To enhance the quality of vehicular communication, vehicular ad hoc network has to be improved to handle the traffic related issues and maintain privacy. In order to fulfill the same, many schemes have been proposed in last decade. The Identity based Batch verification(IBV) scheme is one such scheme, which makes VANET more secure and efficient. Maintaining privacy through anonymity and reduction of verification time of messages by verifying them in Batch, are the main objectives of this scheme. This paper highlights the security issues of the current IBV scheme and introduces the concept of the random change of Anonymous Identity with time as well as location, to prevent the security attack and to maintain the privacy. In this scheme, performances are evaluated in terms of delay and transmission overhead.
{"title":"Enhancing Identity Based Batch Verification Scheme for Security and Privacy in VANET","authors":"P. Mahapatra, A. Naveena","doi":"10.1109/IACC.2017.0088","DOIUrl":"https://doi.org/10.1109/IACC.2017.0088","url":null,"abstract":"To enhance the quality of vehicular communication, vehicular ad hoc network has to be improved to handle the traffic related issues and maintain privacy. In order to fulfill the same, many schemes have been proposed in last decade. The Identity based Batch verification(IBV) scheme is one such scheme, which makes VANET more secure and efficient. Maintaining privacy through anonymity and reduction of verification time of messages by verifying them in Batch, are the main objectives of this scheme. This paper highlights the security issues of the current IBV scheme and introduces the concept of the random change of Anonymous Identity with time as well as location, to prevent the security attack and to maintain the privacy. In this scheme, performances are evaluated in terms of delay and transmission overhead.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133475597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multiplication is an essential vital role in arithmetic operations. In fact, multiplication is allotted on operations like Multiply and Accumulate (MAC). The exaggerate form of Braun multiplier is the Baugh-Wooley multiplier. This work proposes the design of Low-power Baugh-Wooley Multiplier with CMOS full adder with different topologies like 10T, 14T, 17T as well as with CNTFET full adders using different topologies like 10T, 14T, 17T. All circuits are designed and simulated using HSPICE Tool.
{"title":"Design of Low Power Multiplier using CNTFET","authors":"Rajendra Prasad Somineni, S. Jaweed","doi":"10.1109/IACC.2017.0120","DOIUrl":"https://doi.org/10.1109/IACC.2017.0120","url":null,"abstract":"Multiplication is an essential vital role in arithmetic operations. In fact, multiplication is allotted on operations like Multiply and Accumulate (MAC). The exaggerate form of Braun multiplier is the Baugh-Wooley multiplier. This work proposes the design of Low-power Baugh-Wooley Multiplier with CMOS full adder with different topologies like 10T, 14T, 17T as well as with CNTFET full adders using different topologies like 10T, 14T, 17T. All circuits are designed and simulated using HSPICE Tool.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121804383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the users on the cloud network increase, the consumption of the Compute, Network and Storage resources also increases. This leads to increase in the cost of deployment, configuration and maintenance. Hence, the Capital Expenditure (CAPEX) of the organization providing the cloud network increases. Network Function Virtualization (NFV) is a technology which virtualizes network functionalities. This paper studies the influence of NFV on CAPEX of cloud based networks and compares it with traditional implementation (without NFV) of such networks. A prototype cloud network based on NFV implementation is developed and implemented. Based on the test cases developed on the prototype, CAPEX of the resources used for both NFV based and traditional implementations are studied and analyzed. RESTful web services are created for the users of the cloud network to orchestrate and manage the network on the cloud. The results accomplished show that NFV based implementation reduces the CAPEX, when compared with the traditional implementation. It is also observed that orchestration mechanism reduces complexity of management of cloud network. A use case with simple web server is developed to compare the performance of a system on Cloud with that of a physical system.
