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The Internet of the future will be a nervous system for the entire economy, integrating dasiaopportunistic ecosystemspsila of single devices/departments/enterprises into a larger and more complex infrastructure which we refer to as dasiacyber-physical ecosystempsila (CPE). In the CPE, the individual properties or attributes of single entities will be dynamically combined to achieve an emergent desired behavior of the ecosystem. It is extremely hard - if not impossible - to control large scale CPE by building a global logic dasiatop-downpsila system able to rapidly adapt to changes by instructing each element what to do at each step. Using the latest knowledge of complexity science, we aim to develop a methodological framework for designing large scale CPE capable of generating resilient and scalable structure from the dasiabottom-uppsila by evolving self-organized basic architectural component dasiacells.psila These cells will be adaptively crafted through dynamic protocols enabling service composition into novel architectural components. The statistical properties displayed by the underlying network structure of the complex distributed system reveals the appropriate parameters on which efficient reliable operation depends. The parameters will be tuned using the dynamical network model of the CPE co-evolved with an dasiaeNetwork middlewarepsila embedded into the complex systempsilas fabric similar to how DNA molds the fundamental cells in natural systems such that they can evolve to accommodate gradual or abrupt change in the environment or internal operating conditions. Validation on the state-of-the-art testbed recently deployed in the Adaptive Risk Management Lab at UNB enable proof of concept opening the door to applications that will revolutionize several areas of crucial importance, including: blackout-free electricity generation and distribution, optimization of energy consumption, disaster response through deployment of holistic security ecosystems, pandemic- - mitigation, networked transportation and manufacturing, and environmental monitoring and sustainability assessment.
Date of Conference: 10-12 Dec. 2007