Gomathy Nayagam M | Einstein College Of Engineering (original) (raw)
Papers by Gomathy Nayagam M
An application programming interface (API) specifies how some application components should inter... more An application programming interface (API) specifies how some application components should interact with each other. API can be used to ease the work of programming graphical user interface components. Social networking is web-based services that allow individuals to create a public profile, to create a list of users with whom to share connection, and view and cross the connections within the system. A social networking service is a platform to build social networks or social relations among people who, for example, share interests, activities, backgrounds or real-life connections and a variety of additional services. Most social network services are web-based and provide means for users to interact over the Internet, such as e-mail and messaging. They make it easier for people to find and communicate with individuals who are in their networks using the Web as the interface. In this paper, a Social Networking API may build applications that are available to the members of the socia...
Content Distribution Networks (CDNs) are overlay networks for placing the content near the end cl... more Content Distribution Networks (CDNs) are overlay networks for placing the content near the end clients with the aim at reducing the delay, network congestion and balancing the workload, hence improving the service quality perceived by the end clients. The main objective of this work is to construct a semantic overlay network of surrogate servers based on equitable dominating set. This yields any replication algorithm that can replicate the contents to minimum number of surrogate servers within the SON. Such servers can be accessed from anywhere. Then we propose a content distribution algorithm named Optimal Fast Replica (O-FR) and apply our proposed algorithm to distribute the content over the Equitable Dominating set based Semantic Overlay Networks (EDSON). We analyze the performance of our proposed Optimal Fast Replica (O-FR) in terms of average replication time, and maximum replication time and compare its performance with existing content distribution algorithms named Fast Repli...
Computer Communications, 2020
Abstract Object recognition is one of the research areas with good scope in most of the applicati... more Abstract Object recognition is one of the research areas with good scope in most of the applications. However, the object recognition on cloud stored data is very limited and the video based object recognition systems are minimal. Taking this into account, the videos are processed for recognizing the objects of interest by incorporating advanced image processing activities. The video frames are extracted from the videos for recognizing the objects. In order to recognize the objects, the objects have to be detected first. The objects are detected by means of SURF detector and the combination of local and global LDP features is extracted. Finally, the objects present in the videos are matched with the objects of interest. The performance of the proposed object recognition system for cloud video data is tested in three rounds. Initially, the proposed work is tested with different videos and then the proposed work is evaluated by varying the feature extractors such as Local Binary Pattern (LBP), Local LDP, Global LDP. Finally, the video processing time is calculated in terms of both CPU and GPU. All the performance evaluations are carried out in terms of accuracy, sensitivity, specificity and time consumption. The performance of the proposed approach is proven to be satisfactory.
Asian Journal of Research in Social Sciences and Humanities, 2016
Today, Computer Vision is one of the most well-liked and critical research areas in the Computer ... more Today, Computer Vision is one of the most well-liked and critical research areas in the Computer Science field. Moving object detection is the first and foremost step in any computer vision applications. The detection of moving object in any computer vision application is a very critical task. The most widely used method for moving object detection is Frame differencing based background subtraction method. The most of the researchers address the various challenges of background subtraction algorithm to detect the object accurately, the segmentation of objects from non stationary objects is critical, adaptation of illumination changes and handling of camouflage and etc. But they are more CPU and I/O intensive one. Cloud Computing is the new buzz word in computer field which provides computational power on demand basis which requires the representation of e-science workflow model for such kind of large-scale scientific applications. There are four different types of scientific work flow models viz Montage, LIGO, SIPHT, and Cybershake are exist which are varied by either CPU intensive or I/O intensive application. But the Temporal frame differencing based real time object detection is both CPU and I/O intensive one. Hence which could not be expresses as a single workflow model for cloud computing. So, we proposed a hybrid workflow model (Montage and SIPHT) of temporal frame differencing algorithm for real time object detection and the performance of such workflow model is tested and analyzed in already existing scheduling algorithm in workflowsim.
