ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675754
Ajay Shankar Bidyarthy, R. Raman, Dilys Thomas
{"title":"A toolbox for fast and approximate solutions for large linear and semidefinite programs","authors":"Ajay Shankar Bidyarthy, R. Raman, Dilys Thomas","doi":"10.1145/2675744.2675754","DOIUrl":"https://doi.org/10.1145/2675744.2675754","url":null,"abstract":"The multiplicative weights update is an algorithmic design technique that, over the years, has been discovered independently by several groups of researchers in different contexts. The earliest known use of this technique is by Brown and vonNeumann for the computation of equilibrium strategies in zero-sum games. These ideas and variants thereof have found applications in solving games, linear and semidefinite programming, computational geometry, machine learning, auctions and mechanism design, as well as data privacy.\u0000 In this paper, we focus on the use of this technique for solving zero-sum games, and for solving linear and semidefinite programs. In particular, we present empirical results on the efficacy of this method to solve linear and semidefinite programs approximately.\u0000 Our results suggest that this could be the preferred method in scenarios where one is interested in obtaining reasonably good results very quickly, as well as in scenarios where the problem sizes are very large. Another advantage of this technique is that it is amenable to a parallel or distributed implementation unlike interior-point or simplex methods, and therefore could form a primitive in cluster computing, or in sensor networks.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131641873","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}
ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675761
Payal Khurana Batra, K. Kant
{"title":"Stable cluster head selection in LEACH protocol: a cross-layer approach","authors":"Payal Khurana Batra, K. Kant","doi":"10.1145/2675744.2675761","DOIUrl":"https://doi.org/10.1145/2675744.2675761","url":null,"abstract":"Optimal cluster head count plays a key role in determining the efficiency of a cluster based routing protocol. If the cluster head count will be more than the optimal value, aggregation advantage cannot be taken fully. If clusters are less, then there will be more aggregation load on the cluster head and communication load on the cluster members as they have to communicate with cluster head over long distances. LEACH (Low Energy Clustering Adaptive Hierarchy) protocol, a popular clustering protocol, suffers from the cluster head variability problem. In this paper, we propose an approach which uses cross layer information to overcome this problem. NS-2 simulations show that improved LEACH increased the network lifetime i.e FND (First Node Death) time by 22%, HNA (Half Nodes Alive) by 24% and LND (Last Node Death) time by 12% respectively.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114528288","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}
ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675758
S. Baskaran, Manoj M. Apte
{"title":"RAPIDCharts: a framework for charting dynamic data using XML","authors":"S. Baskaran, Manoj M. Apte","doi":"10.1145/2675744.2675758","DOIUrl":"https://doi.org/10.1145/2675744.2675758","url":null,"abstract":"Visualization of the raw data into meaningful information is necessary for the proper understanding of the concepts at hand. Many real life scenarios require visualization of data as a statistical chart. Creation of such charts with dynamic data brings in challenges like impact at different levels in the code, redundancy of the code and restarts of servers every time a new build is released. In this paper, we have studied the issues with the conventional way of development and proposed a framework for charts by giving specifications in a separate eXtensible Markup Language (XML) file called Single File Specification System (SFS) and automating the process of creation of the charts and tables. We present RAPIDCharts, a framework that will reduce the impact of change or addition of new charts, redundancy of code and server restarts using an external file where the specifications are mentioned.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127673505","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}
ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675763
Poonam Goyal, S. Kumari, Dhruv Kumar, S. Balasubramaniam, Navneet Goyal
{"title":"Parallelizing OPTICS for multicore systems","authors":"Poonam Goyal, S. Kumari, Dhruv Kumar, S. Balasubramaniam, Navneet Goyal","doi":"10.1145/2675744.2675763","DOIUrl":"https://doi.org/10.1145/2675744.2675763","url":null,"abstract":"Parallelizing algorithms to leverage multiple cores in a processor or multiple nodes in a cluster setup is the only way forward to handle ever-increasing volumes of data. OPTICS is a well-known density based clustering algorithm to identify arbitrary shaped clusters. Since, hierarchical cluster ordering of OPTICS is sensitive to the order in which data is processed, typically a priority queue is used to maintain the order. This sequential access order makes it difficult to parallelize OPTICS. Moreover, the execution time of OPTICS increases with increase in density of data. We propose a parallel version of OPTICS for shared memory multi-core systems using a master-slave pattern for parallelization. The master runs concurrently with the slaves and distributes data to the slaves. Each slave performs neighborhood queries for a subset of data. Our approach ensures that cluster ordering matches with that of the classical OPTICS. Our solution runs in a mostly data parallel mode yielding scalable performance. We also argue that our approach is well suited for dense datasets in particular.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122274201","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":"Architecture- and workload- aware heterogeneous algorithms for sparse matrix vector multiplication","authors":"Siva Rama Krishna Bharadwaj Indarapu, Manoj Kumar Maramreddy, Kishore Kothapalli","doi":"10.1145/2675744.2675749","DOIUrl":"https://doi.org/10.1145/2675744.2675749","url":null,"abstract":"Multiplying a sparse matrix with a vector, denoted spmv, is a fundamental operation in linear algebra with several applications. Hence, efficient and scalable implementation of spmv has been a topic of immense research. Recent efforts are aimed at implementations on GPUs, multicore architectures, and such emerging computational platforms. Owing to the highly irregular nature of spmv, it is observed that GPUs and CPUs can offer comparable performance.\u0000 In this paper, we propose three heterogeneous algorithms for spmv that simultaneously utilize both the CPU and the GPU. This is shown to lead to better resource utilization apart from performance gains. Our experiments of the work division schemes on standard datasets indicate that it is not in general possible to choose the most appropriate scheme given a matrix. We therefore consider a class of sparse matrices that exhibit a scale-free nature and identify a scheme that works well for such matrices. Finally, we use simple and effective mechanisms to determine the appropriate amount of work to be alloted to the CPU and the GPU.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130098908","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}
ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675746
Satyendr Singh, Tanveer J. Siddiqui, Sunil K. Sharma
{"title":"Naïve Bayes classifier for Hindi word sense disambiguation","authors":"Satyendr Singh, Tanveer J. Siddiqui, Sunil K. Sharma","doi":"10.1145/2675744.2675746","DOIUrl":"https://doi.org/10.1145/2675744.2675746","url":null,"abstract":"This paper investigates Naïve Bayes (NB) classifier for Hindi Word Sense Disambiguation (WSD) utilizing eleven features. The features used in the experiment includes local context, collocations, unordered list of words, nouns and vibhaktis. Evaluation is done on a manually created sense annotated Hindi corpus consisting of 60 polysemous Hindi nouns. A precision of 77.52% was observed, using unordered list of words in feature vector. We obtained maximum precision of 86.11% by utilizing nouns in feature vector after applying morphology. The experimental results demonstrates that by adding more rich features, WSD accuracy of NB classifier can be significantly improved over unordered list of words. We obtained precision of 56.49%, by utilizing vibhaktis in the feature vector.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123133411","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}
ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675750
Vivek Yadav, Chandrashekar Ramanathan
{"title":"Automated layout preservation in cross language translation of document: an integrated approach and implementation","authors":"Vivek Yadav, Chandrashekar Ramanathan","doi":"10.1145/2675744.2675750","DOIUrl":"https://doi.org/10.1145/2675744.2675750","url":null,"abstract":"Layout refers to format and placement of content in a document. Cross language document translation is a well known problem and is addressed widely. Such translations usually remain unsuccessful in preserving original format of document because of typographical differences across the script of different languages. To make translated document look aesthetically identical to the original document, preservation of layout is essential. In this paper, we propose an integrated approach to solve various problems that arise during the process of translation pertaining to the layout of document like content flow, table of content, maintaining relative position and aesthetics of content.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132575153","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}
ComputePub Date : 2014-10-09DOI: 10.1145/2675744.2675757
M. Azeem, Mohammed Sharfuddin, T. Ragunathan
{"title":"Support-based replication algorithm for cloud storage systems","authors":"M. Azeem, Mohammed Sharfuddin, T. Ragunathan","doi":"10.1145/2675744.2675757","DOIUrl":"https://doi.org/10.1145/2675744.2675757","url":null,"abstract":"Replication has been used in cloud storage systems as a way to increase data availability. Existing replication strategies proposed for cloud storage systems allow users to fix the replication factor to replicate data. The problem with this approach is that either the user under estimates or over estimates the replication factor due to which the performance of the cloud storage system is affected. In this paper, we have proposed support-based replication algorithm which decides the replication factor based on the popularity of the file and access frequency of the blocks contained in the file. We have also proposed efficient way of placing the replicas in the cloud storage systems in order to improve the performance. Our analysis on storage and average read access time indicates that the proposed replication algorithm requires less storage space and provides better average read access time in comparison with Hadoop distributed file system.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127547236","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}
ComputePub Date : 2013-08-22DOI: 10.1145/2522548.2523131
A. Asadullah, Nikita Jain, K. Kapoor, Hajar Falih
{"title":"A data-centric heuristic for Hadoop provisioning in the cloud","authors":"A. Asadullah, Nikita Jain, K. Kapoor, Hajar Falih","doi":"10.1145/2522548.2523131","DOIUrl":"https://doi.org/10.1145/2522548.2523131","url":null,"abstract":"Research agencies and organizations work on algorithms and techniques to reduce Operational and Capital Expenditure. They move to Cloud to transform the Capital Expenditure (Capex) to Operational Expenditure (Opex). They use cloud to crunch large amount of commercial and social data. This paper proposes a heuristic approach to reduce the operational cost of virtual machines (VMs) running Hadoop. The heuristic is simple and effective, it scales the number of Hadoop nodes based on the type and size of the job submitted. We validate our heuristic with Hadoop word-count example on different data samples. Our implementation is independent of the cloud provider. Hence, the heuristic is applicable to both private and public cloud.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122744534","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}
ComputePub Date : 2013-08-22DOI: 10.1145/2522548.2522599
Richa Garg, Ravi Sankar Veerubhotla, A. Saxena
{"title":"AtDRM: a DRM architecture with rights transfer and revocation capability","authors":"Richa Garg, Ravi Sankar Veerubhotla, A. Saxena","doi":"10.1145/2522548.2522599","DOIUrl":"https://doi.org/10.1145/2522548.2522599","url":null,"abstract":"This work presents a new Digital Rights Management (DRM) architecture to address rights transfer and revocation aspects of protected content using a threshold Attribute-Based Encryption scheme. We considered two scenarios for rights transfer, here. In first case, a legitimate user needs to consume the protected content on multiple devices, while in second case the user wants to transfer the rights on the content to another user. These scenarios are significant in today's context with the proliferation of smart gadgets and shared cloud services. The architecture is flexible, offers individual or group level access to the protected content and does not require any pre-binding of the devices for consumption. The design inherits this feature from ABE scheme itself and therefore, it is possible to enforce controlled access for individuals as well as groups. Simultaneously, the architecture presents an efficient revocation scheme that eliminates the need of issuing new keys to users or re-encrypting the existing content, either for rights transfer or access revocation. Further, no specific revocation list is to be maintained for revoked users.","PeriodicalId":435920,"journal":{"name":"Compute","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125438283","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}