A Model-Driven Architecture Approach to the Efficient Identification of Services on Service-oriented Enterprise Architecture

Service-Oriented Enterprise Architecture requires the efficient development of loosely-coupled and interoperable sets of services. Existing design approaches do not always take full advantage of the value and importance of the engineering invested in existing legacy systems. This paper proposes an approach to define the key services from such legacy systems effectively. The approach focuses on identifying these services based on a Model-Driven Architecture approach supported by guidelines over a wide range of possible service types

Application of bagging, boosting and stacking to intrusion detection

This paper investigates the possibility of using ensemble algorithms to improve the performance of network intrusion detection systems. We use an ensemble of three different methods, bagging, boosting and stacking, in order to improve the accuracy and reduce the false positive rate. We use four different data mining algorithms, naïve bayes, J48 (decision tree), JRip (rule induction) and iBK( nearest neighbour), as base classifiers for those ensemble methods. Our experiment shows that the prototype which implements four base classifiers and three ensemble algorithms achieves an accuracy of more than 99% in detecting known intrusions, but failed to detect novel intrusions with the accuracy rates of around just 60%. The use of bagging, boosting and stacking is unable to significantly improve the accuracy. Stacking is the only method that was able to reduce the false positive rate by a significantly high amount (46.84%); unfortunately, this method has the longest execution time and so is insufficient to implement in the intrusion detection fiel

Reprogramming embedded systems at run-time

The dynamic re-programming of embedded systems is a long-standing problem in the field. With the advent of wireless sensor networks and the 'Internet of Things' it has now become necessary to be able to reprogram at run-time due to the difficulty of gaining access to such systems once deployed. The issues of power consumption, flexibility, and operating system protections are examined for a range of approaches, and a critical comparison is given. A combination of approaches is recommended for the implementation of real-world systems and areas where further work is required are highlighted.Postprin

Student success on face-to-face instruction and MOOCs : what can learning analytics uncover?

There are fundamental differences between the face-to-faceinstruction model and that of Massive Open Online Courses.This paper hypothesises that despite these fundamental dif-ferences, the success factors in these learning contexts arecomparable. The factors contributing to student successmight be related to the same basic principles, even if mani-festing themselves differently in each context - especially asthe very definition of success is closely dependent on whatcan be measured. Learning analytics can help to uncover theindicators which have the potential for identifying studentsat-risk and for institutions to exercise a timely intervention.Publisher PDFPeer reviewe

Survey of existing fingerprint countermeasures

A number of fingerprint countermeasures have claimed that their countermeasures can prevent the user away from fingerprint tracking. The research attempts to prove their claims and requires to study the effectiveness of their fingerprint prevention and observe the results of side effects after defence in order to assist the attentive user to know the limitation of current approaches. Under investigation, all countermeasures will be installed on the web browser and visit the developed hybrid fingerprint website in order to know the efficiency of the fingerprint resistance of all types. The research shows that all fingerprint countermeasures nowadays are unable to obstruct all kinds of the fingerprint tracking and countermeasures that use the blocking technique appear more side effects to the web browser than other techniques. Also, the increasing number of fingerprint attributes are increasing cause of unusual combination inside the Internet browser

Load Index Metrics for an Optimized Management of Web Services: A Systematic Evaluation

The lack of precision to predict service performance through load indices may lead to wrong decisions regarding the use of web services, compromising service performance and raising platform cost unnecessarily. This paper presents experimental studies to qualify the behaviour of load indices in the web service context. The experiments consider three services that generate controlled and significant server demands, four levels of workload for each service and six distinct execution scenarios. The evaluation considers three relevant perspectives: the capability for representing recent workloads, the capability for predicting near-future performance and finally stability. Eight different load indices were analysed, including the JMX Average Time index (proposed in this paper) specifically designed to address the limitations of the other indices. A systematic approach is applied to evaluate the different load indices, considering a multiple linear regression model based on the stepwise-AIC method. The results show that the load indices studied represent the workload to some extent; however, in contrast to expectations, most of them do not exhibit a coherent correlation with service performance and this can result in stability problems. The JMX Average Time index is an exception, showing a stable behaviour which is tightly-coupled to the service runtime for all executions. Load indices are used to predict the service runtime and therefore their inappropriate use can lead to decisions that will impact negatively on both service performance and execution cost

Jerrymouse: A Tool for a Flexible and Dynamic Distribution of Web Service Requests

This paper presents a novel architecture for distributing web service requests on clusters of servers. The architecture facilitates a transparent dynamic distribution of requests according to a range of specified policies. This enables a flexible performance in respect of different objectives, services and platforms (typically based on server workload). The architecture has been successfully demonstrated with a prototype implementation (called “Jerrymouse”). Our preliminary results with Jerrymouse indicate stable behaviour and worthwhile performance gains (compared with Apache HTTP Server). A specific policy to deliver reduced cluster electricity savings has also been successfully implemented