Volume-1 Issue-5, November 2011 – International Journal of Soft Computing and Engineering (IJSCE)

E0251101511

IJSCE Journal — Sat, 02 Oct 2021 05:23:46 +0000

The International Journal of Soft Computing and Engineering (IJSCE) has ISSN: 2231-2307 (online), an open-access, peer-reviewed, periodical bi-monthly international journal. This journal is published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) in January, March, May, July, September and November.The journal aims to publish high-quality peer–reviewed original articles in the area of Soft Computing and Engineering that covers Data Communication and Networking, Artificial Intelligence and Neural Networking, Image Processing and Recognition, Software Engineering and Project Management (SEPM), Computer Graphics and Multimedia (CGM), Data Mining, Cryptography and Network Security, Smart Computing and Information Processing, Internet of Things (IoT), Computation Intelligence and Analytics, Machine Learning (ML) and Knowledge Mining (KM), Operating System, Data Base Management System (DBMS), Data Structure and Algorithm (DSA), Object Oriented Analysis and Design (OOAD), and all interdisciplinary streams of Soft Computing and Engineering. #Addressing, Routing, Switching and Location Management #Broadband, Mobile, Wired, Wireless Internet #Networks: Adhoc and Sensor Networks, High Speed Networks, Mobile and #Wireless Networks #Network Architectures #Network Based Applications #Network Protocols #Network Operations & Management #Network Security Trust & Privacy #Cross Layer Design and Optimization #Internet and Web Applications #Network Measurement & Performance Analysis #Next Generation Internet & Web Architectures #Peer to Peer and Overlay Networks #QOS And Resource Management #Recent Trends & Developments in Computer Networks #Self-Organizing Networks and Networked Systems #Ubiquitous Networks #Virtual & Overlay Networks #Wireless Mesh Networks and Protocols #Wireless Multimedia Systems #Personal and Wearable Networks #Information-Centric Networking #Embedded Networks #Opportunistic Networking #Delay-Tolerant Networks #Cognitive Radio Networks #Vehicular Networks #Smart Grid Communications #Underwater Sensor Networks #Cyber-Physical Systems #Social Networks #Green Networking #Overlay and Peer-To-Peer Networks #Local-Area and Metropolitan-Area Networks #Storage-Area Networks #Routing and Transport Protocols #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Internet of Things #Link Technologies #Adaptive Networking Applications #Authentication, Authorization, Accounting #Security and Privacy #Cross-Layer Optimization #Multimedia and Real-Time Communication #Machine-To-Machine Communications for Smart Environments #Smart Cities #Network Traffic Characterization and Measurements #Network Management, Reliability and QoS #Performance Evaluation of Networks #Testbeds for Network Experiments #Network Coding #Optical and High-Speed Access Networks #High Performance Computing #Digital System and Logic Design #Networked-Driven Multicourse Chips #Information-Centric Networking #Opportunistic Networking #Mobile and Ubiquitous Networking #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Adaptive Networking Applications #Antenna and Communications Devices #Microstrip Antenna #Microwave #Radar and Satellite #Smart Antenna #MIMO Antenna #Wireless Communication #RFID Network and Applications #5G Communication #6G Communication #Neural Networks #Fuzzy Logic #Simulated Biological Evolution Algorithms (Like Genetic Algorithm) #Ant Colony Optimization(etc) #Reasoning and Evolution #Intelligence Applications #Computer Vision and Speech Understanding #Multimedia and Cognitive Informatics #Data Mining and Machine Learning Tools #Heuristic and Ai Planning Strategies and Tools #Computational Theories of Learning #Technology and Computing (Like Particle Swarm Optimization) #Intelligent System Architectures #Knowledge Representation #Bioinformatics #Natural Language Processing #Multiagent Systems #Supervised Learning #Unsupervised Learning #Deep Learning #Big Data and Ai Approaches #Reinforcement Learning #And Learning with Generative Adversarial Networks #Regression and Prediction #Problem Solving and Planning #Clustering #Classification #Neural Information Processing #Vision and Speech Perception #Heterogeneous and Streaming Data #Probabilistic Models and Methods #Reasoning and Inference #Marketing and Social Sciences #Knowledge Discovery #Web Mining #Information Retrieval #Design and Diagnosis #Game Playing #Streaming Data #Music Modelling and Analysis #Robotics and Control #Multi-Agent Systems #Active Vision and Robotic Systems #Architecture of Imaging and Vision Systems #Autonomous Vehicles #Character and Handwritten Text Recognition #Chemical and Spectral Sensitization #Chemistry of Photosensitive Materials #Coating Technologies #Coding and Transmission #Cognitive Aspects of Image Understanding #Color Imaging #Communication of Visual Data #Data Fusion from Multiple Sensor Inputs #Display and Printing #Document Image Understanding # Generation and Display #Holography #Image Analysis and Interpretation #Image Capturing #Image Databases #Image Generation #Image Manipulation #Image Permanence #Image Processing #Image Processing Applications #Image Processing: Coding Analysis and Recognition #Image Representation #Image Sensing #Imaging Systems and Image Scanning #Implementation and Architectures #Latent Image #Materials for Electro-Photography #Monitoring and Surveillance #Network Architecture for Real-Time Video Transport #New Visual Services Over ATM/Packet Network #Non-Impact Printing Technologies #Object Modeling and Knowledge Acquisition #Photoconductors #Photographic Emulsions #Photopolymers #Prepress and Printing Technologies #Processing and Analysis #Protocols for Packet Video #Remote Image Sensing #Retrieval and Multimedia #Scene Modeling #Signal-Processing Aspects of Image Processing #Storage and Transmission #Video Coding Algorithms and Technologies for ATM/P #Ethics of Software Engineering and Management #Software Life Cycles Development Models #Project Planning and Management #Software Requirements Analysis #Software Design Analysis #Software Testing and Integration #Software Implementation and Maintenance #Software Maintenance and Maintainability #Software Metrics or Attributes #Software Risk Assessment and Containment #Reliability #Software Quality and Quality Assurance #Software Cost Estimation #Object Oriented Developments #Object Oriented Metrics #Object Oriented Testing #Formal Notations #3D Reconstruction #Computer Animation #Computational Fabrication #Computational Geometry #Computational Photography #Computer Vision for Computer Graphics #Data Compression for Graphics #Geometric Modelling #Geometric Processing #HCI and Computer Graphics #Human Modelling #Image Analysis #Image Based Rendering #Image Processing #Machine Learning for Graphics #Medical Imaging #Pattern Recognition #Physically Based Modelling #Illumination and Rendering ethods #Robotics and Vision #Saliency Methods #Scientific Visualization #Shape and Surface Modelling #Shape Analysis and Image Retrieval #Shape Matching #Sketch-based Modelling #Solid Modelling #Stylized rendering #Textures #Virtual and Augmented Reality #Visual Analytics #Volume Rendering #Data Mining #Data Science #Big Data #Data Warehouse #Visualization #Security #Privacy #Big DaaS #Scalable Computing #Cloud Computing #Knowledge Discovery #Integration #Transformation #Information Retrieval #Social Data and Semantics #Mining Functions #Data Regression #Data Classification #Anomaly Detection #Data Clustering #Data Association #Data Regression #Data Cleaning #Feature Selection and Extraction #Data Mining Algorithms #Apriori #Decision Tree #Generalized Linear Models #K-Means #Minimum Description Length #Naive Bayes #Non-Negative Matrix Factorization #0-Cluster #Support Vector Machines #Data Preparation #Mining Unstructured Data #Artificial Intelligence #Future Directions and Challenges in Data Mining #Industrial Challenges in Data Mining #Cryptographic Protocols #Cryptography and Coding #Untrace-Ability #Privacy and Authentication #Key Management #Authentication #Trust Management #Quantum Cryptography #Computational Intelligence in Security #Artificial Immune Systems #Biological & Evolutionary Computation #Intelligent Agents and Systems #Reinforcement & Unsupervised Learning #Autonomy-Oriented Computing #Coevolutionary Algorithms #Fuzzy Systems #Biometric Security #Trust Models and Metrics #Regulation and Trust Mechanisms #Data Integrity #Models for Authentication #Trust and Authorization #Wireless Network Security #Information Hiding #Data & System Integrity #Access Control and Intrusion Detection #Intrusion Detection and Vulnerability Assessment #Authentication and Non-Repudiation #Identification and Authentication #Insider Threats and Countermeasures #Intrusion Detection & Prevention #Secure Cloud Computing #Security Information Systems Architecture and Design and Security Patterns #Security Management #Security Requirements (Threats, Vulnerabilities, Risk, Formal Methods, etc.) #Sensor and Mobile ad hoc Network Security #Service and Systems Design and QOS Network Security #System Security #Intrusion Detection #Secure end Systems #Secure Operating Systems #Data Base Security #Security Infrastructures #Security Evaluation #Software Security #Security and Privacy in Mobile Systems#Security and Privacy in Pervasive/Ubiquitous Computing #Security and Privacy in Web Services #Security and Privacy Policies #Security Area Control #Security Deployment #Security Engineering #Security for Grid Computing #Security in Distributed Systems #Network Security #Internet Security #Firewalls #Mobile Security #Security Agents #Protocols #Anti-Virus and Anti-Hacker Measures #Content Protection #Software Protection #Tamper Resistant Software #Electronic Commerce #Electronic Government #Health #Telecommunications #Mobility #Foundations #Privacy #Access Control #Authentication #Identification #Applied Cryptography #Formal Methods in Information Security #IoT & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Blockchain-enabled IoT Device and Data Security and Privacy #Application of WSN in IoT #Cloud Resources Utilization in IoT #Wireless Access Technologies for IoT #Mobile Applications and Services for IoT #Machine/ Deep Learning with IoT & IoE #Smart Sensors and Internet of Things for Smart City #Logic, Functional programming and Microcontrollers for IoT #Sensor Networks, Actuators for Internet of Things #Data Visualization using IoT #IoT Application and Communication Protocol #Big Data Analytics for Social Networking using IoT #IoT Applications for Smart Cities #Emulation and Simulation Methodologies for IoT #IoT Applied for Digital Contents #Soft Computing #Advance Ubiquitous Computing #Parallel Computing #Distributed Computing #Machine Learning #Information Retrieval #Expert Systems #Data Mining #Text Mining #Data Warehousing #Predictive Analysis #Data Management #Big Data Analytics #Big Data Security #Nature Inspired Computing #Reconfigurable Computing #Cloud, Cluster, Grid and P2P Computing #Biomedical Computing #Green Computing #Mobile Computing #Nano Ubiquitous Computing #Context Awareness and Personalization, Autonomic and Trusted Computing #Internet Computing #Sequential, Parallel and Distributed Algorithms and Data Structures #Approximation and Randomized Algorithms #Graph Algorithms And Graph Drawing #On-Line and Streaming Algorithms #Analysis of Algorithms and Computational Complexity #Algorithm Engineering #Web Algorithms #Exact And Parameterized Computation #Algorithmic Game Theory #Computational Biology #Foundations of Communication Networks #Computational Geometry #Discrete Optimization #Software Engineering Methodologies #Agent-based Software Engineering #Artificial Intelligence Approaches to Software Engineering #Component-based Software Engineering #Embedded and Ubiquitous Software Engineering #Aspect-based Software Engineering #Empirical Software Engineering #Search-Based Software Engineering #Automated Software Design and Synthesis #Computer-Supported Cooperative Work #Automated Software Specification #Reverse Engineering #Software Engineering Techniques and Production Perspectives #Requirements Engineering #Software Analysis, Design and Modelling #Software Maintenance and Evolution #Software Engineering Tools and Environments #Software Engineering Decision Support #Software Design Patterns #Software Product Lines #Process and Workflow Management #Reflection and Metadata Approaches #Program Understanding and System Maintenance #Software Domain Modelling and Analysis #Software Economics #Multimedia and Hypermedia Software Engineering #Software Engineering Case Study and Experience Reports #Enterprise Software, Middleware, and Tools #Artificial Intelligent Methods, Models, Techniques #Artificial Life and Societies #Swarm Intelligence #Smart Spaces #Autonomic Computing and Agent-Based Systems #Autonomic Computing #Adaptive Systems #Agent Architectures, Ontologies, Languages and Protocols #Multi-Agent Systems #Agent-Based Learning and Knowledge Discovery #Interface Agents #Agent-Based Auctions and Marketplaces #Secure Mobile and Multi-Agent Systems #Mobile agents #SOA and Service-Oriented Systems #Service-Centric Software Engineering #Service Oriented Requirements Engineering #Service Oriented Architectures #Middleware for Service Based Systems #Service Discovery and Composition #Service Level Agreements (Drafting, Negotiation, Monitoring and Management) #Runtime Service Management #Semantic web #Data Modelling, Mining and Data Analytics #Aggregation, Integration, and Transformation #Web and Text Mining #Data Mining Methods, Techniques, and Tools #Data Analytics Modelling and Algorithms #Patterns and Frameworks #Data Visualization #Knowledge Systems and Engineering #Knowledge Acquisition #Knowledge-based and Expert Systems #Knowledge Representation and Retrievals #Knowledge Engineering Tools and Techniques #Time and Knowledge Management Tools #Knowledge Modelling, Integration, Transformation, and Management #Uncertainty Knowledge Management #Knowledge Visualization #Mobile Computing and Mobile System Engineering #Mobile App Design and Development #Innovative Mobile Applications #Pervasive Computing #Mobile System Validation and Test Automation #Software & System Quality of Service #Soft Computing #Software and System Testing Methods #Quality Assurance Process, Standards, and Systems #Software Safety Systems #Software Test Automation and Tools #Software Dependability, Reliability, Scalability #Software & System Security #Software and System Security and Privacy #Mobile App Security and Privacy #Encryption Methods and Tools #Security Service Systems #Cloud, Sensor Cloud and Mobile Cloud Security #Mobile System Integrity, Security, And Fault Tolerance #Emergent Topics #Cloud Computing and Innovative Cloud-Based Application Systems #Mobile Cloud Computing and Application Services #Big Data Analytics Application Systems #Innovative Sensing Cloud and Systems #Large-Scale Cyber Systems #IoT and Smart City Application Systems #Big Data Quality Validation #Big Data Application Quality Services #Smart Learning and Innovative Education Systems #Learning Software Design Engineering #Smart Learning Methods and Environments #Online Learning Systems #Mobile Enabled Learning Systems and Tools #PhD Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #ESCI #Science #Journal #Conference #SSRN #PubLons #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLon

