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Ralph Deters

Researcher at University of Saskatchewan

Publications -  206
Citations -  4193

Ralph Deters is an academic researcher from University of Saskatchewan. The author has contributed to research in topics: Mobile computing & Mobile device. The author has an hindex of 28, co-authored 199 publications receiving 3252 citations. Previous affiliations of Ralph Deters include Bundeswehr University Munich & Pennsylvania State University.

Papers
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Integrating blockchain-based access control model TBAAC for privacy and accountability for water science project

Tanvi Jain, +1 more
TL;DR: In this paper , the authors introduce the TBAAC (Token-based attributed access control) management, a modified attribute-based access control (ABAC) scheme to explore the full potential of the used schemas and strategies in a blockchain-supported client application.
Journal Article

Transparent Scheduling of Composite Web Services

TL;DR: This paper focuses on the use of request scheduling for improving CWS performance in overload situations and different scheduling policies are investigated in regards to their effectiveness in helping with bulk arrivals.
Proceedings ArticleDOI

Using Call-Context to Prevent the Emergence of Chaotic Workflow Behaviors in Overload Situations

TL;DR: This paper examines the chaotic behavior of sequential workflows in overload situations and discusses the use of call-contexts as a means of avoiding them.

Improving the Elasticity of Services with a P2P Infrastructure

Weidong Han, +1 more
TL;DR: This paper presents a novel P2P based management approach for WS providers, that allows organizations to dynamically add or remove replicated providers at runtime and thus increases their elasticity and enables organizations to respond faster to changes in WS consumer behavior.
Proceedings ArticleDOI

User Models as Digital Twins: Using Webassembly Techniques to ensure Privacy, Transparency and Control in Personalization

TL;DR: In this paper , a half-day tutorial demonstrates how web-assembly techniques can be used to create sandboxed user models as digital twins within web- and mobile applications, which can learn from the user's behaviour and personalise the application to the user, while ensuring transparency of the model, and ability for the user to experiment and control the personalization.