Cloud computing is an information technology that enables different users to access a shared pool of configurable system resources and different services without physically acquiring them. Most industries nowadays such as banking, healthcare and education are migrating to the cloud due to its efficiency of services especially when it comes to data security and integrity. Cloud platforms encounter numerous challenges such as Data deduplication, Data Transmission, Data Integrity, VM Security, Data Availability, Bandwidth usage… etc. In this paper we have adopted the Blockchain technology - which is a relatively new technology - that emerged for the first time as the cryptocurrency Bitcoin and proved its efficiency in securing data and assuring data integrity. It is mostly a distributed public ledger that holds transactions data in case of Bitcoin. In our work blockchains are adopted in a different way than its regular use in bitcoin. Three of the major challenges in Cloud Computing and Cloud services are Data Deduplication, Storage and Bandwidth usage are discussed in this paper.
Serious games are transcending the way of teaching and learning nowadays. Since serious games balance playful and educational aspects, it constitutes a privileged learning method for the digital natives. However, they are ubiquitous in today's society and their stakes and assets remain largely fuzzy. This paper describes different models and frameworks for serious game design. Between theoretical and technical consideration, authors propose a new reflection model that aims to help pedagogues guiding their conception of serious games. This model is a result of a thematic synthesis analyzing more than 40 texts offering a three-layered model covering the simplest to the most advanced design. Three study cases are announced to be conducted by the end of this year in order to challenge and evaluate this new model.
Cloud users can have access to the service based on “pay as you go.” The daily increase of cloud users may decrease the performance, the availability and the profitability of the material and software resources used in cloud service. These challenges were solved by several load balancing algorithms between the virtual machines of the data centers. In order to determine a new load balancing improvement; this article's discussions will be divided into two research axes. The first, the pre-classification of tasks depending on whether their characteristics are accomplished or not (Notion of Levels). This new technique relies on the modeling of tasks classification based on an ascending order using techniques that calculate the worst-case execution time (WCET). The second, the authors choose distributed datacenters between quasi-similar virtual machines and the modeling of relationship between virtual machines using the pre-scheduling levels is included in the data center in terms of standard mathematical functions that controls this relationship. The key point of the improvement, is considering the current load of the virtual machine of a data center and the pre-estimation of the execution time of a task before any allocation. This contribution allows cloud service providers to improve the performance, availability and maximize the use of virtual machines workload in their data centers.
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