Application of Continues Wavelet Transform to Investigate the Resolution Effect of Digital Elevation Model on Topographic Index Distribution
Vahid Nourani
Vahid Nourani, Associate Prof., Dept. of Water Resources Eng., Faculty of Civil Eng., Univ. of Tabriz, Tabriz, Iran; Formerly, Visiting Associate Prof., St. Anthony Falls Lab. and NCED, Dept. of Civil Eng., Univ. of Minnesota, USA.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 26, 2011. | Manuscript published on November 05, 2011. | PP: 405-410 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0251101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Current progress in computer, geographic information system (GIS) and remote sensing technology has led to the LIDAR (light detection and ranging) data, as a new generation of high-resolution digital elevation model (DEM). Although such a high resolution DEM can be a useful tool for terrain analysis, high amount of noise is also expected to be existent in a mega-data set. To deal with this problem in this study, continues wavelet transform (CWT), as a mathematical filter, was employed to extract slope, specific area and topographic index which are important parameters in hydro-environmental studies at different resolutions. In this way the proposed methodology was applied to 1-m resolution LIDAR DEM of the Elder Creek River watershed where is a sub-basin of the South Folk Eel River basin at California. The results were also compared favorably with the results of a classic method. The result indicates that smoothing ability of the wavelet can be a promising DEM processing alternative to cope with the noise and pits of a high resolution DEM.
Keywords: DEM, Elder Creek River, GIS, LIDAR Topography, Wavelet transform.

