data pre-processing time by analyzing various sensitivity levels by considering the heuristic parameters in different probability of nodes in smart cities. The proposed IoT-based UBN computing devices improve the objective function due to proper integrated communication between the sensors using a machine learning based regression algorithm. The proposed algorithm also identifies the probability sensitivity of optimal path between smart devices in a smart city thereby enhancing the connectivity of mutated sensor nodes. The proposed algorithm also enhances the probability of smart device connectivity to improve the accuracy, flexibility and large geographical coverage using machine learning based regression algorithm.
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An Efficient String Matching Technique for Desktop Search to Detect Duplicate Files
Статья научная
Information retrieval is used to identify the relevant documents in a document collection, which is matching a user's query. It also refers to the automatic retrieval of documents from the large document corpus. The most important application of information retrieval system is search engine like Google, which identify those documents on the World Wide Web that are relevant to user queries. In most situations, users may download the files that are already downloaded and stored in their computer. Then, there is a chance of multiple copies of the files that are already stored in different drives and folders on the system, which in turn reduces the performance of the system and these files occupy a lot of memory space. Analyzing the contents of the file and finding their similarity is one of the major problems in text mining and information retrieval. The main objective of this research work is to analyze the file contents and deletes the duplicate files in the system. In order to perform this task, this research work proposes a new tool named Duplicate File Detector Tool i.e. DFDT. DFDT helps the user to search and delete duplicate files in the system at a minimum time. It also helps to delete the duplicate files not only with the same file category, but also with different file categories. Boyer Moore Horspool and Knuth Morris Pratt string searching algorithms are existing algorithms and these algorithms are used to compare the file contents for finding their similarity. This work also proposes a new string matching algorithm named as W2COM (Word to Word COMparison). From the experimental results it is observed that the newly proposed W2COM string matching algorithm performance is better than Boyer Moore Horspool and Knuth Morris Pratt algorithms.
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An Empirical Study on Testing of SOA based Services
Статья научная
Service-Oriented Architecture (SOA) removed the gap between software and business. Today, there is a business transformation among enterprises and they adopt a service based information technology (IT) model. So, testing is necessary for SOA based applications. This paper investigates different type of approaches and techniques that address the testing problems of SOA based services. Here we also investigate the differences between SOA and web services and traditional testing and SOA testing. Various testing levels are also discussed in detail. This paper also expresses various testing perspectives, challenges of SOA testing and review the many testing approaches and identify the problems that improve the testability of SOA based services.
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An Energy Effective WBAN Architecture for Athletes Efforts Analysis under a Common Activity
Статья научная
Wireless Body Area Network (WBAN) is one of the most critical real time networks. In order to increase network lifetime, several protocols have been proposed in the Literature. Majority of these protocols are based on either coverage or residual energy of the network. However, none of the protocols is based on node criticality, communication count, coverage and residual energy. In this paper, we have taken into consideration all the above stated parameters to determine the optimal path for transmission of message. In particular, we are implementing this scenario for Athlete Activity Monitoring to identify the athlete with maximum physical stamina. As per best of our knowledge, only intra-BAN routing protocols are proposed till date. However, in this paper we have simulated Athlete Activity Monitoring scenario for intra-WBAN and inter-WBAN architecture. It is clear from the simulation results that our scheme performs much better in terms of energy consumption than earlier routing schemes.
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Статья научная
Consolidation of storage into IP SANs (Internet protocol storage area network) has led to a combination of multiple workloads of varying demands and importance. To ensure that users get their Service level objective (SLO) a technique for isolating workloads is required. Solutions that exist include cache partitioning and throttling of workloads. However, all these techniques require workloads to be classified in order to be isolated. Previous works on performance isolation overlooked the classification process as a source of overhead in implementing performance isolation. However, it’s known that linear search based classifiers search linearly for rules that match packets in order to classify flows which results in delays among other problems especially when rules are many. This paper looks at the various limitation of list based classifiers. In addition, the paper proposes a technique that includes rule sorting, rule partitioning and building a tree rule firewall to reduce the cost of matching packets to rules during classification. Experiments were used to evaluate the proposed solution against the existing solutions and proved that the linear search based classification process could result in performance degradation if not optimized. The results of the experiments showed that the proposed solution when implemented would considerably reduce the time required for matching packets to their classes during classification as evident in the throughput and latency experienced.
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An Experimental Analysis on Performance and Energy Saving in Mobile Cloud Computing
Статья научная
Mobile Cloud Computing is a combination of mobile, cloud and wireless network where data storage and processing happens outside the mobile device. The storage capacity, processing power and battery life can be improved by moving resource intensive applications onto the cloud. In this paper, the performance of the mobile device is measured by using four different sorting techniques. Two different strategies were used for execution. In the first strategy, the input, execution and the output happens on the mobile device. In the other strategy, the input and output happens on the mobile device while the execution of the sorting techniques is offloaded to the server. The parameters considered for measurement are the execution time and mobile device’s energy consumption. The results show that offloading the task to the server reduces the execution time and energy consumption on the mobile device.
