2. Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/7
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Item Quality driven web service selection and ranking(2008) D'Mello, D.A.; Ananthanarayana, V.S.The increasing number of Web service providers with numerous functionally similar or same Web services produced a new problem of choosing a suitable Web service for the requester based on his expectations. The Quality of Service (QoS) can be used to select and rank functionally similar Web services. In this paper we define four Web service provider qualities to distinguish functionally similar and qualitatively competitive Web services. The main objective of this paper is to explore the mechanism which breaks the tie that may arise among functionally similar and qualitatively equivalent (competitive) Web services during Web service selection and ranking. � 2008 IEEE.Item Prefix-Suffix trees: A novel scheme for compact representation of large datasets(2007) Pai, R.M.; Ananthanarayana, V.S.An important goal in data mining is to generate an abstraction of the data. Such an abstraction helps in reducing the time and space requirements of the overall decision making process. It is also important that the abstraction be generated from the data in small number of scans. In this paper we propose a novel scheme called Prefix-Suffix trees for compact storage of patterns in data mining, which forms an abstraction of the patterns, and which is generated from the data in a single scan. This abstraction takes less amount of space and hence forms a compact storage of patterns. Further, we propose a clustering algorithm based on this storage and prove experimentally that this type of storage reduces the space and time. This has been established by considering large data sets of handwritten numerals namely the OCR data, the MNIST data and the USPS data. The proposed algorithm is compared with other similar algorithms and the efficacy of our scheme is thus established. � Springer-Verlag Berlin Heidelberg 2007.Item Parallel method for discovering frequent itemsets using weighted tree approach(2009) Kumar, P.; Ananthanarayana, V.S.Every element of the transaction in a transaction database may contain the components such as item number, quantity, cost of the item bought and some other relevant information of the customer. Most of the association rules mining algorithms to discover frequent itemsets do not consider the components such as quantity, cost etc. In a large database it is possible that even if the itemset appears in a very few transactions, it may be purchased in a large quantity. Further, this may lead to very high profit. Therefore these components are the most important information and without which it may cause the lose of information. This motivated us to propose a parallel algorithm to discover all frequent itemsets based on the quantity of the item bought in a single scan of the database. This method achieves its efficiency by applying two new ideas. Firstly, transaction database is converted into an abstraction called Weighted Tree that prevents multiple scanning of the database during the mining phase. This data structure is replicated among the parallel nodes. Secondly, for each frequent item assigned to a parallel node, an item tree is constructed and frequent itemsets are mined from this tree based on weighted minimum support. � 2009 IEEE.Item NPRank: Nexus based Predicate Ranking of Linked Data(2019) Sakthi, Murugan, R.; Ananthanarayana, V.S.In the typical use case of browsing Linked Data in DBpedia, the user would find an average of 180 facts attached to each entity. These facts are ordered alphabetically based on predicates, but a logical ordering of these facts is a better option. In this article, we present a Nexus based predicate ranking of Linked Data facts named NPRank. The key idea of NPRank is, the importance of a predicate is directly proportional to its familiarity among its group called Nexus. NPRank is a language and endpoint independent model allowing seamless integration and querying of data from multiple endpoints. Nexus score generated to rank predicates also assists in fragmentation of large data and bring in more hidden data from the SPARQL endpoints. Our experiments, conducted with the ranking of the Linked Data facts, corresponding to most visited pages of Wikipedia; from 275 active SPARQL endpoints, achieves better performance than the state-of-the-art methods. � 2019 IEEE.Item Multi-level per node combiner (MLPNC) to minimize mapreduce job latency on virtualized environment(2018) Jeyaraj, R.; Ananthanarayana, V.S.Big data drove businesses and researches more data driven. Hadoop MapReduce is one of the cost-effective ways for processing huge amount of data and also offered as a service from cloud on cluster of Virtual Machines (VM). In Cloud Data Center (CDC), Hadoop VMs are co-located with other general purpose VMs across racks. Such a multi-tenancy leads to varying local network bandwidth availability for Hadoop VMs, which directly impacts MapReduce job latency. Because, shuffle phase in MapReduce execution sequence itself contributes 26%-70% of overall job latency due to large number of intermediate records. Therefore, Hadoop virtual cluster requires to ensure a maximum bandwidth to minimize job latency, but, it also increases the bandwidth usage cost. In this paper, we propose "Multi-Level Per Node Combiner" (MLPNC) that curtails the number of intermediate records in shuffle