Research
A Review of Contact Tracing Approaches for Controlling COVID-19 Pandemic
The year 2020 will always be in the history of mankind due to the deadly outbreak of COVID-19. Many people are already infected around the world due to the spreading of this novel coronavirus. The virus mainly replicates through close contacts, so there are no other alternatives than to keep social distance, use proper safety gear, and maintain self-quarantine. As a result, the growth of the virus has changed the lifestyle of every individual to a great extent. It is also compelling the Governments to dictate strict lock-downs of the highly affected areas, impose work-from-home approaches where applicable, enforce strict social distancing standards, and so on. Some of the countries are also using smartphonebased applications for contact tracing to track the possibly infected individuals. However, there is a lot of discussion around the world about these contact tracing applications and also about their architecture, attribute, data privacy, and so on. In this paper, we have provided a comprehensive review of these contact tracing approaches in terms of their system architecture, key attributes, and data privacy. We have also outlined a list of potential research directions that can improvise the tracing performance while maintaining the privacy of the user to a great extent.
An Agent-based Grouping Strategy for Federated Grid Computing
Characterizing users based on their requirements and forming groups among providers accordingly to deliver them the stronger quality of service is a challenge for federated grid community. Federated grid computing allows providers to behave cooperatively to ensure required utility by users. Grouping grid providers under such an environment thus enhance the possibility of more jobs executed whereas a single provider or organization might not be able to do the same. In this paper, we propose an agent-based iterative Contract Net Protocol which supports in building federated grid via negotiating distributed providers. The main focus of this paper is to minimize the number of iterations using a grouping mechanism. Minimizing the number of iterations would produce less communication overhead which results in the minimum queue waiting time for users to publish their jobs. Simulation results further ensure the feasibility of our approach in terms of profit and resource utilization compared to that of the traditional non-grouped market.