Scientific Programming
Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling i... more Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling is considered important to reduce the make span rate. In this paper, we developed a smart model approach for the best task schedule of Hybrid Moth Flame Optimization (HMFO) for cloud computing integrated in the IoHT environment over e-healthcare systems. The HMFO guarantees uniform resource assignment and enhanced quality of services (QoS). The model is trained with the Google cluster dataset such that it learns the instances of how a job is scheduled in cloud and the trained HMFO model is used to schedule the jobs in real time. The simulation is conducted on a CloudSim environment to test the scheduling efficacy of the model in hybrid cloud environment. The parameters used by this method for the performance assessment include the use of resources, response time, and energy utilization. In terms of response time, average run time, and lower costs, the hybrid HMFO approach has offered incr...
INTERNATIONAL JOURNAL OF RECENT TRENDS IN ENGINEERING & RESEARCH, 2019
Internet users spend an amount of time on videos and their needs have generated tremendous amount... more Internet users spend an amount of time on videos and their needs have generated tremendous amount of data .However ,too many videos are quite difficult for human beings to categorize and labelling it .As of today ,a significant human effort is needed to categorize these video data file that could substantially help the people to reduce the growing amount of clustering video data on Internet .The main objective of this project is to create a model to categorize and label the videos automatically with the help of SVM methods .As the result of this project we can able to classify the videos without any predefined class labels .We achieved classification accuracy of approximately 90 % on the test set which is a decent result considering the relative simplicity of the model. A proposed system is to identify the video belongs to which category using machine learning model. Our base idea is to collect the common features vectors from various videos dataset. Then we use Support Vector Machine algorithm to train our model to detect the video classification.
Multiple sequence alignment is the most common task in computational biology. This multiple seque... more Multiple sequence alignment is the most common task in computational biology. This multiple sequence alignment is computationally difficult and classified as a NP-Hard problem; so approximate algorithm(s) are generally required for most multiple alignment tasks. The Molecular Biologist may require the alignment of thousands of sequences that each can be of many hundreds of amino acids or even several millions of nucleotides. The approximation algorithm requires a long processing period of time to compute near optimal alignment. Thus, one step to reduce the processing time is to parallelize the algorithm. In order to have solution over parallelism method, we can either use expensive multiprocessor programming or cheaper cluster/Grid programming. Multiprocessor systems are specialized expensive hardware and are not commonly available. An alternative cheapest way is to use either a computer cluster or a Computing Grid. A cluster can be used for amino acid sequences and will be very slow for multiple sequence alignment of DNA molecule. So, the computing grid is the only cheapest alternative for performing multiple sequence alignment of DNA molecules. We have designed an efficient grid scheduler to perform the parallel tasks in grid that minimizes the communication cost and time complexity and also implemented parallel algorithm on computing grid. The experimental results show enhanced speedup.
Content Distribution Networks (CDNs) are overlay networks for placing the content near the end cl... more Content Distribution Networks (CDNs) are overlay networks for placing the content near the end clients with the aim at reducing the delay, network congestion and balancing the workload, hence improving the service quality perceived by the end clients. The main objective of this work is to construct a semantic overlay network of surrogate servers based on equitable dominating set. This yields any replication algorithm that can replicate the contents to minimum number of surrogate servers within the SON. Such servers can be accessed from anywhere. Then we propose a content distribution algorithm named Optimal Fast Replica (O-FR) and apply our proposed algorithm to distribute the content over the Equitable Dominating set based Semantic Overlay Networks (EDSON). We analyze the performance of our proposed Optimal Fast Replica (O-FR) in terms of average replication time, and maximum replication time and compare its performance with existing content distribution algorithms named Fast Replica and Resilient Fast Replica. The result of such approach improves the service quality perceived by the end clients. This paper also analyzes the use of equitable dominating set for the construction of semantic overlay networks and also investigates how it is useful for maintaining the uniform utilization of the surrogate servers.
