Information Architects (IAs) must consider the small memory size of the mobile phones and their inability to support large bandwidth connectivity rather than squeezing the original website to be rendered on mobile devices. At present software and hardware such as Java Micro Edition (J2ME), Bluetooth, Global Positioning System (GPS), Digital Cameras of more than 5 mega pixels size, and several others are well integrated into cell phones and such phones are economical, hence, they are well liked and well known to all. Such low cost and improved infrastructure aid in making the mobile phones well suited for developing mobile applications; business, communication or entertainment. Further the authors assert the main concerns for the development of mobile applications lies in poor connectivity and insufficient data storage facility of mobile phones as mobile phones have very poor processing capacity. The authors suggest that because of the above listed constraints data exchange, transformation and user interfacing becomes challenging in mobile phones. They enlist the basic requirements for developing mobile applications, which are developing lightweight application software, low cost, flexible and accessible Service-Oriented Architecture (SOA), well integrated and customized system to match services as required by user and smooth flow of data. Furthermore in order to realize these the authors propose a lightweight SOA for such mobile business applications, which involves transferring specific data as per users’ requirement using business process and data access statistics, performing pro-active loading of data from server as per users’ request, providing asynchronous exchange of data with back end system in offline mode to allow smooth functioning of applications and compressing the transference and storing of data using XML (Natchetoi, Kaufman & Shapiro, 2008, p 27).
The authors observe SOA requires standardized data flow and compression in XML formats enabling storage and processing at lower bandwidths. They recommend that lossy method of data compression is significant as the file size is small and do not alter the application functionality after careful consideration. However, as lossy form of compression requires truncation of data not needed by web service user, client, or data truncation not probable to be used by client, then it is not easy to determine what exact data can be truncated. The authors in their IA design advocate truncation of data never to be used by client, as that does not alter the data precision and ensures sameness of original message and smooth functioning of application functionality (Natchetoi, Kaufman & Shapiro, 2008, p 28).
The authors claim that for fast uploading of mosite IA needs to develop a generic solution allowing automatic filtering of the business objects for transference of respective data required by users to decrease chances of customization required for the respective use case (Natchetoi, Kaufman & Shapiro, 2008, p 28). The transference of only required data and truncation of other data could be established because of commonality of knowledge between systems (Natchetoi, Kaufman & Shapiro, 2008, p 29).
The authors maintain that in the lightweight IA or framework the business objects are serialized, compressed and transmitted to the client as Resource Description Framework (RDF) messages on demand. The exchange is asynchronous and can be done in offline mode as well. The authors also claim that for mobile environment asynchronous mode of communication is more congenial, as the server and client are loosely connected, and mobile devices use different network channels based on communication capabilities, as for example when a mobile device is near to a computer then Bluetooth is used for communication but when it is out of the Bluetooth range then General Packet Radio Service (GPRS) or EDGE technology is used for communication (Natchetoi, Kaufman & Shapiro, 2008, p 29).
In the authors opinion for optimum mobile communication in mobile environment IAs need to design a proactive data feeding mechanism based on the prediction of the existing data used and processed by the client to run the mobile applications smoothly. They ascertain that based on demand pattern of the business object probability distribution guidelines can be set automatically and analyzed by Data Connection Manager (CM) and analyzed and changed if the application is augmented (Natchetoi, Kaufman & Shapiro, 2008, p 31).
Business communication in mobile environment must ensure data security similar to those of desktop environment using the internet. In the IA proposed by the authors claim the security system supports data encryption using a combination of asymmetric and symmetric Primary Key Infrastructure (PKI) and have shorter public keys sizes but similar encryption strength. Moreover in the authors’ IA design data encryption feature is implemented as a replaceable module, substituted with another component (Natchetoi, Kaufman & Shapiro, 2008, pp. 30-31).
The authors conclude that the world of technology is speeding towards wireless network and their IA design for mobile environment allows sufficient exchange and security of business data by proactive feeding, compression of data into RDF files and incorporating an asynchronous offline exchange in the event of poor connectivity between user and client and lower processing capacities of mobile devices sans intensive Java coding (Natchetoi, Kaufman & Shapiro, 2008, p 32). The authors suggest following their lean framework of SOA novel mobile business applications can be incorporated for mobile devices.
Reference: -
Natchetoi, Y., Kaufman, V. & Shapiro, A. 2008, ‘Service-Oriented Architecture for Mobile Applications’, International Conference on Software Engineering Proceedings of the 1st international workshop on Software architectures and mobility, Association for Computing Machinery, NY, USA, 10 May 2008, Leipzig, Germany, Viewed 20 March 2009, <http://portal.acm.org/citation.cfm?id=1370896>
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