A Context-aware Workflow System Framework and Scheduling Algorithm

2014 ◽  
Vol 11 (18) ◽  
pp. 6689-6701
Author(s):  
Pengfei Wang
2013 ◽  
Vol 12 (20) ◽  
pp. 5616-5620 ◽  
Author(s):  
Wang Xiao-chi ◽  
Xu Jie ◽  
Fang Zhi-gang

2020 ◽  
Vol 16 (1) ◽  
pp. 85-94
Author(s):  
Michael Chima Ogbuachi ◽  
Anna Reale ◽  
Péter Suskovics ◽  
Benedek Kovács

This paper is an extension of work originally presented in SoftCOM 2019 [1]. The novelty of this work reside in its focused improvement of our scheduling algorithm towards its usage on a real 5G infrastructure. Industrial IoT applications are often designed to run in a distributed way on the devices and controller computers with strict service requirements for the nodes and the links between them. 5G, especially in concomitance with Edge Computing, will provide the desired level of connectivity for these setups and it will permit to host application run-time components in edge clouds. However, allocation of the edge cloud resources for Industrial IoT (IIoT) applications, is still commonly solved by rudimentary scheduling techniques (i.e. simple strategies based on CPU usage and device readiness, employing very few dynamic information). Orchestrators inherited from the cloud computing, like Kubernetes, are not satisfying to the requirements of the aforementioned applications and are not optimized for the diversity of devices which are often also limited in capacity. This design is especially slow in reacting to the environmental changes. In such circumstances, in order to provide a proper solution using these tools, we propose to take the physical, operational and network parameters (thus the full context of the IIoT application) into consideration, along with the software states and orchestrate the applications dynamically.


2013 ◽  
Vol 10 (11) ◽  
pp. 155-164 ◽  
Author(s):  
Zheng Hong ◽  
Pan Li ◽  
Wang Jingxiao

Author(s):  
Yitayish Lema Et.al

Context-aware systems are getting rapid popularity towards enabling a pervasive computing environment over hand-held mobile devices, wearable devices, and Tablets.  These systems deliver services tailored to the specific needs and user’s context. The context-aware system services can utilize information about the user’s context to adapt services based on the user’s location. The prime aim of this research paper is to investigate and analyse the critical issues and challenges while delivering the job information to the job seekers when they migrate from one place to another in search of jobs. In addition, the research also tries to investigate the challenges faced by employers/ job providers when they search and recruit the right person for the right jobs. In this paper the issues and challenges investigated and analysed were timeliness of information dissemination, opportunity missing, fake/genuine information, anywhere, anytime accessibility over small handheld devices. After rigorous analysis of the investigated issues and challenges in the existing state of art employment/job information dissemination systems, a real-time context-aware employment information delivery system framework for the pervasive environment is proposed. The research parameters considered are Preference of Job seekers, Location of Jobs, Context, Qualification, CGPA, Experience, everywhere access at any time, and Identity.  The paper used both the quantitative and qualitative approaches for proposing a research-based applied solution. Survey of job seekers, Interview of recruiters, and technical observation of the researcher are used for collecting the relevant facts to check the researchability of the issues and challenges. Protégé version 4.3 is used for modelling, Edraw-Max for designing the framework, Google Form for Survey, and Justin mind tool for Prototype design and testing. The framework and its Prototype was examined using a user acceptance test. The acceptance test indicated that 84.6% of target stakeholders accepted the proposed system framework as a new knowledge solution for the aforementioned issues and challenges in the employment sectors


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