Cloud computing is an extension of parallel computing, distributed computing and grid computing. ... more Cloud computing is an extension of parallel computing, distributed computing and grid computing. It provides secure, quick, convenient data storage and computing power with the help of internet. Cloud provides ondemand services based on user requirements. Whenever meet the different user with different QoS requirements scheduling the services is challenging one. Most of the existing papers for scheduling concentrate on cost or time or both. In this paper, the MQMCE schedule the services based on more than three QOS requirement such as time cost, reliability and availability. It evaluates performance for various test cases with different number of workflows and different set of QoS parameters for each workflow. The MQMCE results is the improved performance from the existing method such as reducing time effect, reducing cost effect as well as increase reliability and availability in a single objective manner.
Multiple sequence alignment is the most common task in computational biology. This multiple seque... more Multiple sequence alignment is the most common task in computational biology. This multiple sequence alignment is computationally difficult and classified as a NP-Hard problem; so approximate algorithm(s) are generally required for most multiple alignment tasks. The Molecular Biologist may require the alignment of thousands of sequences that each can be of many hundreds of amino acids or even several millions of nucleotides. The approximation algorithm requires a long processing period of time to compute near optimal alignment. Thus, one step to reduce the processing time is to parallelize the algorithm. In order to have solution over parallelism method, we can either use expensive multiprocessor programming or cheaper cluster/Grid programming. Multiprocessor systems are specialized expensive hardware and are not commonly available. An alternative cheapest way is to use either a computer cluster or a Computing Grid. A cluster can be used for amino acid sequences and will be very slow for multiple sequence alignment of DNA molecule. So, the computing grid is the only cheapest alternative for performing multiple sequence alignment of DNA molecules. We have designed an efficient grid scheduler to perform the parallel tasks in grid that minimizes the communication cost and time complexity and also implemented parallel algorithm on computing grid. The experimental results show enhanced speedup.
Content Distribution Networks (CDNs) are overlay networks for placing the content near the end cl... more Content Distribution Networks (CDNs) are overlay networks for placing the content near the end clients with the aim at reducing the delay, network congestion and balancing the workload, hence improving the service quality perceived by the end clients. The main objective of this work is to construct a semantic overlay network of surrogate servers based on equitable dominating set. This yields any replication algorithm that can replicate the contents to minimum number of surrogate servers within the SON. Such servers can be accessed from anywhere. Then we propose a content distribution algorithm named Optimal Fast Replica (O-FR) and apply our proposed algorithm to distribute the content over the Equitable Dominating set based Semantic Overlay Networks (EDSON). We analyze the performance of our proposed Optimal Fast Replica (O-FR) in terms of average replication time, and maximum replication time and compare its performance with existing content distribution algorithms named Fast Replica and Resilient Fast Replica. The result of such approach improves the service quality perceived by the end clients. This paper also analyzes the use of equitable dominating set for the construction of semantic overlay networks and also investigates how it is useful for maintaining the uniform utilization of the surrogate servers.
Cloud computing is an extension of parallel computing, distributed computing and grid computing. ... more Cloud computing is an extension of parallel computing, distributed computing and grid computing. It provides secure, quick, convenient data storage and computing power with the help of internet. Cloud provides on-demand services based on user requirements. Whenever meet the different user with different QoS requirements scheduling the services is challenging one. Most of the existing papers for scheduling concentrate on cost or time or both. In this paper, the MQMCE schedule the services based on more than three QOS requirement such as time cost, reliability and availability. It evaluates performance for various test cases with different number of workflows and different set of QoS parameters for each workflow. The MQMCE results is the improved performance from the existing method such as reducing time effect, reducing cost effect as well as increase reliability and availability in a single objective manner.
ABSTRACT Emerging e-scientific applications involve the production of large data set from simulat... more ABSTRACT Emerging e-scientific applications involve the production of large data set from simulation or from large-scale experiments, which requires high capacity resources such as supercomputers, high bandwidth networks and mass storage systems. This requires one new paradigm that addresses issues such as multi-domain applications, co-operations and co-ordination of resource owners and blurring of system boundaries. Grid computing is one such paradigm that proposes aggregating geo graphically distributed, heterogeneous computing,storage and network resources to provide unified, secure and pervasive access to their combined capabilities. A major issue in grid computing is to provide security because grid shares the resources in different location and different administrative domains which imply that there will be different management policies. This work looks in to a user can dynamically search through numerous data set and ability to transfer large sized data set between resources which can be done at run time and securely access the data through networks. The key idea is to develop a policy of strong authentication between users with digital certificate and provide users with restricted access control of available resources.
