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T1. Advanced Computation Models for Rule Based Networks T2. Resource Management on Clouds and Grids
DETAILS T1. Advanced Computation Models for Rule Based Networks This tutorial consists of 10 sections. The first section discusses complexity as a systemic feature and the ability of rule based systems thandle different attributes of complexity. Section 2 reviews several types of rule based systems in the context of systemic complexity, including systems with single, multiple and networked rule bases. Section 3 introduces advanced computation models for rule based networks such as Boolean matrices, binary relations, block schemes and topological expressions. Section 4 presents basic operations on nodes in rule based networks, including merging and splitting in horizontal, vertical and output context. Section 5 discusses structural properties of basic operations such as associativity of merging and variability of splitting in horizontal, vertical and output context. Section 6 describes advanced operations on nodes in rule based networks, including node transformation for input augmentation, output permutation and feedback equivalence, as well as node identification in horizontal, vertical and output merging. Section 7 shows the application of the theoretical results from Sections 3-6 in feedforward rule based networks with single or multiple levels and layers. Section 8 illustrates the application of the theoretical results from Sections 3-6 in feedback rule based networks with single or multiple local and global feedback. Section 9 evaluates rule based networks in the context of fuzzy logic by means of composition of hierarchical fuzzy systems, decomposition of standard fuzzy systems, indicators of model performance and applications for case studies. The last section highlights the theoretical significance, the application areas and the methodological impact of the presented computational models for rule based networks. More details about this tutorial can be found at: http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-15599-4
T2. Resource Management on Clouds and Grids Grids and more recently clouds are distributed system infrastructures that are rapidly gaining popularity among researchers and users. Grids are used typically for resource sharing in a virtual organization comprising various partner institutions that run scientific/engineering applications. By providing the ability tacquire resources on demand ta variety of different users ranging from enterprises tacademic institutions the cloud has started receiving a great deal of attention. A cloud is characterized by elasticity that allows a dynamic change in the number of resources based on the varying demand from a customer as well as a pay-as-you-gopportunity, both of which can lead ta substantial savings for the system users. Appropriate management of resources by the middleware used in clouds and grids is crucial for effectively harnessing the power of the underlying distributed resource infrastructure. The problems range from handling resource heterogeneity, allocating resources tuser requests efficiently as well as effectively scheduling the requests that are mapped ta given resource, as well as handling uncertainties associated with the workload and the system. This three hour tutorial will address a number of important issues in the context of resource management. Examples from existing systems will be used tcomplement the discussion of algorithms and techniques. Although most of the time will be directed towards resource management issues in the context of clouds application of resource management techniques tgrids will alsbe included. This tutorial is directed at attendees with some knowledge of distributed processing – introductory knowledge of clouds and grids is desirable but not essential. The topics addressed by the tutorial include:
Some of the topics in the proposed tutorial will be based on material presented in a professional faculty development course and on material used in the lecture notes for a graduate course taught by the tutorial presenter. |
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