Abstract
Future-generations cyber-infrastructure must enable the dynamic coordinated composition of computing and information services. Resulting applications need to provide high-performance distributed computing to end users in a scalable, reliable and secure manner. This pervasive and ubiquitous grid computing infrastructure will view physical devices and computational agents uniformly, enabling radical improvement of existing applications, and opening the door for applications in entirely new domains. For example, wireless sensoractuator networks deployed in buildings and bridges can semi-automatically and cooperatively react to natural or man-made disasters in order to prevent human losses. Temperature, pressure, and stress-sensing devices can inform authorities about the probability of structural damage leading to collapse, can automatically activate fire extinguishing equipment, can help locate survivors and devise exit strategies, and can deviate traffic on emergency situations in semi-automated ways. Another example is virtual surgical planning, in which a surgeon simulates several surgery plans on a detailed computational model of a patient’s body. The surgeon can interactively analyze the effect of different plans on the patient’s body fluid dynamics. Another example is a distributed camera network coordinated by a real-time data mining component for airport surveillance and security. Unusual irregular patterns of human behavior can be detected and communicated promptly to authorities. A final example is a manned and unmanned aerial vehicle network that can exchange sensed information and plans of action, and combine them with terrain and map databases for decentralized coordinated air traffic control. These applications will directly benefit from coordinated computational resources offered by the future pervasive grid. To realize this pervasive grid vision, it is imperative to develop programming technology and modular middleware to facilitate systems development on highly heterogeneous and dynamic cyber-infrastructure. In closed grid environments, a centralized coordination module often needs to reserve dedicated network and computing resources for specific tasks. Furthermore, users are often expected to manually allocate resources and install any needed software on target computing environments. In contrast, open dynamic grid environments require coordination and resource management protocols to be automated. Resources in open grid environments can be organized into peer-to-peer networks. These networks are scalable because information lives in individual nodes and communication is highly, if not completely, decentralized. In an envisioned grid computing scenario, a process or data item will be created by a human user in a single node. The process or data item will get replicated and propagated by middleware
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