2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), 2014
ABSTRACT Cloud computing is a new infrastructure environment that delivers on the promise of supp... more ABSTRACT Cloud computing is a new infrastructure environment that delivers on the promise of supporting on-demand services in a flexible manner by scheduling bandwidth, storage and compute resources on the fly. Content delivery networks (CDN) based systems are considered as the potential solutions to deliver User-generated content (UGC). But none of the existing CDN based solutions can support all the required features in UGC delivery. In this paper we analyses the various mechanism for deploying video in geographically distributed cloud server and optimal utilization of bandwidth, storage and other computing resources. Optimal Deployment can be done by using Dominating Set Algorithm.
Multiple sequence alignment is the most common task in computational biology. This multiple seque... more Multiple sequence alignment is the most common task in computational biology. This multiple sequence alignment is computationally difficult and classified as a NP-Hard problem; so approximate algorithm(s) are generally required for most multiple alignment tasks. The Molecular Biologist may require the alignment of thousands of sequences that each can be of many hundreds of amino acids or even several millions of nucleotides. The approximation algorithm requires a long processing period of time to compute near optimal alignment. Thus, one step to reduce the processing time is to parallelize the algorithm. In order to have solution over parallelism method, we can either use expensive multiprocessor programming or cheaper cluster/Grid programming. Multiprocessor systems are specialized expensive hardware and are not commonly available. An alternative cheapest way is to use either a computer cluster or a Computing Grid. A cluster can be used for amino acid sequences and will be very slow for multiple sequence alignment of DNA molecule. So, the computing grid is the only cheapest alternative for performing multiple sequence alignment of DNA molecules. We have designed an efficient grid scheduler to perform the parallel tasks in grid that minimizes the communication cost and time complexity and also implemented parallel algorithm on computing grid. The experimental results show enhanced speedup.
An application programming interface (API) specifies how some application components should inter... more An application programming interface (API) specifies how some application components should interact with each other. API can be used to ease the work of programming graphical user interface components. Social networking is web-based services that allow individuals to create a public profile, to create a list of users with whom to share connection, and view and cross the connections within the system. A social networking service is a platform to build social networks or social relations among people who, for example, share interests, activities, backgrounds or real-life connections and a variety of additional services. Most social network services are web-based and provide means for users to interact over the Internet, such as e-mail and messaging. They make it easier for people to find and communicate with individuals who are in their networks using the Web as the interface. In this paper, a Social Networking API may build applications that are available to the members of the socia...
Content Distribution Networks (CDNs) are overlay networks for placing the content near the end cl... more Content Distribution Networks (CDNs) are overlay networks for placing the content near the end clients with the aim at reducing the delay, network congestion and balancing the workload, hence improving the service quality perceived by the end clients. The main objective of this work is to construct a semantic overlay network of surrogate servers based on equitable dominating set. This yields any replication algorithm that can replicate the contents to minimum number of surrogate servers within the SON. Such servers can be accessed from anywhere. Then we propose a content distribution algorithm named Optimal Fast Replica (O-FR) and apply our proposed algorithm to distribute the content over the Equitable Dominating set based Semantic Overlay Networks (EDSON). We analyze the performance of our proposed Optimal Fast Replica (O-FR) in terms of average replication time, and maximum replication time and compare its performance with existing content distribution algorithms named Fast Repli...
