Unified Architecture: Review of Three Articles

Table of Contents

1. Introduction2

2. Development in the Unified Architecture3

3. Discussion…………………………………………………………………………………………………………………………………….4

3.1. Issues Associated to UA4

3.2. Benefits of UA 5

3.3. Future Direction…………………………………………………………………………………………………………………….6

4. Conclusion……………………………………………………………………………………………………………………………………6

5. References………………………………………………………………………………………………………………………………….6

1. Introduction:

Architecture frameworks help to create systems that are relevant to stakeholder’s concerns. Often, models and non-models are used. With changing needs of stakeholders, architecture frameworks evolve correspondingly. One of the evolved advanced models is the Unified Architecture. The Unified Architecture was released in 2008 (Hause, Bleakely, & Morkevicius, 2016). It is a multi-layered and independent service-oriented architecture. Unified Architecture is a system which is a medium of communication between various clients and services and different systems and devices. Moreover, this system supports robust and secure communication. The goal of Unified Architecture (UA) is to provide a mechanism that allows for integration of process control and system management, whereby ‘address space’ has been designed to achieve this goal of UA; Address space is a flexible, real time environment modelling concept (Hause, Bleakely, & Morkevicius, 2016). The Address space supports the intended integration by building a common discipline between knowledge base – semantics and representation base – vocabulary.

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The purpose of this report is to study and analyse three articles related to UA. This report analyses the findings of three studies that were conducted by, i.e. given by Jalali and Borujerdi (2011), Lehnhoff, Rohjans, Uslar and Mahnke (2012) and, Pelka and Hellbrück (2016) on the use of a Unified Architecture. Notably, these articles discuss the use of Universal Architecture to make medical engines (Jalali & Borujerdi, 2011) smart grids (Lehnhoff et al., 2012) and location providers (Pelka & Hellbrück, 2016) into much better and effective methods. To illustrate, Jalali and Borujerdi (2011) explain the need to use a unified architecture for a biomedical search engine which will include unified schemas for ontologies and annotated documents and includes the use of standard architecture for annotation and retrieval processes. On the other hand, Lehnhoff et al. (2012) discuss 10 drivers to create the new OPC Unified Architecture which include the end-life cycle, the need for internet-based communication, platform independence, and the use of common information model. Nonetheless, Pelka and Hellbrück (2016) discuss the challenges faced by the current location provider system and explain that a Unified Architecture system will improve the location provider system.

2. Development in the Unified Architecture:

To help researchers store and retrieve information easily, a model of the UA was proposed in the medical field (Jalali & Borujerdi, 2011), which can be used in other domains following the same concept. A unified schema for biomedical ontologies would use OWL-DL. OWL-DL is The Web Ontology Language that is expressive, traceable and widely-used; these features make it a better option than OWL-Full and OWL-Lite. OWL-Full is the most expressive but untraceable web ontology language and OWL-Lite-the least expressive (Jalali & Borujerdi, 2011). The most important part for an ontology search engine is the links created that relate different concepts together. The use of web ontology languages, such as OWL, provide user with the ability to perform inference over data. Likewise, OWL helps to facilitate resource sharing and processing as well as making it possible to exploit interference engines (Jalali & Borujerdi, 2011).

The unified schema for annotated documents contains a base document class that represent documents in bio-medical literature. These documents have zero to multiple keywords assigned for retrieval approach (Jalali & Borujerdi, 2011). Retrieval engine and annotations introduce an architecture based on object orientated principles for medical information retrieval. The idea of semantic information retrieval is to overlook and overcome the shortcomings of the keyword approach. Without semantic information retrieval, two documents that are entirely the same would be shown as irrelevant because of the difference in key words. The UA allows the texts to be annotated by different and multiple ontologies resulting in the combination of different statistical and semantic retrieval approaches with different similarity measures and ontologies, thereby giving rise to new retrieval methods. The search engine based and made upon the UA, uses different retrieval methods which range from semantic to retrieval approaches. A search engine was evaluated using OSHUMED and Medline tests. For the OSHUMED, test evaluation was conducted using trec-eval library developed and released by text retrieval conference; while for Medline, the evaluation was carried out through MeSh ontology in OWL. The results showed an increase in Medline test, as the concept-based research decreased to 5%, hybrid research increased to 13% and the pseudo feedback increased to 18%, as compared to OSHUMED test (Jalali & Borujerdi, 2011).

Furthermore, there are uses and evidences of need of UA in technology such as smart grids. To make future smart Grids more service orientated, to improve quality and maintenance, and to add new features, it is necessary to have service-oriented automation and control architecture. OPC UA was tested on the wind mills of Alpha Ventus by the Beckhoff Automation Company using an SDK by Unified Automation. OPC UA was chosen from this company because of its authentication mechanism and security model. It was noted that the risk of failures was minimized without installing any other software (Lehnhoff et al. 2012). Notably, OPC Universal Architecture sets multiple services in Service Orientated Architecture (SOA) for communication. This involves three steps as i.e. the information modelling capacities are described; the communication services are explained and lastly the standardizing information models are introduced (Lehnhoff et al. 2012).

Other than Service Orientated Architecture there are some processes like:

  • Information Modelling- Information Modelling allows the exchange of semantic information rather than just raw data.
  • Communication services- It supports the uprising communication technologies making use of technology mapping without changing information or style. This further extends to abstract services, technology mapping, information security, and standardized information models.
  • Smart grid data model mappings – OPC Universal Architecture holds a high potential to be the standardized infrastructure of communication. The different mappings of models to help OPC Universal Architecture include Common Information Model IEC 61970/61968 and IEC 61850 (Lehnhoff et al. 2012).