Download PDF

The post E0251101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0253101511

IJSCE Journal — Sat, 02 Oct 2021 05:17:52 +0000

Floating-Point FPGA: Architecture Performance and Modeling
Shaik Ayesha¹, B.V. Ramana², K.V. Ramana Rao³
¹Shaik Ayesha, M. Tech, Department of ECE, Pydah College of Engineering & Technology, India.
²B.V. Ramana, M. Tech, Department of ECE, Pydah College of Engineering & Technology, India.
³K.V. Ramana Rao, Associate Professor & Head, Department of ECE, Pydah College of Engineering & Technology, India.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 26, 2011. | Manuscript published on November 05, 2011. | PP: 402-404 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0253101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents a novel architecture for domain-specific FPGA devices. This architecture can be optimized for both speed and density by exploiting domain-specific information to produce efficient reconfigurable logic with multiple granularity. In the reconfigurable logic, general-purpose fine grained units are used for implementing control logic and bit-oriented operations, while domain-specific coarse-grained units and heterogeneous blocks are used for implementing data paths; the precise amount of each type of resources can be customized to suit specific application domains. Issues and challenges associated with the design flow and the architecture modeling are addressed. Examples of the proposed architecture for speeding up floating point applications are illustrated. We assume that current proposed architecture can achieve 2.5 times improvement in speed and 18 times reduction in area on average, when compared with traditional FPGA devices on selected floating point benchmark circuits.
Keywords: Architecture, field-programmable gate array (FPGA), Floating Point, Application domains, modeling.