Computer Communications, 2020
Abstract Object recognition is one of the research areas with good scope in most of the applicati... more Abstract Object recognition is one of the research areas with good scope in most of the applications. However, the object recognition on cloud stored data is very limited and the video based object recognition systems are minimal. Taking this into account, the videos are processed for recognizing the objects of interest by incorporating advanced image processing activities. The video frames are extracted from the videos for recognizing the objects. In order to recognize the objects, the objects have to be detected first. The objects are detected by means of SURF detector and the combination of local and global LDP features is extracted. Finally, the objects present in the videos are matched with the objects of interest. The performance of the proposed object recognition system for cloud video data is tested in three rounds. Initially, the proposed work is tested with different videos and then the proposed work is evaluated by varying the feature extractors such as Local Binary Pattern (LBP), Local LDP, Global LDP. Finally, the video processing time is calculated in terms of both CPU and GPU. All the performance evaluations are carried out in terms of accuracy, sensitivity, specificity and time consumption. The performance of the proposed approach is proven to be satisfactory.
Asian Journal of Research in Social Sciences and Humanities, 2016
Today, Computer Vision is one of the most well-liked and critical research areas in the Computer ... more Today, Computer Vision is one of the most well-liked and critical research areas in the Computer Science field. Moving object detection is the first and foremost step in any computer vision applications. The detection of moving object in any computer vision application is a very critical task. The most widely used method for moving object detection is Frame differencing based background subtraction method. The most of the researchers address the various challenges of background subtraction algorithm to detect the object accurately, the segmentation of objects from non stationary objects is critical, adaptation of illumination changes and handling of camouflage and etc. But they are more CPU and I/O intensive one. Cloud Computing is the new buzz word in computer field which provides computational power on demand basis which requires the representation of e-science workflow model for such kind of large-scale scientific applications. There are four different types of scientific work flow models viz Montage, LIGO, SIPHT, and Cybershake are exist which are varied by either CPU intensive or I/O intensive application. But the Temporal frame differencing based real time object detection is both CPU and I/O intensive one. Hence which could not be expresses as a single workflow model for cloud computing. So, we proposed a hybrid workflow model (Montage and SIPHT) of temporal frame differencing algorithm for real time object detection and the performance of such workflow model is tested and analyzed in already existing scheduling algorithm in workflowsim.
Scientific Programming
Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling i... more Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling is considered important to reduce the make span rate. In this paper, we developed a smart model approach for the best task schedule of Hybrid Moth Flame Optimization (HMFO) for cloud computing integrated in the IoHT environment over e-healthcare systems. The HMFO guarantees uniform resource assignment and enhanced quality of services (QoS). The model is trained with the Google cluster dataset such that it learns the instances of how a job is scheduled in cloud and the trained HMFO model is used to schedule the jobs in real time. The simulation is conducted on a CloudSim environment to test the scheduling efficacy of the model in hybrid cloud environment. The parameters used by this method for the performance assessment include the use of resources, response time, and energy utilization. In terms of response time, average run time, and lower costs, the hybrid HMFO approach has offered incr...
INTERNATIONAL JOURNAL OF RECENT TRENDS IN ENGINEERING & RESEARCH, 2019
Internet users spend an amount of time on videos and their needs have generated tremendous amount... more Internet users spend an amount of time on videos and their needs have generated tremendous amount of data .However ,too many videos are quite difficult for human beings to categorize and labelling it .As of today ,a significant human effort is needed to categorize these video data file that could substantially help the people to reduce the growing amount of clustering video data on Internet .The main objective of this project is to create a model to categorize and label the videos automatically with the help of SVM methods .As the result of this project we can able to classify the videos without any predefined class labels .We achieved classification accuracy of approximately 90 % on the test set which is a decent result considering the relative simplicity of the model. A proposed system is to identify the video belongs to which category using machine learning model. Our base idea is to collect the common features vectors from various videos dataset. Then we use Support Vector Machine algorithm to train our model to detect the video classification.
