In this study, a SCORM-compliant ubiquitous learning grid was constructed by using the grid services technologies combined with CC/PP. The purpose was to let anyone to access any information at anyplace, anytime, with any device to learn. Several SCORM-compliant learning management systems collaborated by Globus Toolkit V3.2 grid engine and CC/PP were implemented to provide a content adaptive environment. In the experiment, English learning objects were produced with access to learn and made accessible using PC, Laptop, Tablet PC, PDA, and mobile phones. Results of this study demonstrate the feasibility of the proposed framework.

This investigation proposed a workflow framework for composing pervasive learning objects. The grid services flow language was adopted to describe the workflow for composing pervasive learning objects distributed in heterogeneous environments. The framework was applied to the pervasive learning grid to enable effective collaboration and reuse of the learning objects. Experimental results showed that different LO services not only interacted themselves, but the service lifecycle was also good.

To solve the load imbalance problem of a solution-adaptive finite element application program on a distributed memory multicomputer, nodes of a refined finite element graph can be remapped to processors or load of a refined finite element graph can be redistributed based on the current load of each processor. For the former case, remapping can be performed by some fast mapping algorithms. For the latter case, a load-balancing algorithm can be applied to balance the computational load of each processor. In this paper, three tree-based parallel load-balancing methods, the MCSTLB method, the BTLB method, and the CBTLB method, were proposed to deal with the load imbalance problems of solution-adaptive finite element application programs. To evaluate the performance of the proposed methods, we have implemented those methods along with three mapping methods, the AE/ORB method, the AE/MC method, and the MLkP method, on an SP2 parallel machine. Three criteria, the execution time of mapping/load-balancing methods, the execution time of a solution-adaptive finite element application program under different mapping/load-balancing methods, and the speedups achieved by mapping/load-balancing methods for a solution-adaptive finite element application program, are used for the performance evaluation. The experimental results show that 1) if the initial mapping is performed by a mapping method and the same mapping method and load-balancing methods were used in each refinement to balance the load of processors, the execution time of an application program under a load-balancing method is always shorter than that of the mapping method, and 2) the execution time of an application program under the CBTLB method is shorter than that of the BTLB method and the MCSTLB method.

In this paper, we propose a prefix code matching parallel load-balancing method (PCMPLB) to efficiently deal with the load unbalancing problems of solution-adaptive finite element application programs on distributed memory multicomputers. The main idea of the PCMPLB method is first to construct a prefix code tree for processors. Based on the prefix code tree, a schedule for performing load transfer among processors can be determined by concurrently and recursively dividing the tree into two subtrees and finding a maximum matching for processors in the two subtrees until the leaves of the prefix code tree are reached. The experimental results show that the execution time of an application program under the PCMPLB method is less than that of the direct diffusion method and the multilevel diffusion method.