Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan.

Unraveling the Effects of Task Sequencing on the Syntactic Complexity, Accuracy, Lexical Complexity, and Fluency of L2 Written Production

Although several studies have explored the effects of task sequencing on second language (L2) production, there is no established set of criteria to sequence tasks for learners in L2 writing classrooms. This study examined the effect of simple ̶ complex task sequencing manipulated along both resource-directing (± number of elements) and resource-dispersing (± planning time) factors on L2 writing compared to individual task performance using Robinson’s (2010) SSARC model of task sequencing. Upper-intermediate L2 learners (N = 90) were randomly divided into two groups: (1) Participants who performed three writing tasks in a simple–complex sequence, and (2) participants who performed either the simple, less complex, or complex task. Findings revealed that simple-complex task sequencing led to increases in syntactic complexity, accuracy, lexical complexity, and fluency, as compared to individual task performance. Results are discussed in light of the SSARC model, and theoretical and pedagogical implications are provided.

EXISTENCE AND SIZING OF BUFFERS IN PARALLEL ASSEMBLY LINES WITH MULTI-LINE WORKSTATIONS AND DIFFERENT CYCLE TIMES

ABSTRACT: Parallel Assembly Lines with multi-line stations (PALBs) have been widely studied in recent years because PALBs can help improve the efficiency of a production system. However, the need of buffers has not been considered in the PALBP literature. In this study, for the first time in the literature, it is shown and demonstrated the need to consider the use of buffers in this type of line when their cycle times are different. Moreover, the buffer sizing problem in a multi-line workstation is presented and formalized. It is shown that the sequencing and scheduling of the task influences the buffer size. Finally, the designed resolution method is shown: solve a mixed integer linear programming model with a commercial software, with the objective of minimizing the size of the buffers. Keywords: Parallel assembly lines balancing, buffer sizing, task sequencing and scheduling.