Performance modeling of the SPECjAppServer business case using LQN templates

Enterprise Java Beans (EJB) are one such tool that developers can choose to help them simplify the technical aspects, allowing them to focus more on the business requirements. However, as the enterprise solution is developed and constrained, there are several factors that need to be determined but are unknown at this early stage of development. Modeling these systems to predict the unknown is a possible solution that can save both time and money. However. as hardware and architectural aspects change over time, the model may need to change as well, which may be a very difficult task in the case of large systems. This paper presents the use of EJB templates of Layered Queueing Networks to handle the change for both the software and architecture of the SPECjAppServer Business Case. In this work, two LQN models have been developed and their results have been discussed.

Performance modeling of the SPECjAppServer business case using LQN templates

Enterprise Java Beans (EJB) are one such tool that developers can choose to help them simplify the technical aspects, allowing them to focus more on the business requirements. However, as the enterprise solution is developed and constrained, there are several factors that need to be determined but are unknown at this early stage of development. Modeling these systems to predict the unknown is a possible solution that can save both time and money. However. as hardware and architectural aspects change over time, the model may need to change as well, which may be a very difficult task in the case of large systems. This paper presents the use of EJB templates of Layered Queueing Networks to handle the change for both the software and architecture of the SPECjAppServer Business Case. In this work, two LQN models have been developed and their results have been discussed.

Correlation Transformational operators in Reactive Streams.

This paper describes two operators, autocorrelation and with transformational A.I for an event and sensor streams in reactive object-oriented programming.The use of stream-beans and event-beans with multi-sensor integration with application in robotics is illustrated, with use in SLAM and other semantic transfer functions with cloud integration.Keywords: Correlation operators, transformational A.I, Reactive Programming, Correlation operators, EJBs, automated persistence, RxJava, RxJS What: Reactive Programming provides for the application of operators through iterators and the observer pattern on streams. In a previous paper (Bheemaiah 2019) we have extended automated persistence of java beans as EJBs to reactive programming, with the addition of event-beans and stream-beans, we now extend the iterator methods on these beans with cross-correlation and auto-correlation functions.We illustrate this with SLAM algorithms with correlation transformational A.I. We extend the SLAM algorithms to auditory localization.How: We define a transformational A.I based system of correlation algorithms for application to stream beans and event beans.We define its functionality in SLAM and in audio stream based localization of audio sources, both with or without echos.Why:Simultaneous localization and mapping can be achieved through both visual and auditory mechanisms. Localization is traditionally implied to mean the localization in absolute or relative coordinates with the creation of mapping and the additional determination of the pose of a camera for sensory input or a similar auditory localization as a pose in the case of lidar or ultrasound or audible range sound. Localization of sound sources is an extension of correlation-based SLAM algorithms.

Enterprise Java Beans with ReactiveX.

This publication is on the automation of persistence, with the example of a Legacy solution, in the form of Enterprise Java Beans. While Java EE and EJB’s are depreciated. They are bridged to the present models of SaaS and serverless computing, through the introduction of two new stateful beans, StreamBean and EventBean, for functional, reactive and Cloud based automated persistence with the ability to implement any design pattern template with the Bean.This paper is on the transition from imperative programming in SQL to a NoSQL based serverless design with automation of the persistence layer in the cloud.

Technologies of Cross-Program Interfaces

Основное внимание в исследовании уделяется межпрограммным интерфейсам. Концепция управления бизнес-процессами (УБП) сильно продвинулась вперед. Это промежуточное программное обеспечение автоматизации работы бизнес-аналитиков и формализации процесса интеграции гетерогенных приложений в информационную инфраструктуру предприятия. Он акцентирован на основных задачах и не должен зависеть от используемой технологии - можно использовать CORBA, COM / DCOM, XML или Enterprise Java Beans для построения базы данных. Главные цели исследования - добиться уменьшения постоянной модернизации межпрограммных интерфейсов и уменьшения доли общего бюджета информационной системы. Наша качественная методология включает, во-первых, анализ научных статей, во-вторых, создание математической модели и, наконец, проведение экспериментов. Мы пришли к выводу, что развитая технология (межпрограммные интерфейсы) необходима для интеграции гетерогенных приложений на уровне бизнес-логики, что обеспечивает простой и гибкий способ интеграции приложений в единую программную среду.