{"title":"Implementation of IDEA, BATS, ARIMA and queuing model for task scheduling in cloud computing","authors":"M. B. Gawali, S. Shinde","doi":"10.1109/ECO-FRIENDLY.2016.7893233","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893233","url":null,"abstract":"In today's technological era, the cloud computing is the most popular because of its dynamic nature to provide the resources as per the user's need or request. The pay as per service pricing model add the strongest corner into the cloud computing. The services can be available and used anywhere, anytime makes the cloud computing more popular. But still the cloud computing has facing many issues. Task scheduling and resource allocation is one of them. Actually, these are separate issues which affected on this technology. The optimum scheduling of task with efficient allocation of resources have provide the maximum benefits to the cloud service provider in terms of QoS(Quality of Service). This is the preliminary experimental work to identify the less finish time require task completion algorithm out of, IDEA, BATS, ARIMA and Energy-saving based on queuing vacation. This paper has experimentally proves the BATS is better algorithm for task completion time with respect to the Berger Model input data.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116887375","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}
S. R. Balakrishnan, Shanmugam Veeramani, J. Leong, I. Murray, A. Sidhu
{"title":"High Performance Computing on the Cloud via HPC+Cloud software framework","authors":"S. R. Balakrishnan, Shanmugam Veeramani, J. Leong, I. Murray, A. Sidhu","doi":"10.1109/ECO-FRIENDLY.2016.7893240","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893240","url":null,"abstract":"There is an increased need for scalable high performance computing systems as the amount of generated data grows. Traditional High Performance Computing (HPC) clusters built to handle big data processing have inherent weaknesses that can be overcome by migrating to a more flexible cloud computing environment. This article discusses high performance computing and the paradigm shift from traditional onsite computing clusters to using the cloud for the same tasks. This article also proposes a solution called HPC+Cloud that enables enterprises to migrate to, and subsequently manage, high performance computing on the cloud. HPC+Cloud manages multiple, disparate, nodes on the hybrid cloud over software defined networks to complete tasks in a queue.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128122303","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}
{"title":"ANFIS based control strategy for frequency regulation in AC microgrid","authors":"Amandeep Singh, Sathans","doi":"10.1109/ECO-FRIENDLY.2016.7893238","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893238","url":null,"abstract":"Driven by the present day environmental concerns, distribution generation sources for electricity generation is increasing at a rapid pace. This makes a fundamental creation of microgrid as changing nature of distribution generation sources changes the quality of generated power. To avoid adverse effects of the unpredictable variations in RES many control concepts have been proposed in literature. This work considers autonomous mode of AC-microgrid. Under the effect of sudden changes in load and wind speed variation, the ANFIS scheduled PID controller is proposed and its comparative performance analysis is also shown. The simulations are carried out using MATLAB® the results of which show a ANFISPID controller behaves less oscillatory behavior.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133105331","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}
{"title":"Dynamic data leakage detection model based approach for MapReduce computational security in cloud","authors":"S. Chhabra, Ashutosh Kumar Singh","doi":"10.1109/ECO-FRIENDLY.2016.7893234","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893234","url":null,"abstract":"Cloud computing has become a popular buzzword and come out to be of great success in recent years with many advanced contributions. As cloud is storing an enormous amount of digital data engaged with third party services over the internet which raises new security concerns. Efforts are being made by researchers to make cloud secure and reliable computing environment. The technique used in this paper can be recognized as one of the leading methods to secure our sensitive data. The data we used is weather forecasting data which we have accumulated from the website of the government of India. Proposed methodology balances the load of whole data into chunks so that parallel processing will increase and execution time will decrease. Then the whole data are made to undergo map reduce by analysis of filtering and reducing the data with the help of a well known Hadoop framework. There are two main constituents of map reduce: Job follower and Task follower. These constituents will assign the tasks further to slave nodes. It reduces data storage size up to 70%. Reduced data will build more secure by using data leakage detection. Also, when any leakage of data comes to our concern identification of the guilty agent is performed. With the help of s-max algorithm we can conclude that it gives a significant improvement to find a guilty agent in probability with respect to > 0.4 of the reduced data. The level of security is computed or analyzed in the range of 0 to 1, with some probability criteria.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126007241","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}
{"title":"An end-to-end header compression for multihop IPv6 tunnels with varying bandwidth","authors":"D. Chauhan, Dr. Jay Kumar Jain, S. Sharma","doi":"10.1109/ECO-FRIENDLY.2016.7893247","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893247","url":null,"abstract":"With the exponential growth of internet it's impossible to sustain with IPv4 protocol due to its limited space capability and the only option is to move towards new next generation internet protocol IPv6. Different transition techniques have been proposed from the far to enable the smooth interoperation between the two protocols: Dual Stack, Tunneling, and Header Translation. Tunneling is the generally used solution to carry an IPv6 packet across the IPv4 network. Tunneling comes with several imperfections like inefficient routing, header overhead due to multiple headers present, Quality of service and high band width usage. These overheads could degrade the network performance especially over wireless links where there is scarcity of resources. In this paper we are addressing the header overhead issue in context of IPv6 tunnels, where the IPv6 header of 40 bytes is encapsulated inside an IPv4 header of length 20 bytes. This overhead would affect the network performance, especially over low bandwidth links, where resource is a constraint. So, it's better to compress this header and then send it over link and decompress it at the other end of the link. In this paper we have proposed a new approach to compress the IPv6 header of the packet, in context of IPv6 tunnels, which would improve the efficiency of IPv6 tunneling mechanism. Doing this we have compressed the 40 bytes of IPv6 header up to 6 bytes. We have applied this compression over multihop wired and wireless tunnels. Extensive amount of simulations are provided to compare the newly developed protocol with the standard tunneling technique. Results show that using this approach we are getting better network deliverables in terms of throughput, average end-to-end delay, Jitter, and Packet delivery ratio.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133751677","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}