Download PDF

The post E0253101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0252101511

IJSCE Journal — Sat, 02 Oct 2021 05:07:38 +0000

Compact Zigzag Inverted-F Antenna with Matching Network for Wi-Fi Operation in Portable Devices
Md. Selim Hossain¹, Debabrata Kumar Karmokar², Khaled Mahbub Morshed³
¹Md. Selim Hossain, Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh.
²Debabrata Kumar Karmokar is with the department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh.
³Khaled Mahbub Morshed is with the department of Electronics & Communication Engineering, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 26, 2011. | Manuscript published on November 05, 2011. | PP: 386-401 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0252101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents a compact zigzag inverted-F antenna with matching network for Wi-Fi operation in portable devices. The antenna occupies a very small area of 8 × 18 mm2 and provides high gain of 6.91 dBi with the peak return loss of -49.75 dB, VSWR of 1.006 and input impedance of 50.2045 Ω at 5.5 GHz. This antenna covers a 10 dB return loss bandwidth of 609 MHz (5250 MHz~5859 MHz). In addition an impedance matching pie filter is used to ensure impedance matching between the source and the antenna. As well, the antenna has acceptable radiation characteristics
Keywords: Inverted-F antenna (IFA), Compact Antenna, Matching Network (MN), Zigzag IFA, Voltage Standing Wave Ratio (VSWR), Wi-Fi.

Download PDF

The post E0252101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0250101511

IJSCE Journal — Sat, 02 Oct 2021 04:59:02 +0000

Wire Type Multiband Strip Antenna for WiMAX /WLAN Operations
Md. Selim Hossain¹, A. N. M. Enamul Kabir², Debabrata Kumar Karmokar³
¹Md. Selim Hossain is with the Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
²A. N. M. Enamul Kabir is with the Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
³Debabrata Kumar Karmokar is with the Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 26, 2011. | Manuscript published on November 05, 2011. | PP: 389-395 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0250101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents a wire type multiband strip antenna for WiMAX and WLAN operations by means of numerical simulations. The dimension of the antenna is 39×30 mm2 and provides an impedance bandwidth of 300 MHz (2350-2650 MHz) and 130 MHz (5490-5620 MHz) at lower and upper frequency band respectively, which fully covers the 2.4, 2.5 and partially covers the 2.3, 5.5 GHz bands. The antenna contains very high peak gains of 8.25, 8.43, 8.46 and 6.43 dBi at 2.3, 2.4, 2.5 and 5.5 GHz band respectively with less than 0.2, 0.1, 0.3 and 1.5 dBi gain variations within the 10 dB return loss bandwidth. The VSWR of the antenna varies between 1.20~1.80 and 1.06~1.83 at the lower and upper resonant frequency bands respectively and the peak values of the return loss are -20.85 and -30.71dB. The antenna has good omnidirectional radiation characteristics at E-plane and H-plane.
Keywords: Strip Antenna, Multiband Antenna, Numerical Electromagnetic Code (NEC), WiMAX, WLAN.

Download PDF

The post E0250101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0249101511

IJSCE Journal — Sat, 02 Oct 2021 04:53:26 +0000

Mac Architecture – Accumulator Based on Booth Encoding Parallel Multiplier
K. Hima Bindu¹, K. Bala Souri², K. V. Ramana Rao³
¹K. Hima Bindu, M. Tech, Department of ECE, Pydah College of Engineering & Technology, India.
²K. Bala Souri, M. Tech, Department of ECE, Pydah College of Engineering & Technology, India.
³K.V. Ramana Rao, Associate Professor & Head, Department of ECE, Pydah College of Engineering & Technology, India.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 26, 2011. | Manuscript published on November 05, 2011. | PP: 385-388 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0249101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The MAC provides high speed multiplication with accumulative addition. In this paper, we study the various parallel MAC architectures and then implement a design of parallel MAC based on some booth encodings such as radix-4 booth encoder and some final adders such as CLA, Kogge stone adder and then compare their performance characteristics. The one most effective way to increase the speed of a multiplier is to reduce the number of the partial products. Although the number of partial products can be reduced with a higher radix booth encoder, but the number of hard multiples that are expensive to generate also increases simultaneously. To increase the speed and performance, many parallel MAC architectures have been proposed. Parallelism in obtaining partial products is the most common technique used in this implemented architecture.
Keywords: Radix-4 Booth multiplier, CLA, multiplier and accumulator (MAC).

