Mobile Computing: A Disruptive Innovation Whose Time Has Come
The pervasive adoption of mobile computing devices, combined with cloud computing and the quantum gains in application software are creating a globally diverse collaborative platform. These elements taken together are deliver an exceptionally fast and pervasive level of disruptive innovation across all sociocultural and technology sectors (Bernoff, Li, 2008). The impact of this disruptive innovation is so significant that IT departments have to drastically reorder their policies in smartphones, tablet PCs and other devices that employees are using to streamline their lives (Thomson, 2012). Smartphones, tablet PCs and devices like them are becoming so pervasive today that they are considered a formable cultural and socioeconomic factor in the planning and execution of business and government strategies well into the future (Bernoff, Li, 2008).
This platform of technology is so pervasive, that it requires in-depth support to enable integration of systems to supporting data and network access to ensure the stability, security and reliability of performance. All of these factors are leading enterprises to create end-to-end platforms and technologies to enable the use of smartphones and tablet PCs' integration into the most complex workflows companies have (Saltzer, Reed, Clark, 1984). The large-scale investments by Google, Microsoft and others in the area of context-based computing and algorithm development, the continual investments in a technique called cyber-foraging, which is the ability to determine a person's location and interests based on the messaging provided by their smartphone or tablet PCs are nascent yet showing very significant potential (Gaddah, Kunz, 2003). In conjunction with these technologies is the continued reliance on Global Positioning Systems (GPS) to determine relative location of smartphones or tablet PCs and interlink them with local Web servers that have potentially relevant information (Satyanarayanan, 2001). Of the many technologies used for defining relative location of mobile devices to Web and cyber-foraging-based servers, the most reliable to date has been Radio Frequency Identification (RFID) (Welbourne, Balazinska, Borriello, Brunette, 2007). RFID has also emerged as the most reliable and secured technology to build middleware components of an enterprise-wide mobile platform on (Gaddah, Kunz, 2003). Middleware is software that unites the operating systems running the variety of diverse legacy and 3rd party systems enterprises rely on for successfully running their businesses on the one hand, and the application layer of the mobile software that users actually see on their systems. Based on the analysis completed for this study, middleware is a critical component for the overall performance of any mobile network.
In evaluating the role of mobility in general and specifically the technologies needed to enable it on a global scale, the need for capturing, interpreting and providing insights in real-time back to mobile devices is critical. One of the most successful approaches for accomplishing this has been developed by Nokia, which uses a cyber-foraging technology that defines relative location of a smartphone or mobile device, also capturing its characteristics and the interests of the owner (Gaddah, Kunz, 2003). Cyber-foraging seeks to capture, classify, aggregate response to and then selectively publish content of interest from localized servers back to a mobile device, all transparently and in real-time to the user. This study evaluates how much more effective users of mobile devices are when the have access to the data they need, both from a personal and professional standpoint (Bernoff, Li, 2008). There has been five years of analysis completed on how to use cyber-foraging to streamline complex selling and services tasks throughout enterprises using this technology (Emmerich, 2007). Middleware's role in the future of mobility enterprise application development and its pervasive adoption is well-documented and known, and will continue to accelerate given the interest in this area by venture capitalists globally (Blair, Coulson, Grace, 2004). This analysis evaluates the advances made in Cloud-based middleware development and its use in enterprise-wide and metro-based network architectures. The third factor this that of usability, an area that has continually be a weakness in the development of mobile-based operating systems and applications. Smaller and lower-resolution screens have made even the simplest applications difficult to use over time. There are significant implications for how the future of mobility will progress based on the development and fine-tuning of operating systems on the usability dimension. The adoption of devices based on operating system is also included in this analysis, as the impact of design and usability standards has an immediate impact on customer adoption and long-term usability. The operating systems including Apple iOS, Google Android and Microsoft Windows and others are included in the analysis. This study has determined that the greater the level of robustness in middleware the higher the level of cross-platform integration support and stability of legacy applications over time (Gaddah, Kunz, 2003). The last section of this analysis includes an assessment of the security aspects of mobility strategies and devices, including the potential of hackers to completely overtake a mobile device and capture al personal data on it. The impact of middleware on the security and stability of any mobility network is evident in how effective Apple has been in creating enterprise-level options for enterprise IT departments to immediately wipe the contents clean off of any iPhone or iPad that may have confidential data stored on it after it has been lost or stolen (Zhang, Gao, Jacobsen, 2005). This advanced level of functionality is attained through the use of middleware functions and support.
Analysis of Geolocation and Contextual Technologies
Geocaching, precise support for Global Positioning Systems and the pervasive use of Radio Frequency Identification (RFID) are all means that companies are using today to determine the relative location of their devices to geocaching and cyber-foraging servers, two components of mobility networks that deliver content based on user profiles. GPS systems have the ability to provide precise locations essential for cyber-foraging Web connections and the use of geocaching, yet lack signal integrity and strength for long-range updates of data and content. GPS systems are often configured with the lowest-end electronics as well to ensure a low cost-per-device is achieved, maximizing gross margins. There is also the binary nature of the data these systems deliver, often being constrained in terms of data traffic over congested networks. GPS doesn't scale well for the advanced geocaching and cyber-foraging nature of broader networks as a result.
RFID-based technologies when combined with their native ePC codes have the potential to deliver a much greater depth and breadth of information, creating a more effective user experience as a result. The RFID chipset's downward cost spiral has also made them more economically viable for mid-range smartphones and tablet PCs. The ePC command set, which is integral to the industrial uses of RFID, includes up to 32 different codes that can be used for better understanding the information and data needs of users. In pilots completed by Nokia and others using their cyber-foraging technologies, the ePC command set and mid-range RFID technologies have delivered scalable, secure results (Welbourne, Balazinska, Borriello, Brunette, 2007). RFID can also provide a stable enough signal for the more intricate data and information included in taxonomy entries on geocaching and cyber-foraging servers to be delivered over more congested networks. As a result, middleware researchers in the field of enterprise mobility have said that RFID is a preferred technology for metro and urban uses of geocaching and cyber-foraging (Zhang, Gao, Jacobsen, 2005).
An additional benefit of RFID is the ability to define relative location in context to geocaching and geo-locational parameters in cyber-foraging algorithms (Blair, Coulson, Grace, 2004). What this translates into is the ability to quickly determine location relative to the most relevant and highest-performing server, and then download updates to user taxonomies in real-time, completely unknown to the user. This transaction of data to the taxonomies is driven by the ePC command set on the smartphone or tablet PC, and also requires the opt-in or approval of the user to enable its accomplishment. Google, Nokia and other are also experimenting with Web Services patents originally obtained in 2003 that create a content-aware state engine that determines, through interpolation from surrounding caching servers, if the data on the smartphone or tablet PC needs updating or not, and then selects the highest-performing server to gain the necessary data from (Gaddah, Kunz, 2003). What has made the investments in Web Services architecture so significant is the accelerating nature it is having on the development of geocaching and cyber-foraging-based servers in pilots globally. These pilots include workflows for managing the more complex transaction-oriented systems including distributed and multichannel order capture and order management, order logistics planning and development, and the greater pricing management including optimization and pricing analysis (Medvidovic, 2002). Enterprises are seeing the potential to automate enterprise-wide networks of buyers, sellers, distributors and services organizations through the use of geocaching and cyber-foraging based approaches to selectively managing updates to mobile devices (Medvidovic, 2002).
What has Google so focused on these series of innovations and the emerging platform of technologies they represent is the ability to completely accelerate their advertising-based business model and also streamline content deliver.…