{"title":"Cost and Performance Analysis of Network Function Virtualization Based Cloud Systems","authors":"M. Ananth, Rinki Sharma","doi":"10.1109/IACC.2017.0029","DOIUrl":"https://doi.org/10.1109/IACC.2017.0029","url":null,"abstract":"As the users on the cloud network increase, the consumption of the Compute, Network and Storage resources also increases. This leads to increase in the cost of deployment, configuration and maintenance. Hence, the Capital Expenditure (CAPEX) of the organization providing the cloud network increases. Network Function Virtualization (NFV) is a technology which virtualizes network functionalities. This paper studies the influence of NFV on CAPEX of cloud based networks and compares it with traditional implementation (without NFV) of such networks. A prototype cloud network based on NFV implementation is developed and implemented. Based on the test cases developed on the prototype, CAPEX of the resources used for both NFV based and traditional implementations are studied and analyzed. RESTful web services are created for the users of the cloud network to orchestrate and manage the network on the cloud. The results accomplished show that NFV based implementation reduces the CAPEX, when compared with the traditional implementation. It is also observed that orchestration mechanism reduces complexity of management of cloud network. A use case with simple web server is developed to compare the performance of a system on Cloud with that of a physical system.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121038310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matrix multiplication is an operation used in many algorithms with a plethora of applications ranging from Image Processing, Signal Processing, to Artificial Neural Networks and Linear algebra. This work aims to showcase the effect of developing matrix multiplication strategies that are less time and processor intensive by effectively handling memory accesses. The paper also touches upon on the advantages of using OpenMP, a multiprocessing toolkit to show the effect of parallelizing matrix multiplication.
{"title":"Cache Friendly Strategies to Optimize Matrix Multiplication","authors":"M. Ananth, S. Vishwas, M. R. Anala","doi":"10.1109/IACC.2017.0020","DOIUrl":"https://doi.org/10.1109/IACC.2017.0020","url":null,"abstract":"Matrix multiplication is an operation used in many algorithms with a plethora of applications ranging from Image Processing, Signal Processing, to Artificial Neural Networks and Linear algebra. This work aims to showcase the effect of developing matrix multiplication strategies that are less time and processor intensive by effectively handling memory accesses. The paper also touches upon on the advantages of using OpenMP, a multiprocessing toolkit to show the effect of parallelizing matrix multiplication.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"588 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117071229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Sowmya, C. D. Naidu, Rajendra Prasad Somineni, D. R. Reddy
Water is a precious source vital for healthy living. Most of the infectious diseases are due to contaminated water which leads to millions of deaths every year. There is a need to establish Water quality monitoring system to verify whether the determined water quality is suitable for intended use. This paper presents the application of Wireless Sensor Network (WSN) technology for real time online Water quality monitoring. In this paper, the details of system design and implementation of WSN are presented. Wireless Sensor Network (WSN) for a water quality monitoring is composed of number of sensor nodes with networking capability which are deployed at different overhead tanks and water bodies in an area. Each sensor node consists of an Arduino microcontroller, Xbee module and water quality sensors, the sensor probes shall continuously measure the different water quality parameters like pH, Temperature, Conductivity. The parameters are measured in real time by the sensors and send the data to the data center. Solar panel is used to power the system for each node. Data collected from remote nodes are displayed in the user PC. This developed system will demonstrate online sensor data analysis and has the advantages of power optimization, portability and easy installation.
{"title":"Implementation of Wireless Sensor Network for Real Time Overhead Tank Water Quality Monitoring","authors":"C. Sowmya, C. D. Naidu, Rajendra Prasad Somineni, D. R. Reddy","doi":"10.1109/IACC.2017.0118","DOIUrl":"https://doi.org/10.1109/IACC.2017.0118","url":null,"abstract":"Water is a precious source vital for healthy living. Most of the infectious diseases are due to contaminated water which leads to millions of deaths every year. There is a need to establish Water quality monitoring system to verify whether the determined water quality is suitable for intended use. This paper presents the application of Wireless Sensor Network (WSN) technology for real time online Water quality monitoring. In this paper, the details of system design and implementation of WSN are presented. Wireless Sensor Network (WSN) for a water quality monitoring is composed of number of sensor nodes with networking capability which are deployed at different overhead tanks and water bodies in an area. Each sensor node consists of an Arduino microcontroller, Xbee module and water quality sensors, the sensor probes shall continuously measure the different water quality parameters like pH, Temperature, Conductivity. The parameters are measured in real time by the sensors and send the data to the data center. Solar panel is used to power the system for each node. Data collected from remote nodes are displayed in the user PC. This developed system will demonstrate online sensor data analysis and has the advantages of power optimization, portability and easy installation.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117111504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rain will be estimated with the formation of cloud consists of water droplets, at higher frequencies such as millimetre band, that experiences a signal degradation and signal reduction due to the cloud consists of water droplets. The atmospheric gases, clouds, rain, snow, fog, cloud droplets, noise, water vapour, hydrometers absorbs electromagnetic energy, which results in the signal degradation. Clouds in generally consists of water droplets of less than 0.10mm in diameter, whereas raindrops in generally consists of range from 0.10mm to 9.5mm in diameter. So all these effects were leads to degradation in the quality of transmissions and in increase in the error rate of digital transmissions. In general, the higher frequency leads to, the more a signal is susceptible to rain in the atmosphere. For the purpose of cloud impact effect evaluation, the cloud cover statistical data, for low level clouds were derived from the earth-satellite link observations. These Extracted statistical data were used to obtain the seasonal drastic fluctuations.