Download PDF

The post E0249101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0248101511

IJSCE Journal — Sat, 02 Oct 2021 04:47:29 +0000

Establishing Job Scheduling and Checkpointing in Multi-Cluster Systems
K. Akshitha¹, B. V. S. S. R. S. Sastry², M. V. Vijaya Saradhi³
¹K. Akshitha, Department of IT , Aurora’s Engineering College, Bhuvanagiri, Andhra Pradesh, India.
²B. V. S. S. R. S. SASTRY, Department of IT, Aurora’s Engineering College, Bhuvanagiri, (Andhra Pradesh), India.
³Dr. M. V. Vijaya Saradhi, Department of IT, Aurora’s Engineering College, Bhuvanagiri, Andhra Pradesh, India.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 24, 2011. | Manuscript published on November 05, 2011. | PP: 380-384 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0248101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Multi-site parallel job schedulers can improve average job turn-around time by making use of fragmented node resources available throughout the grid. By mapping jobs across potentially many clusters, jobs that would otherwise wait in the queue for local resources can begin execution much earlier; thereby improving system utilization and reducing average queue waiting time. Recent research in this area of scheduling leverages user-provided estimates of job communication characteristics to more effectively partition the job across system resources. In this paper, we address the impact of inaccuracies in these estimates on system performance and show that multi-site scheduling techniques benefit from these estimates, even in the presence of considerable inaccuracy. While these results are encouraging, there are instances where these errors result in poor job scheduling decisions that cause network over-subscription. This situation can lead to significantly degraded application performance and turnaround time. Consequently, we explore the use of job check pointing, termination, migration, and restart (CTMR) to selectively stop offending jobs to alleviate network congestion and subsequently restart them when (and where) sufficient network resources are available. We then characterize the conditions and the extent to which the process of CTMR improves overall performance.
Keywords: Parallel job scheduling; check pointing; migration; clusters; grid scheduling.

Download PDF

The post E0248101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0246101511

IJSCE Journal — Sat, 02 Oct 2021 04:41:12 +0000

Establishing Security for Group Communication in Multicast Environment
B. V. S. S. R. S. Sastry¹, K. Akshitha², M. V. Vijaya Saradhi³
¹B. V. S. S. R. S. SASTRY, Department of IT, Aurora’s Engineering College, Bhuvanagiri, (Andhra Pradesh), India.
²K. Akshitha, Department of IT , Aurora’s Engineering College, Bhuvanagiri, (Andhra Pradesh), India.
³Dr. M. V. Vijaya Saradhi, Department of IT, Aurora’s Engineering College, Bhuvanagiri, (Andhra Pradesh), India.
Manuscript received on October 15, 2011. | Revised Manuscript received on October 24, 2011. | Manuscript published on November 05, 2011. | PP: 372-379 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0246101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Multicast is an internetwork service that provides efficient delivery of data from a source to multiple receivers. It reduces the bandwidth requirements of the network and the computational overhead of the host devices. This makes multicast an ideal technology for communication among a large group of participants. Secure group communications involves many service types include teleconferencing, pay TV and real-time delivery of stock quotes. IP multicast is the traditional mechanism to support multicast communications. Multicast security includes group membership control, secure key distribution, secure data transfer and copyright protection. This paper is an overview of the schemes proposed for group key management, authentication and watermarking in wired networks with fixed members and wireless networks with mobile members.
Keywords: Multimedia, key management, authentication, multicast security, watermarking, access control, copyright protection.