Multiple sequence alignment is the most common task in computational biology. This multiple seque... more Multiple sequence alignment is the most common task in computational biology. This multiple sequence alignment is computationally difficult and classified as a NP-Hard problem; so approximate algorithm(s) are generally required for most multiple alignment tasks. The Molecular Biologist may require the alignment of thousands of sequences that each can be of many hundreds of amino acids or even several millions of nucleotides. The approximation algorithm requires a long processing period of time to compute near optimal alignment. Thus, one step to reduce the processing time is to parallelize the algorithm. In order to have solution over parallelism method, we can either use expensive multiprocessor programming or cheaper cluster/Grid programming. Multiprocessor systems are specialized expensive hardware and are not commonly available. An alternative cheapest way is to use either a computer cluster or a Computing Grid. A cluster can be used for amino acid sequences and will be very slow for multiple sequence alignment of DNA molecule. So, the computing grid is the only cheapest alternative for performing multiple sequence alignment of DNA molecules. We have designed an efficient grid scheduler to perform the parallel tasks in grid that minimizes the communication cost and time complexity and also implemented parallel algorithm on computing grid. The experimental results show enhanced speedup.
Content Distribution Networks (CDNs) are overlay networks for placing the content near the end cl... more Content Distribution Networks (CDNs) are overlay networks for placing the content near the end clients with the aim at reducing the delay, network congestion and balancing the workload, hence improving the service quality perceived by the end clients. The main objective of this work is to construct a semantic overlay network of surrogate servers based on equitable dominating set. This yields any replication algorithm that can replicate the contents to minimum number of surrogate servers within the SON. Such servers can be accessed from anywhere. Then we propose a content distribution algorithm named Optimal Fast Replica (O-FR) and apply our proposed algorithm to distribute the content over the Equitable Dominating set based Semantic Overlay Networks (EDSON). We analyze the performance of our proposed Optimal Fast Replica (O-FR) in terms of average replication time, and maximum replication time and compare its performance with existing content distribution algorithms named Fast Replica and Resilient Fast Replica. The result of such approach improves the service quality perceived by the end clients. This paper also analyzes the use of equitable dominating set for the construction of semantic overlay networks and also investigates how it is useful for maintaining the uniform utilization of the surrogate servers.
Cloud computing is an extension of parallel computing, distributed computing and grid computing. ... more Cloud computing is an extension of parallel computing, distributed computing and grid computing. It provides secure, quick, convenient data storage and computing power with the help of internet. Cloud provides ondemand services based on user requirements. Whenever meet the different user with different QoS requirements scheduling the services is challenging one. Most of the existing papers for scheduling concentrate on cost or time or both. In this paper, the MQMCE schedule the services based on more than three QOS requirement such as time cost, reliability and availability. It evaluates performance for various test cases with different number of workflows and different set of QoS parameters for each workflow. The MQMCE results is the improved performance from the existing method such as reducing time effect, reducing cost effect as well as increase reliability and availability in a single objective manner.
Multiple sequence alignment is the most common task in computational biology. This multiple seque... more Multiple sequence alignment is the most common task in computational biology. This multiple sequence alignment is computationally difficult and classified as a NP-Hard problem; so approximate algorithm(s) are generally required for most multiple alignment tasks. The Molecular Biologist may require the alignment of thousands of sequences that each can be of many hundreds of amino acids or even several millions of nucleotides. The approximation algorithm requires a long processing period of time to compute near optimal alignment. Thus, one step to reduce the processing time is to parallelize the algorithm. In order to have solution over parallelism method, we can either use expensive multiprocessor programming or cheaper cluster/Grid programming. Multiprocessor systems are specialized expensive hardware and are not commonly available. An alternative cheapest way is to use either a computer cluster or a Computing Grid. A cluster can be used for amino acid sequences and will be very slow for multiple sequence alignment of DNA molecule. So, the computing grid is the only cheapest alternative for performing multiple sequence alignment of DNA molecules. We have designed an efficient grid scheduler to perform the parallel tasks in grid that minimizes the communication cost and time complexity and also implemented parallel algorithm on computing grid. The experimental results show enhanced speedup.