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An Exploratory Analysis between the Feature Selection Algorithms IGMBD and IGChiMerge
Статья научная
Most of the data mining and machine learning algorithms will work better with discrete data rather than continuous. But the real time data need not be always discrete and thus it is necessary to discretize the continuous features. There are several discretization methods available in the literature. This paper compares the two methods Median Based Discretization and ChiMerge discretization. The discretized values obtained using both methods are used to find the feature relevance using Information Gain. Using the feature relevance, the original features are ranked by both methods and the top ranked attributes are selected as the more relevant ones. The selected attributes are then fed into the Naive Bayesian Classifier to determine the predictive accuracy. The experimental results clearly show that the performance of the Naive Bayesian Classifier has improved significantly for the features selected using Information Gain with Median Based Discretization than Information Gain with ChiMerge discretization.
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Статья научная
A mathematical model and a solving strategy for the Pickup and Delivery Problem with three-dimensional loading constraints regarding a combinatorial configuration instead of a traditional approach that utilizes Boolean variables is proposed. A traditional one-to-one Pickup and Delivery Problem in a combination with a problem of packing transported items into vehicles by means of the proposed combinatorial generation algorithm is solved.
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An ICT based solution for virtual garment fitting for online market place
Статья научная
In this paper, we describe various technologies that are being used in virtual garment fitting and simulation. There, we have focused on the usage of anthropometry in the clothing industry and avatar generation of virtual garment fitting. Most commonly used technologies for avatar generation in virtual environment have been discussed in this paper such as generic body model method and laser scanning technologies. Moreover, this paper includes the usage of real-time tracking technologies used in virtual garment fitting like markers and depth cameras. Apart from these, virtual clothing methods such as geometrical, physical and hybrid-based models were also discussed in this paper. As ease allowance has a major impact on virtual cloth fitting, it is also considered in this paper relating to similar research studies. As the final stage, our proposed design has been explained including the steps of the experiment that has been conducted to generate a two-dimensional model of the garment item. Within this paper, all the above-mentioned areas were described thoroughly while stating the existing gap of the virtual garment fitting in online marketplaces and our proposed solution to bridge that gap.
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An Image Encryption Scheme Based on Bit Circular Shift and Bi-directional Diffusion
Статья научная
A novel image encryption scheme based on chaotic system is proposed. The proposed encryption scheme utilizes one tent map to generate a pseudo-random sequence and then shift the bits of the expanding 0-1 image circularly so as to shuffle the image gray values. To make the encryption scheme resist differential attack efficiently, generalized Arnold maps and Bernoulli shift maps are applied to produce two pseudo-random gray value sequences and then diffuse the gray values bi-directionally. The bit circular shift process and diffusion processes greatly confuse the statistical nature between plain-images and cipher-images. Security analyses including key sensitivity analysis, key space analysis, statistical analysis, differential attack analysis and information entropy analysis are performed. All the experimental results demonstrate that the proposed image encryption scheme possesses large key space to frustrate brute-force attack efficiently and can resist statistical attack, differential attack, etc.
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An Improved Active Shape Model Application onFacial Feature Localization
Статья научная
An improved active shape model is proposed in this paper. The proposed algorithm includes the following four aspects. Firstly, this paper adopts a semi-automatic facial feature points marking tool. Secondly, this paper proposes to extract 2D gradient feature on the highest level and the higher level of multi-resolution pyramid images, and use Gabor wavelet transformation to extract the lowest level’s 2D texture feature. Thirdly, this paper adopts a new method of decomposition of multi-resolution pyramid. Pyramid images are got by wavelet transformation. Finally, this paper uses an improved searching scheme of multiresolution pyramid. The length of 2D profile searching rectangle is changed according to different pyramid levels. Experimental results demonstrate that the proposed algorithm exhibits better performance than the original ASM.
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An Improved Classification Model for Fake News Detection in Social Media
Статья научная
Fake news dissemination is a critical issue in today’s fast-changing network environment. Existing classification models for fake news detection have not completely stopped the spread because of their inability to accurately classify news, thus leading to a high false alarm rate. This study proposed a model that can accurately identify and classify deceptive news articles content infused on social media by malicious users. The news content, social-context features and the respective classification of reported news was extracted from the PHEME dataset using entropy-based feature selection. The selected features were normalized using Min-Max Normalization techniques. A predictive fake news detection model was formulated as a stacked ensemble of three algorithms. The model was simulated and its performance was evaluated by benchmarking with an existing model using detection accuracy, sensitivity, and precision as metrics. The result of the evaluation showed a higher 17.25% detection accuracy, 15.78% sensitivity, but lesser 0.2% precision than the existing model. Thus, the proposed model detects more fake news instances accurately based on news content and social content perspectives. This indicates that the proposed classification model has a better detection rate, reduces the false alarm rate of news instances and thus detects fake news more accurately.
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An Improved Kerberos Scheme Based on Dynamic Password
Статья научная
By studying the Kerberos authentication scheme, an improved authentication scheme is raised, which is based on Dynamic Password Method. In the improved scheme, user’s password can be effectively protected, and the authentication is double between users and severs. Also, the scheme can resist jacking connection attack. The improved scheme is more secure and more practical than the original one.
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