Enterprise Systems Education: New Directions & Challenges for the Future

Enterprise systems design, implementation, and integration are focal points for business and information technology (IT). Businesses of all sizes are looking to information technology to better integrate with business partners, reduce costs, and provide strategic advantage. These challenges require a new type of technical professional, one with the training and perspective of an enterprise architect with general technical expertise as well as business strategy and planning skills. This paper investigates the need for this new type of IT professional and the implications for higher education

Management of future data networks.

Data network complexity will increase dramatically over the next 5 years. Ad-hoc, active and parasitic paradigms will all make the already onerous task of network management increasingly problematic. An algorithm for managing data networks based on bacterial colony behaviour is discussed, offering automated management of essential tasks such as software distribution, load balancing, and quality of service. The algorithm is tested by using a log of real network requests to generate simulated network load. It is concluded that applying adaptive management could be the ideal approach to managing the behaviour of data networks of the futur

Management of Future Data Networks: An Approach Based on Bacterial Colony Behavior.

Network complexity will increase dramatically over the next 5 years as will the amount of devices inhabiting these networks. Ad-hoc and active paradigms will make the already onerous task of network management increasingly problematic. An approach to managing such networks based on bacterial colony behaviour is discussed, offering innate abilities for essential tasks such as software proliferation, load balancing and differing but distinct qualities of service. Robustness to realistic request streams is also demonstrated using real world requests as a source of simulated network load. The ‘hands off ’ element of the adaptive algorithm is a major asset for any configuration and optimisation task. This biologically inspired adaptive management solution could be the ideal approach to managing the behaviour of complex data networks of the future. Index Terms