Moreover, UA can be used in location providing as well, because it plays a role in location systems. Localization is an aspect of medical, industrial and consumer fields. Location systems can be used, for example, to manage goods in a store. Localization has also been used in Robot localization, consumer applications, IEEE 802.11 positioning, and time-based systems and several others.

3. Discussion

3.1. Issues Associated to UA

The major issues regarding UA in smart grids include the high cost, the support of the system of only one function, complex set up planning, and frequent updates and maintenances (Lehnhoff et al., 2012). To overcome these challenges and for the application of Smart Grids in future an architecture that can support functional detachment of software, hardware, and communication and a flexible system is needed, much like the OPC UA. OPC Universal Architecture offers a high potential in the domain of Smart Grids. Different countries would prefer to use smart grids, some which took part in the experiments (Lehnhoff et al., 2012).

There are several challenges that take place in each level of the position provider (Pelka & Hellbrück, 2016). Positioning algorithm can be used to determine a position from measurements. Algorithm requires anchors and beacons which are a reference point for positioning algorithm and other methods. Positioning algorithm faces difficulty in the presence of obstacles which causes non-line of sight (NLOS) which influences the measurements. Another issue is scalability which is the coverage in an area and the number of objects. Furthermore, other issues include performance metrics and energy consumption. All the problems of the positioning layer are interlinked and cannot be looked as separately (Pelka & Hellbrück, 2016). The middle layer manages the positioning and to manage the positioning detection of available positioning service is required. Service discovery is a tough task which not only limits to location service but to other services like Bluetooth as well. The availability of several different positioning technologies is another complication. Moreover, no standard is present to exchange positioning information. The challenge with the application layer is that there is not any standard available that fits all needs. Cost, zero effort system, security, configuration, and privacy are other issues faced by the application layer (Pelka & Hellbrück, 2016).

One way to solve the challenges in the position provider is to use UA to combine the positioning layer and the middle layer also called the integration layer. This UA can be used in the future for location providing, investigating problems, to provide solutions and to provide service advertisements for multiple position providers in heterogeneous systems (Pelka & Hellbrück, 2016).

3.2. Benefits of UA:

Utilized in medical search engines, UA will produce a positive impact on the overall medical research. Setting UA in different search engines will also help the researchers to evaluate or reuse their peer’s works leading to the development of more accurate and powerful medical search engines. Moreover, medical resources in semantic web language will help agents and inference engines for processing these resources. UA can result in better researches and medical engines which can overall help in better outcomes of the researches being conducted (Jalali & Borujerdi, 2012)

3.3. Future Direction:

Lehnhoff et al. (2012) suggest that the further work should focus on increasing the flexibility of architecture. On the other hand, Pelka and Hellbrück (2016) suggest that the future work should emphasize on positioning and integration layer in domain of UA concerning positioning systems. Trulsson (2013) mentions that multithreading should be embedded in UA in future. Feng, Kumar, Recht and Ré, (2012) argue that highly advanced models like ‘simulation models’ should be integrated in UA in future. Furthermore, improving performance of UA should be a significant aspect of future work in the field. Likewise, Pelka and Hellbrück (2016) suggested that a new layer, i.e. ‘integration layer’ should be designed while amalgamating positioning layer and middle layer. From these suggestions, it is evident that the focus of future work should be to enhance the design and performance of UA, so that it can become more efficient.

4. Conclusion

The studies mentioned above shed light on the development in the field of UA, while discussing the challenges associated with it. Nonetheless, it is evident that UA is employed in several fields, and it has proven its significance in these fields. Companies have preferred the use of UA because of its advantages that include transaction between multiple corpuses (Jalali & Borujerdi, 2012) or multiple levels of a machine to minimize the challenges and issues present before this architecture (Pelka & Hellbrück, 2016). Likewise, the use of UA in wind mills helps to increase flexibility, provide error-free results without the need of any other software and creates a better outcome which was preferred by companies (Lehnhoff et al., 2012). Furthermore, the issues in each layer of the position provider system can be successfully resolved by using a UA, thereby leading to an efficient product.

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Feng, X., Kumar, A., Recht, B., & Ré, C. (2012, May). Towards a unified architecture for in-RDBMS analytics. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (pp. 325-336). ACM.

Greßmann, B., Klimek, H., & Turau, V. (2010, March). Towards ubiquitous indoor location-based services and indoor navigation. In Positioning Navigation and Communication (WPNC), 2010 7th Workshop on (pp. 107-112). IEEE.

Hause, M., Bleakely, G., & Morkevicius, A. (2016). Technology Update on the Unified Architecture Framework (UAF) (Master’s thesis, 26th Annual INCOSE International Symposium (IS 2016), 2016). Edinburg.

Jalali, V., & Borujerdi, M. R. M. (2011). A unified architecture for biomedical search engines based on semantic Web Technologies. Journal of medical systems35(2), 237-249.

Lehnhoff, S., Rohjans, S., Uslar, M., & Mahnke, W. (2012, June). OPC unified architecture: A service-oriented architecture for smart grids. In Proceedings of the First International Workshop on Software Engineering Challenges for the Smart Grid (pp. 1-7). IEEE Press.

Pelka, M., & Hellbrück, H. (2016). Survey of challenges and towards a unified architecture for location systems. Journal of Network and Computer Applications67, 75-85.

Trulsson, M. (2013). Investigation, Evaluation and Implementation of OPC Unified Architecture. Masters Thesis submitted to Department of Computer Sciences, Lund University. Retrieved March 16, 2018 from http://sam.cs.lth.se/ExjobGetFile?id=538

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