Content Distribution Networks (CDNs) are overlay networks for placing the content near the end cl... more Content Distribution Networks (CDNs) are overlay networks for placing the content near the end clients with the aim at reducing the delay, network congestion and balancing the workload, hence improving the service quality perceived by the end clients. The main objective of this work is to construct a semantic overlay network of surrogate servers based on equitable dominating set. This yields any replication algorithm that can replicate the contents to minimum number of surrogate servers within the SON. Such servers can be accessed from anywhere. Then we propose a content distribution algorithm named Optimal Fast Replica (O-FR) and apply our proposed algorithm to distribute the content over the Equitable Dominating set based Semantic Overlay Networks (EDSON). We analyze the performance of our proposed Optimal Fast Replica (O-FR) in terms of average replication time, and maximum replication time and compare its performance with existing content distribution algorithms named Fast Replica and Resilient Fast Replica. The result of such approach improves the service quality perceived by the end clients. This paper also analyzes the use of equitable dominating set for the construction of semantic overlay networks and also investigates how it is useful for maintaining the uniform utilization of the surrogate servers.
Cloud computing is an extension of parallel computing, distributed computing and grid computing. ... more Cloud computing is an extension of parallel computing, distributed computing and grid computing. It provides secure, quick, convenient data storage and computing power with the help of internet. Cloud provides on-demand services based on user requirements. Whenever meet the different user with different QoS requirements scheduling the services is challenging one. Most of the existing papers for scheduling concentrate on cost or time or both. In this paper, the MQMCE schedule the services based on more than three QOS requirement such as time cost, reliability and availability. It evaluates performance for various test cases with different number of workflows and different set of QoS parameters for each workflow. The MQMCE results is the improved performance from the existing method such as reducing time effect, reducing cost effect as well as increase reliability and availability in a single objective manner.
ABSTRACT Emerging e-scientific applications involve the production of large data set from simulat... more ABSTRACT Emerging e-scientific applications involve the production of large data set from simulation or from large-scale experiments, which requires high capacity resources such as supercomputers, high bandwidth networks and mass storage systems. This requires one new paradigm that addresses issues such as multi-domain applications, co-operations and co-ordination of resource owners and blurring of system boundaries. Grid computing is one such paradigm that proposes aggregating geo graphically distributed, heterogeneous computing,storage and network resources to provide unified, secure and pervasive access to their combined capabilities. A major issue in grid computing is to provide security because grid shares the resources in different location and different administrative domains which imply that there will be different management policies. This work looks in to a user can dynamically search through numerous data set and ability to transfer large sized data set between resources which can be done at run time and securely access the data through networks. The key idea is to develop a policy of strong authentication between users with digital certificate and provide users with restricted access control of available resources.
2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), 2014
ABSTRACT Cloud computing is a new infrastructure environment that delivers on the promise of supp... more ABSTRACT Cloud computing is a new infrastructure environment that delivers on the promise of supporting on-demand services in a flexible manner by scheduling bandwidth, storage and compute resources on the fly. Content delivery networks (CDN) based systems are considered as the potential solutions to deliver User-generated content (UGC). But none of the existing CDN based solutions can support all the required features in UGC delivery. In this paper we analyses the various mechanism for deploying video in geographically distributed cloud server and optimal utilization of bandwidth, storage and other computing resources. Optimal Deployment can be done by using Dominating Set Algorithm.
Multiple sequence alignment is the most common task in computational biology. This multiple seque... more Multiple sequence alignment is the most common task in computational biology. This multiple sequence alignment is computationally difficult and classified as a NP-Hard problem; so approximate algorithm(s) are generally required for most multiple alignment tasks. The Molecular Biologist may require the alignment of thousands of sequences that each can be of many hundreds of amino acids or even several millions of nucleotides. The approximation algorithm requires a long processing period of time to compute near optimal alignment. Thus, one step to reduce the processing time is to parallelize the algorithm. In order to have solution over parallelism method, we can either use expensive multiprocessor programming or cheaper cluster/Grid programming. Multiprocessor systems are specialized expensive hardware and are not commonly available. An alternative cheapest way is to use either a computer cluster or a Computing Grid. A cluster can be used for amino acid sequences and will be very slow for multiple sequence alignment of DNA molecule. So, the computing grid is the only cheapest alternative for performing multiple sequence alignment of DNA molecules. We have designed an efficient grid scheduler to perform the parallel tasks in grid that minimizes the communication cost and time complexity and also implemented parallel algorithm on computing grid. The experimental results show enhanced speedup.