Self-management of Distributed Computing Using Hybrid-Computing Elements
Tarek Ali, Eman S. Nasr, Mervat H. Gheith · 2016
The expression "hybrid-computing elements" denotes a category of computing elements where human-based and machine-based computing elements complement one another. This hybridity supports human tasks, for example, TopCoder might be used to manage hybrid-computing elements which are used in crowdsourcing software. Managing a human-based computing element is a more complex process than managing a machine-based computing element, as the task must be "structured". This leads to deal with more macro-sociological factors on tasks than formal languages usually work with. We hence model the hybridity using two types of computing elements: The human-based, with whatever purposes the crowd envisions, and the machine-based which is used to develop it. This research presents the adaptation engine, a new rule-based engine for the description of hybridity. These rules can be composed of a set of smaller atomic, reusable, parametric, interchangeable and interoperable human-based and machine-based computing elements, with clear restrictions on their combinations. It identifies the underlying seven building-blocks to use a biological metaphor. The seven blocks that are managed in crowdsourcing software development: Task, social, motivations, experiences, limitations, software development life cycle and management blocks. We illustrate our model with the application of this engine to manage an adaptive crowdsourcing software that generates interfaces with hints, which can be adapted based on defined rules. We evaluate our model by developing a business application through crowd work. The primary result was completed well for managing self-adaptive software.