{"title":"Severe Cause of Cloud Attenuation and Rain Attenuation on Space Communication Link at Millimetre Band and Differentiation between Rain Attenuation and Cloud Attenuation","authors":"K. K. Srinivas, T. Ramana","doi":"10.1109/IACC.2017.0063","DOIUrl":"https://doi.org/10.1109/IACC.2017.0063","url":null,"abstract":"Rain will be estimated with the formation of cloud consists of water droplets, at higher frequencies such as millimetre band, that experiences a signal degradation and signal reduction due to the cloud consists of water droplets. The atmospheric gases, clouds, rain, snow, fog, cloud droplets, noise, water vapour, hydrometers absorbs electromagnetic energy, which results in the signal degradation. Clouds in generally consists of water droplets of less than 0.10mm in diameter, whereas raindrops in generally consists of range from 0.10mm to 9.5mm in diameter. So all these effects were leads to degradation in the quality of transmissions and in increase in the error rate of digital transmissions. In general, the higher frequency leads to, the more a signal is susceptible to rain in the atmosphere. For the purpose of cloud impact effect evaluation, the cloud cover statistical data, for low level clouds were derived from the earth-satellite link observations. These Extracted statistical data were used to obtain the seasonal drastic fluctuations.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116563405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Given an application of a spatial data set, we discover a set of co-location patterns using a GUI (Graphical User Interface) model in a less amount of time, as this application is implemented using a parallel approach-A Map-Reduce framework. This framework uses a grid based approach to find the neighboring paths using a Euclidean distance. The framework also uses a dynamic algorithm in finding the spatial objects and discovers co-location rules from them. Once co-location rules are identified, we give the input as a threshold value which is used to form clusters of similar behavior. If the threshold value is too low more clusters are formed, if it is too high less clusters are formed. The comparison of the results shows that the proposed system is computationally good and gives the co-location patterns in a less amount of time.
{"title":"A Map-Reduce Framework for Finding Clusters of Colocation Patterns - A Summary of Results","authors":"M. Sheshikala, D. Rao, R. Prakash","doi":"10.1109/IACC.2017.0039","DOIUrl":"https://doi.org/10.1109/IACC.2017.0039","url":null,"abstract":"Given an application of a spatial data set, we discover a set of co-location patterns using a GUI (Graphical User Interface) model in a less amount of time, as this application is implemented using a parallel approach-A Map-Reduce framework. This framework uses a grid based approach to find the neighboring paths using a Euclidean distance. The framework also uses a dynamic algorithm in finding the spatial objects and discovers co-location rules from them. Once co-location rules are identified, we give the input as a threshold value which is used to form clusters of similar behavior. If the threshold value is too low more clusters are formed, if it is too high less clusters are formed. The comparison of the results shows that the proposed system is computationally good and gives the co-location patterns in a less amount of time.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124196232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fractal Dimension was firstly introduced by Mandelbort [1]. Fractal Dimension describe about the shape and appearance of object, which have the property of self similarity. Fractal Dimension of several objects are calculated by using the concept of self similarity. Because Fractal objects are self similar to the original object and dimensions are little varies as per scale length. Our main purpose is to find smoothness and roughness of images and image analysis. Various methods were proposed to estimate the fractal dimension of Grey scale images. Some existing methods were described using Fractal Dimension methodology for finding the roughness and smoothness of images. So many experiments has been done by using existing methods of fractal dimension and found various results. In this report we have described some proposed approach for finding the fractal dimension of color images. We found out fractal dimension of both gray scale and color image using Differential Box Count (DBC) method, cell counting method and our proposed approach.