Download PDF

The post E0246101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0245101511

IJSCE Journal — Sat, 02 Oct 2021 04:32:18 +0000

Semantic Document Classification using Lexical Chaining & Fuzzy Approach
Upasana Pandey¹, S. Chakraverty², Bhawna Juneja³, Ashima Arora⁴, Pratishtha Jain⁵
¹Upasana Pandey, Computer Engineering, Netaji Subhas Institute of Technology, Delhi University, New Delhi, India.
²S. Chakraverty, Computer Engineering, Netaji Subhas Institute of Technology, Delhi University, New Delhi, India.
³Bhawna Juneja, Information Technology, Netaji Subhas Institute of Technology, Delhi University, New Delhi, India.
⁴Ashima Arora, Information Technology, Netaji Subhas Institute of Technology, Delhi University, New Delhi, India.
⁵Pratishtha Jain, Information Technology, Netaji Subhas Institute of Technology, Delhi University, New Delhi, India.
Manuscript received on October 13, 2011. | Revised Manuscript received on October 24, 2011. | Manuscript published on November 05, 2011. | PP: 367-371 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0245101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: We propose a novel approach to classify documents into different categories using lexical chaining. In this paper we present a text categorization technique that extracts lexical features of words occurring in a document. Two kinds of lexical chains based on the WordNet and Wikipedia reference sources are created using the semantic neighborhood of tokens. The strength of each lexical chain is determined with the help of TF/IDF, category keyword strength and relative position of tokens in the document. Each category is assigned a weight depending upon the value obtained after the lexical chain computation. Fuzzy logic is incorporated to generate a range for each category using a triangular membership function. The document belongs to the category which satisfies the range criteria. Lexical chaining has large applicability in automated email spam filtering, topic spotting, email routing.
Keywords: Lexical Chaining, TF-IDF, Wikipedia, WordNet.

Download PDF

The post E0245101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0244101511

IJSCE Journal — Sat, 02 Oct 2021 04:23:57 +0000

Comparative Analysis of Cluster Based Routing Protocols used in Heterogeneous Wireless Sensor Network
Poonam Tyagi¹, Ravinder Prakash Gupta², Rakesh Kumar Gill³
¹Poonam Tyagi, Research Scholar, Department of Electronics & Communication, JNU, Jaipur, Rajasthan, India.
²Ravinder Prakash Gupta, Associate Professor, Department of Electronics & Communication, JNU, Jaipur, Rajasthan, India.
³Rakesh Kumar Gill, Assistant Professor, Department of Electronics & Communication, GITM, Gurgaon, Haryana, India.
Manuscript received on October 13, 2011. | Revised Manuscript received on October 24, 2011. | Manuscript published on November 05, 2011. | PP: 362-366 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0244101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Energy Efficient are one of the most practical solutions in order to handle with the requirements of large-scale wireless sensor networks (WSN). Energy consumption is one of the basic problem of WSNs. In this paper we have compare the performance of (DEEC) Distributed Energy Efficient routing protocol in terms of energy consumption, alive nodes, and packet transmission .We propose a new approach to exploit efficiently the network energy, by increasing the network lifetime. We have used a clustering technique so that the energy consumption of the network decreases, packet transmission increases and alive nodes increases. Simulation results reveal that the lifetime of proposed algorithm is 40% longer than DEEC and shows the no of packets transmission increases as compare to DEEC.
Keywords: Wireless Sensor Networks, Clustering Protocol, Energy Efficiency, Cluster-Head Selection, Network lifetime.

Download PDF

The post E0244101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).

E0243101511

IJSCE Journal — Sat, 02 Oct 2021 04:20:01 +0000

Design of Open Core Protocol
NayabRasool Shaik¹, Srikanth Pothula²
¹Nayab Rasool Shaik, Electronics and Communication Engg, Jntuk, Pdah College, Vishakapatnam, India.
²Srikanth Pothula, Electronics and Communication Engg, Jntuk, Pdah College, Vishakapatnam, India.
Manuscript received on October 13, 2011. | Revised Manuscript received on October 24, 2011. | Manuscript published on November 05, 2011. | PP: 357-361 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0243101511/2011©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: As more and more IP cores are integrated into an SOC design, the communication flow between IP cores has increased drastically and the efficiency of the on-chip bus has become a dominant factor for the performance of a system. The on-chip bus design can be divided into two parts, namely the interface and the internal architecture of the bus. In this work we adopt the well-defined interface standard, the Open Core Protocol and focus on the design of the internal bus architecture. We develop an efficient bus architecture to support most advanced bus functionalities defined in open core protocol , including burst transactions, lock transactions, pipelined transactions, and out-of-order transactions. We first model and design the on-chip bus with transaction level modeling for the consideration of design flexibility and fast simulation speed. We then implement the RTL models of the bus for synthesis and gate-level simulation. Experimental results show that the proposed TLM model is quite efficient for the whole system simulation and the real implementation can significantly save the communication time.
Keywords: AMBA,OCP.

Download PDF

The post E0243101511 appeared first on International Journal of Soft Computing and Engineering (IJSCE).