Cloud offload is an important technique in mobile computing. VMbased cloudlets have been proposed as offload sites for the resourceintensive and latency-sensitive computations typically associated with mobile multimedia applications. Since cloud offload relies on precisely-configured back-end software, it is difficult to support at global scale across cloudlets in multiple domains. To address this problem, we describe just-in-time (JIT) provisioning of cloudlets under the control of an associated mobile device. Using a suite of five representative mobile applications, we demonstrate a prototype system that is capable of provisioning a cloudlet with a non-trivial VM image in 10 seconds. This speed is achieved through dynamic VM synthesis and a series of optimizations to aggressively reduce transfer costs and startup latency.

VM handoff enables rapid and transparent placement changes to executing code in edge computing use cases where the safety and management attributes of VM encapsulation are important. This versatile primitive offers the functionality of classic live migration but is highly optimized for the edge. Over WAN bandwidths ranging from 5 to 25 Mbps, VM handoff migrates a running 8 GB VM in about a minute, with a downtime of a few tens of seconds. By dynamically adapting to varying network bandwidth and processing load, VM handoff is more than an order of magnitude faster than live migration at those bandwidths. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Background:We propose a new cognitive rehabilitation program, which relies on reading aloud, for elementary school students with autism spectrum disorder (ASD). This study examined reading aloud by children with ASD, hypothesizing that this process would improve the cognitive functions and mental health of these children. Methods: Eleven children (ages: 8 -10 years old) and their mothers participated in this study. They were randomly allocated into the intervention group (6 children) or the control group (five children). The children of the intervention group were asked to read books aloud for 30 min a day five times a week for 5 weeks. The Wisconsin Card Sorting Test (WCST), the Digit Span, the Span-board, the Raven ' s colored Progressive Matrices, and the Child Behavior Check List (CBCL) were used in assessing the effectiveness of this program in improving their cognitive abilities. Results: The primary outcome was " Perseverative errors " of the WCST. The secondary outcomes were " Categories achieved " of the WCST, forward span-board task, backward span-board task, forward digit span, backward digit span, and the total score of the RCPM. Post-pre changes in the test scores of the intervention group were compared with those of the control group by Mann-Whitney ' s U-tests. Significant improvements were shown in " Perseverative errors " and "Categories achieved " of the WCST, and " Depression/Anxiety " of the CBCL. Conclusions:The results revealed that reading aloud improved the children ' s executive function and mental health. The results also indicate that reading aloud can be used for cognitive rehabilitation of children with ASD.

Abstract-Amazon S3-style storage is an attractive option for clouds that provides data access over HTTP/HTTPS. At the same time, parallel file systems are an essential component in privately owned clusters that enable highly scalable dataintensive computing. In this work, we take advantage of both of those storage options, and propose pWalrus, a storage service layer that integrates parallel file systems effectively into cloud storage. Essentially, it exposes the mapping between S3 objects and backing files stored in an underlying parallel file system, and allows users to selectively use the S3 interface and direct access to the files. We describe the architecture of pWalrus, and present preliminary results showing its potential to exploit the performance and scalability of parallel file systems.

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