{"title":"New Approach for Estimating Fractal Dimension of Both Gary and Color Images","authors":"Abadhan Ranganath, J. Mishra","doi":"10.1109/IACC.2017.0142","DOIUrl":"https://doi.org/10.1109/IACC.2017.0142","url":null,"abstract":"Fractal Dimension was firstly introduced by Mandelbort [1]. Fractal Dimension describe about the shape and appearance of object, which have the property of self similarity. Fractal Dimension of several objects are calculated by using the concept of self similarity. Because Fractal objects are self similar to the original object and dimensions are little varies as per scale length. Our main purpose is to find smoothness and roughness of images and image analysis. Various methods were proposed to estimate the fractal dimension of Grey scale images. Some existing methods were described using Fractal Dimension methodology for finding the roughness and smoothness of images. So many experiments has been done by using existing methods of fractal dimension and found various results. In this report we have described some proposed approach for finding the fractal dimension of color images. We found out fractal dimension of both gray scale and color image using Differential Box Count (DBC) method, cell counting method and our proposed approach.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128932673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the performance of hard-decision and soft-data fusion schemes for a cooperative spectrum sensing (CSS) in noisy-Rayleigh faded channel. Hard-decision fusion operations on the local binary decisions and soft-data fusion operations on the energy values obtained from the different cognitive radio (CR) users are performed at fusion center (FC)and a final decision on the status of a primary user (PU) is made. More precisely, the performance of CSS with various hard-decision fusion schemes (OR-rule, AND-rule, and majority-rule) and soft-data fusion schemes (square law selection (SLS), maximal ratio combining (MRC), square law combining (SLC), and selection combining (SC)) is analyzed in this work. Towardsthat, novel and closed-form analytic expressions are derived for probability of detection under all soft schemes in Rayleigh fading channel. A comparative performance between hard-decision and soft-data fusion schemes has been illustrated for different network parameters: time-band width product, average sensingchannel signal-to-noise ratio (SNR), and detection threshold. The optimal detection thresholds for which minimum total error rate is obtained for both soft and hard schemes are also indicated.
{"title":"Analysis of Hard-Decision and Soft-Data Fusion Schemes for Cooperative Spectrum Sensing in Rayleigh Fading Channel","authors":"S. Nallagonda, Y. Kumar, P. Shilpa","doi":"10.1109/IACC.2017.0057","DOIUrl":"https://doi.org/10.1109/IACC.2017.0057","url":null,"abstract":"This paper investigates the performance of hard-decision and soft-data fusion schemes for a cooperative spectrum sensing (CSS) in noisy-Rayleigh faded channel. Hard-decision fusion operations on the local binary decisions and soft-data fusion operations on the energy values obtained from the different cognitive radio (CR) users are performed at fusion center (FC)and a final decision on the status of a primary user (PU) is made. More precisely, the performance of CSS with various hard-decision fusion schemes (OR-rule, AND-rule, and majority-rule) and soft-data fusion schemes (square law selection (SLS), maximal ratio combining (MRC), square law combining (SLC), and selection combining (SC)) is analyzed in this work. Towardsthat, novel and closed-form analytic expressions are derived for probability of detection under all soft schemes in Rayleigh fading channel. A comparative performance between hard-decision and soft-data fusion schemes has been illustrated for different network parameters: time-band width product, average sensingchannel signal-to-noise ratio (SNR), and detection threshold. The optimal detection thresholds for which minimum total error rate is obtained for both soft and hard schemes are also indicated.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130995488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ravichand Kancharla, Shanthi Karpurapu, Vadeghar Ramesh Kumar, G. P. Reddy
Fourier transformation infrared spectroscopy has been used widely for understanding the structure and organization of membranes. The data obtained from FTIR spectroscopy will be huge and preprocessing of the data is an essential step. For accomplishing this task, we need to depend on various software which are not open source. Also the data processing will be time consuming and rigorous. This paper discusses a novel approach for analysis of multiple FTIR spectra. This paper discusses our tool developed Using MATLAB Image processing tool box functions for analyzing the multiple FTIR spectroscopy's.
{"title":"A Novel Approach for Analysis of FTIR Membrane Spectroscopy","authors":"Ravichand Kancharla, Shanthi Karpurapu, Vadeghar Ramesh Kumar, G. P. Reddy","doi":"10.1109/IACC.2017.0151","DOIUrl":"https://doi.org/10.1109/IACC.2017.0151","url":null,"abstract":"Fourier transformation infrared spectroscopy has been used widely for understanding the structure and organization of membranes. The data obtained from FTIR spectroscopy will be huge and preprocessing of the data is an essential step. For accomplishing this task, we need to depend on various software which are not open source. Also the data processing will be time consuming and rigorous. This paper discusses a novel approach for analysis of multiple FTIR spectra. This paper discusses our tool developed Using MATLAB Image processing tool box functions for analyzing the multiple FTIR spectroscopy's.","PeriodicalId":248433,"journal":{"name":"2017 IEEE 7th International Advance Computing Conference (IACC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130644071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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