A Survey Paper on Implementing Service Oriented Architecture for Data Mining

Web service is working with the web with an object or component to achieve the communication between the distributed applications and between the different platforms through a series of protocols. Web Service provides a set of standard types systems, rules, techniques and internet service-oriented applications for communication between the different platforms, different programming languages and different types of systems to achieve interoperability. This survey paper gives the application of web service for data mining also we build a data mining model based on Web services and going forward it is possible to build a new data mining solution for security according to the prototype of a dynamic web service based data mining process system. DOI: 10.17762/ijritcc2321-8169.15079

Implementing Service Oriented Architecture for Data Mining

With Web technology, data on internet has become increasingly large and complex. No matter users or internet users needs all this data. Also the data which is available on web not all the time useful information or it is knowledgeable. Hence web data mining is necessary to fulfill this demand. Web data mining can extract unstructured, undiscovered data which is possibly useful information and knowledge, from much incomplete, noisy, ambiguous, random, practical application related data from WWW network. It is a new emerging commercial information/data mining technology. Its main characteristic is to extract key data to support business for decision making from business database through the use of extraction, conversion, analysis and other transaction models. Web service is deployed on the web with an object or component to achieve distributed application software platform through a series of protocols. Web Service platform provides a set of standard types systems, rules, techniques and internet service-oriented applications for communication between the different platforms, different programming languages and different types of systems to achieve interoperability. This paper gives the actual and practical application of web services for data mining, we build a data mining model based on Web services and going forward it is possible to implement the new data mining solution for security configuration. This has been achieved with the use of prototypes of a dynamic web service based data mining systems. DOI: 10.17762/ijritcc2321-8169.15079

Application-level differential checkpointing for HPC applications with dynamic datasets

High-performance computing (HPC) requires resilience techniques such as checkpointing in order to tolerate failures in supercomputers. As the number of nodes and memory in supercomputers keeps on increasing, the size of checkpoint data also increases dramatically, sometimes causing an I/O bottleneck. Differential checkpointing (dCP) aims to minimize the checkpointing overhead by only writing data differences. This is typically implemented at the memory page level, sometimes complemented with hashing algorithms. However, such a technique is unable to cope with dynamic-size datasets. In this work, we present a novel dCP implementation with a new file format that allows fragmentation of protected datasets in order to support dynamic sizes. We identify dirty data blocks using hash algorithms. In order to evaluate the dCP performance, we ported the HPC applications xPic, LULESH 2.0 and Heat2D and analyze them regarding their potential of reducing I/O with dCP and how this data reduction influences the checkpoint performance. In our experiments, we achieve reductions of up to 62% of the checkpoint time.This project has received funding from the European Unions Seventh Framework Programme (FP7/2007-2013) and the Horizon 2020 (H2020) funding framework under grant agreement no. H2020-FETHPC-754304 (DEEP-EST); and from the European Unions Horizon 2020 research and innovation programme under the LEGaTO Project (legato- project.eu), grant agreement No 780681.Peer ReviewedPostprint (author's final draft

Optimization of Web Services for Cloud Deployment and Mobile Consumption

Research performed for this thesis indicates an impedance mismatch between prevailing approaches to development of service-oriented enterprise applications and the consumption capabilities of mobile devices. The rich semantics and strong validation mechanisms inherent in SOAP-based web services, common to large-scale enterprise development, introduce inefficiencies of network bandwidth consumption and serialization/de-serialization processing requirements. These inefficiencies may be financially burdensome when systems are migrated to a cloud-based hosting environment and both costly and non-performant when accessed from network and processor constrained mobile devices. Yet wholesale abandonment of established enterprise practice and legacy systems for the adoption of unfamiliar architectural styles is rarely practical.  This thesis proposes a series of incremental changes to enterprise web services architecture that, individually, provide measurable efficiency benefits both when served from the cloud and when consumed from mobile devices. The objective of this research is to quantify the benefits and illustrate trade-offs for each. Within a cloud deployment, selective application of HTTP compression is shown to yield performance improvements in excess of 40% with data transfer  reductions of up to 85%. Analysis identifies the characteristics of services that suffer degraded performance under compression, and illustrates how similar performance and data reduction benefits may be achieved through service augmentation with alternative message and request formats.  Thesis focus then turns to options for improving efficiency in the consumption of these services from native applications on prevailing mobile device platforms. Development and measurements performed for this thesis identify approaches for faster and more efficient processing of existing services on mobile devices and relates these to the developer effort required. Further enhancements to application performance and development simplicity are demonstrated through mobile consumption of the augmented services and formats proposed for optimized cloud deployment. Research for this thesis suggests that in both cloud and mobile sides of a distributed system, performance and financial benefits may be achieved while building upon, rather than replacing, existing services code and architectural patterns.  M.S

Using cooperation to improve the experience of web services consumers

Web Services (WS) are one of the most promising approaches for building loosely coupled systems. However, due to the heterogeneous and dynamic nature of the WS environment, ensuring good QoS is still non-trivial. While WS tend to scale better than tightly coupled systems, they introduce a larger communication overhead and are more susceptible to server/resource latency. Traditionally this problem has been addressed by relying on negotiated Service Level Agreement to ensure the required QoS, or the development of elaborate compensation handlers to minimize the impact of undesirable latency. This research focuses on the use of cooperation between consumers and providers as an effective means of optimizing resource utilization and consumer experiences. It introduces a novel cooperative approach to implement the cooperation between consumers and providers

Enhanced SOAP Performance for low bandwidth environments

It is desirable that SOAP performs efficiently in environments where there are a large number of transactions. However, SOAP is based on XML and therefore inherits XML's disadvantage of having voluminous messages. Firstly, the performance of different SOAP bindings is investigated. A benchmark of different SOAP bindings in wireless environments demonstrates the unsuitability of HTTP and TCP bindings in limited bandwidth environments. UDP is recommended as an alternative transport protocol for SOAP. Secondly, the thesis examines the use of multicast in reducing the traffic caused by SOAP messages in low bandwidth environments to deal with challenges described. A novel SOAP-level multicast protocol based on the similarity of SOAP messages, called SMP (Similarity-based SOAP Multicast Protocol), is proposed. In particular, issues of traffic, network optimization, response time and scalability are investigated. Lastly, two extensions of SMP are proposed to further improve the performance of SMP. SMP's extensions are two algorithms, greedy and incremental tc-SMP, for traffic-constrained similarity-based SOAP multicast. Tc-SMP optimizes network traffic by building its own spanning trees instead of using the one built by traditional methods, such as Dijkstra's algorithm. A new client is added to a tc-SMP tree through an existing tc-SMP node that causes minimal additional traffic for that connection. Detailed analytical models and experimental evaluations of the proposed methods demonstrate that combining SOAP messages of similar content and multicasting them as aggregated messages can significantly lower total network traffic. These improvements are advantageous for Web service applications that involve a high number of simultaneous similar transactions such as stock quotes, weather and sport event reports