Cardei, Ionut E.

Designing and developing enterprise applications is a complex and resource intensive process, as it often must address thousands of requirements. At the same time, the software architecture of most enterprise applications at their core have many features and structures in common. Designers from different teams do not normally share design elements because of the competitive and proprietary nature of development, and enterprise applications design and development teams end up re-inventing the wheel when tackling a new product.
My objective is to formulate new design patterns for enterprise application architectures that assist software architects with reusable solutions to improve design quality and productivity. I achieve this by presenting seven patterns, each providing a solution to a specific challenge or a problem that is common to many enterprise applications.
The Business Object Pattern provides a generic approach to design extensible Business Objects and their frameworks for enterprise applications. The pattern covers a number of concepts, including the Dynamic business object, the Static business object, constraints for validity, editability, and attribute visibility, as well as the mechanisms for workflow.
The Business Object Life Cycle Pattern introduces the concept of stages which comprise a business object’s life cycle, and their relation to the business object’s integrity during that life cycle.
The Simple Change History Pattern provides a concept of enforcing record keeping of the owner and date of the last change performed on a given business data object. The Business Data Object Versioning Pattern offers a solution by introducing a new version of a given business data object which allows for preservation of the original data. The Change History Record Pattern defines a solution for cases when there is a need to capture detailed information about the changes performed on a given business object, such as who made the changes, when, and what changes were made.
The Permission Based Granular Access Control Pattern offers a basic approach for access control to objects and their attributes.
Finally, the Money Object Pattern offers a language neutral approach to internationalization and globalization of business applications which require multi-currency capability.
It is hoped that applying these patterns will provide many advantages, ranging from quicker delivery times to a more reliable software, and ultimately help achieve a systematic approach to designing and building complex enterprise applications.

Nowadays the widespread availability of wireless networks has created an interest
in using them for other purposes, such as localization of mobile devices in indoor
environments because of the lack of GPS signal reception indoors. Indoor localization
has received great interest recently for the many context-aware applications it could make possible. We designed and implemented an indoor localization platform for Wi-Fi nodes (such as smartphones and laptops) that identifies the building name, floor number, and room number where the user is located based on a Wi-Fi access point signal fingerprint pattern matching. We designed and evaluated a new machine learning algorithm, KRedpin, and developed a new web-services architecture for indoor localization based on J2EE technology with the Apache Tomcat web server for managing Wi-Fi signal data from the FAU WLAN. The prototype localization client application runs on Android cellphones and operates in the East Engineering building at FAU. More sophisticated classifiers have also been used to improve the localization accuracy using the Weka data mining tool.

To ensure that a system is robust and will continue operation even when facing
disruptive or traumatic events, we have created a methodology for system architects and
designers which may be used to locate risks and hazards in a design and enable the
development of more robust and resilient system architectures. It uncovers design
vulnerabilities by conducting a complete exploration of a systems’ component
operational state space by observing the system from multi-dimensional perspectives and
conducts a quantitative design space analysis by means of probabilistic risk assessment
using Bayesian Networks. Furthermore, we developed a tool which automated this
methodology and demonstrated its use in an assessment of the OCTT PHM communication system architecture. To boost the robustness of a wireless communication system and efficiently allocate bandwidth, manage throughput, and ensure quality of service on a wireless link, we created a wireless link management architecture which applies sensor fusion to gather and store platform networked sensor metrics, uses time series forecasting to predict the platform position, and manages data transmission for the links (class based, packet scheduling and capacity allocation). To validate our architecture, we developed a link management tool capable of forecasting the link quality and uses cross-layer scheduling and allocation to modify capacity allocation at the IP layer for various packet flows (HTTP, SSH, RTP) and prevent congestion and priority inversion. Wireless sensor networks (WSN) are vulnerable to a plethora of different fault types and external attacks after their deployment. To maintain trust in these systems and
increase WSN reliability in various scenarios, we developed a framework for node fault
detection and prediction in WSNs. Individual wireless sensor nodes sense characteristics
of an object or environment. After a smart device successfully connects to a WSN’s base
station, these sensed metrics are gathered, sent to and stored on the device from each
node in the network, in real time. The framework issues alerts identifying nodes which
are classified as faulty and when specific sensors exceed a percentage of a threshold
(normal range), it is capable of discerning between faulty sensor hardware and anomalous
sensed conditions. Furthermore we developed two proof of concept, prototype
applications based on this framework.