Brijesh Bakariya, Kapil Chaturvedi, Krishna Pratap Singh, G. Thakur
{"title":"Efficient approach for mining top-k strong patterns in Social Network Service","authors":"Brijesh Bakariya, Kapil Chaturvedi, Krishna Pratap Singh, G. Thakur","doi":"10.1109/ECO-FRIENDLY.2016.7893251","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893251","url":null,"abstract":"Social Network Service is a one of the service where people may communicate with one another; and may also exchange messages even of any type of audio or video communication. Social Network Service as name suggests a type of network. Such type of web application plays a dominant role in internet technology. In such type of online community, people may share their common interest. Facebook LinkedIn, Orkut and many more are the Social Network Service and it is good medium of making link with people having unique or common interest and goals. But the problem of privacy protection is a big issue in today's world. As social networking sites allows anonymous users to share information of other stuffs. Due to which cyber crime is also increasing to a rapid extent. In this article, we have proposed an algorithm named MSPSN (Mining Strong Pattern from Social Network). In MSPSN, considering three parameters such as User (U), Time (T) and Image (I) from weblog of Social Network Services. This algorithm is very useful to identify user behaviour in social networking service environment. Most frequently used pattern can be identify using these parameters in Social Networking Services.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115016192","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}
{"title":"A Cooperative Additional Hybrid and Clipping technique for PAPR reduction in OFDM System","authors":"R. Saroj","doi":"10.1109/ECO-FRIENDLY.2016.7893241","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893241","url":null,"abstract":"OFDM is a multicarrier modulation technique used in the 4G wireless communication which provides numerous advantages such as High speed data transmission, high spectral efficiency, robustness to multipath fading etc. Despite of all these enormous advantages one of the major drawbacks associated with the OFDM system is the high Peak to Average Power ratio value. In this paper, we have proposed various algorithms such as Additional Hybrid technique, Alternate Additional Hybrid technique and Cooperative Additional Hybrid technique for finding the PAPR value in the OFDM system. After calculation of the PAPR values for the Alternate and Cooperative Additional Hybrid technique, we have applied the Clipping technique after IFFT in the Cooperative Additional Hybrid technique to suppress the excess peaks from the OFDM signal waveform thereby further reducing the PAPR value.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133125167","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}
{"title":"Scaling applications on cloud using GPGPU- trends and techniques","authors":"Ghanshyam Verma, Priyanka Tripathi","doi":"10.1109/ECO-FRIENDLY.2016.7893248","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893248","url":null,"abstract":"This survey presents an elaborative study of different GPU accelerated cloud frameworks. Although, a school of thought still advocated CPU over GPU computation stating limited on chip memory of GPU, several models have been proposed which have proved GPU can outperform CPU based systems if properly optimized. The authors have discussed the contexts which serve beneficial for such GPU based systems, and have presented examples through literature survey where GPU based computations have outperformed CPU despite limited on-chip memory. The discussion also includes application areas which can be enhanced using CPU-GPU hybrid system and remarks on how to achieve this.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115840081","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}
{"title":"Dynamic resource scaling in cloud using neural network and black hole algorithm","authors":"J. Kumar, Ashutosh Kumar Singh","doi":"10.1109/ECO-FRIENDLY.2016.7893243","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893243","url":null,"abstract":"Cloud computing has gained much attention in recent years. In spite of several advantages, cloud computing involves a number of issues such as dynamic resource scaling and power consumption. These factors lead a cloud system to be inefficient and costly. Workload prediction is one of the factors by which the efficiency of a cloud can be improved and operational cost would be reduced. In this paper, we present a workload prediction model using neural network and black hole algorithm. The experiments were performed on the benchmark data sets of HTTP traces from NASA, Calgary and Saskatchewan web servers. We achieved an improvement on mean squared error upto 134 times over back propagation.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126575585","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}
{"title":"Data preprocessing algorithm for Web Structure Mining","authors":"Suvarna Sharma, Amita Bhagat","doi":"10.1109/ECO-FRIENDLY.2016.7893249","DOIUrl":"https://doi.org/10.1109/ECO-FRIENDLY.2016.7893249","url":null,"abstract":"World Wide Web is an extremely large collection of information, i.e. beyond our imagination. It provides enough information according to user's need. Web is rising dreadfully as approximately 70 million pages are added daily. Knowledge Discovery on web data is referred as Web Mining. Web Structure Mining based on the analysis of patterns from hyperlink structure in the web. Like as Data Mining, Web Mining has four stages i.e. Data Collection, Preprocessing, Knowledge Discovery and Knowledge Analysis. This paper based on the first two stages Data collection and Preprocessing. Data collection is to collect the data required for analysis. Data preprocessing is considered as an important stage of Web Structure mining because of data available on web is unstructured, heterogeneous and noisy.","PeriodicalId":405434,"journal":{"name":"2016 Fifth International Conference on Eco-friendly Computing and Communication Systems (ICECCS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115106904","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}