phase resulting to reduction in overall job latency. It also minimizes bandwidth usage cost as well. We evaluate MLPNC results on wordcount job against default combiner, and Per Node Combiner (PNC). We also discuss the results based on number of shuffled records, shuffle latency, average merge latency, average reduce latency, average reduce task start time, and overall job latency. Finally, we argue in favor of MLPNC as it achieves up to 33% reduction in number of intermediate records and up to 32% reduction in average job latency than PNC. � 2018 ACM.Item MapReduce scheduler to minimize the size of intermediate data in shuffle phase(2019) Jeyaraj, R.; Ananthanarayana, V.S.; Paul, A.Hadoop MapReduce is one of the cost-effective ways for processing huge data in this decade. Despite it is opensource, setting up Hadoop on-premise is not affordable for small-scale businesses and research entities. Therefore, consuming Hadoop MapReduce as a service from cloud is on increasing pace as it is scalable on-demand and based on pay-per-use model. In such multi-tenant environment, virtual bandwidth is an expensive commodity and co-located virtual machines race each other to make use of the bandwidth. A study shows that 26%-70% of MapReduce job latency is due to shuffle phase in MapReduce execution sequence. Primary expectation of a typical cloud user is to minimize the service usage cost. Allocating less bandwidth to the service costs less but increases job latency, consequently increases makespan. This trade-off is compromised by minimizing the amount of intermediate data generated in shuffle phase at application level. To achieve this, we proposed Time Sharing MapReduce Job Scheduler to minimize the amount of intermediate data; thus, service cost is cut down. As a by-product, MapReduce job latency and makespan also are improved. Result shows that our proposed model minimized the size of intermediate data upto 62.1%, when compared to the classical schedulers with combiners. � 2019 IEEE.Item Cloud based service registry for location based mobile web services system(2013) D'Souza, M.; Ananthanarayana, V.S.Location based services (LBS) are growing in popularity due to the growing number of smart-phone users. The architectural design of LBS systems plays a major role in delivering location based services in ubiquitous environments. Service oriented architecture (SOA) which uses services as its basic constructs is the latest trend in designing and developing loosely coupled distributed applications even in heterogeneous environments. Cloud computing is another latest area which provides highly reliable and scalable infrastructure environment for resource intensive applications. This paper gives an overview of SOA based LBS system and explains how to move service registry to the cloud to utilize the best of both SOA and Cloud infrastructure. � 2013 IEEE.Item EfficientTreeMiner: Mining frequent induced substructures from XML documents without candidate generation(2006) Santhi Thilagam, P.; Ananthanarayana, V.S.Tree structures are used extensively in domains such as XML databases, computational biology, pattern recognition, computer networks, web mining, multi-relational data mining and so on. In this paper, we present an EfficientTreeMiner, a computationally efficient algorithm that discovers all frequently occurring induced subtrees in a database of labeled rooted unordered trees. The proposed algorithm mines frequent subtrees without generating any candidate subtrees. Efficiency is achieved by compressing the large database into a condensed data structure, namely prefix string representation, which reduces space complexity and by adopting a Frequent Immediate Descendents method that avoids the costly generation of candidate sets. Experimental results show that our algorithm has less time complexity when compared to existing approaches and is also scalable for mining both long and short frequent subtrees. � 2006 IEEE.Item Efficient mining of frequent rooted continuous directed subgraphs(2006) Sreenivasa, G.J.; Ananthanarayana, V.S.Mining frequent rooted continuous directed (RCD) subgraphs is very useful in Web usage mining domain. We formulate the problem of mining RCD subgraphs in a database of rooted labeled continuous directed graphs. We propose a novel approach of merging like RCD subgraphs. This approach builds a Pattern Super Graph (PSG) structure. This PSG is a compact structure and ideal for extracting frequent patterns in the form of RCD subgraphs. The PSG based mine avoids costly, repeated database scans and there is no generation of candidates. Results obtained are appreciating the approach proposed. � 2006 IEEE.Item Effective web service discovery based on functional semantics(2009) D'Mello, D.A.; Ananthanarayana, V.S.Web service discovery is a mechanism which facilitates an access to the Web service descriptions. UDDI facilitates the discovery based on the service functionality through keyword and category matching. Such discovery techniques do not consider the semantics and user context as they are too syntactic in nature. In this paper, we propose a well formed functional semantics to describe an operation of a Web service. We design the extendible functional knowledge to map the requested or published operation descriptions into an abstract operation. The experimentation shows that, the proposed functional semantics based discovery mechanism has better performance in terms of precision and recall. � 2009 IEEE.