Cloud computing, autonomic computing, pervasive and mobile computing tends to converge, maximizing the benefits from different computing paradigms. This convergence makes emerging applications such as search and rescue applications, smart city and smart planet applications, e.g., to minimize the power consumption of a full city to achieve green computing vision, more promising on the one hand, but more complex to manage on the other hand. Interesting research questions arise due to this convergence. For example, how to efficiently retrieve underlying contexts that are difficult to recognize especially with resource-limited handheld devices, how to make use of these contexts for achieving self-management, and how to process large-scale contexts. These challenges require that researchers from software engineering, artificial intelligence, pattern recognition, high-performance distributed systems, cloud and mobile computing, etc. collaborate in order to make systems work in an efficiently self-managed manner.
Weishan Zhang, Klaus Marius Hansen, Paolo Bellavista (2013). A Research Roadmap for Context-Awareness-Based Self-managed Systems. Heidelberg : Springer [10.1007/978-3-642-37804-1_28].
A Research Roadmap for Context-Awareness-Based Self-managed Systems
BELLAVISTA, PAOLO
2013
Abstract
Cloud computing, autonomic computing, pervasive and mobile computing tends to converge, maximizing the benefits from different computing paradigms. This convergence makes emerging applications such as search and rescue applications, smart city and smart planet applications, e.g., to minimize the power consumption of a full city to achieve green computing vision, more promising on the one hand, but more complex to manage on the other hand. Interesting research questions arise due to this convergence. For example, how to efficiently retrieve underlying contexts that are difficult to recognize especially with resource-limited handheld devices, how to make use of these contexts for achieving self-management, and how to process large-scale contexts. These challenges require that researchers from software engineering, artificial intelligence, pattern recognition, high-performance distributed systems, cloud and mobile computing, etc. collaborate in order to make systems work in an efficiently self-managed manner.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.