A Comparison of Cloud Execution Mechanisms: Fog, Edge and Clone Cloud Computing

Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to  users  and  organizations. Cloud  computing  also  became  an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies gave a new area of computing called mobile cloud computing. This  combined technology is  used to augment the resources existing in smart devices. In recent times Fog computing, Edge computing and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail. This paper also addresses the differences in these technologies and how each of them are effective to organizations and developers.Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing  also became an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies gave a new area of computing called mobile cloud computing. This  combined technology is  used to augment the resources existing in smart devices. In recent times Fog computing, Edge computing and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail. This paper also addresses the differences in these technologies and how each of them are effective to organizations and developers.Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to  users  and  organizations. Cloud  computing  also  became  an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies gave a new area of computing called mobile cloud computing. This  combined technology is  used to augment the resources existing in smart devices. In recent times Fog computing, Edge computing and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail. This paper also addresses the differences in these technologies and how each of them are effective to organizations and developers

A Study of Mobility Support in Wearable Health Monitoring Systems: Design Framework

International audienceThe aim of this work is to investigate main techniques and technologies enabling user's mobility in wearable health monitoring systems. For this, design requirements for key enabling mechanisms are pointed out, and a number of conceptual and technological recommendations are presented. The whole is schematized and presented into the form of a design framework covering design layers and taking in consideration patient context constraints. This work aspires to bring a further contribution for the conception and possibly the evaluation of health monitoring systems with full support of mobility offering freedom to users while enhancing their life qualit

TownshipNet: A Localized Hybrid TVWS-WiFi and Cloud Services Network

This paper describes a network architecture to provide low cost last mile access and cloud services for local content sharing in a poorly resourced township environment. We describe how ICT solutions are developed in close partnership with the local community who will benefit from the interventions. We analyze the data usage patterns of mobile users in the township to provide us with a real understanding of the needs of the community. This data usage analysis is used to inform the design of the network and of the localized cloudlet services. The network consists of hybrid TV White Space and WiFi backhaul and WiFi public access points

Next generation single board clusters

Until recently, cluster computing was too expensive and too complex for commodity users. However the phenomenal popularity of single board computers like the Raspberry Pi has caused the emergence of the single board computer cluster. This demonstration will present a cheap, practical and portable Raspberry Pi cluster called Pi Stack. We will show pragmatic custom solutions to hardware issues, such as power distribution, and software issues, such as remote updating. We also sketch potential use cases for Pi Stack and other commodity single board computer cluster architectures

Situation-aware Edge Computing

Future wireless networks must cope with an increasing amount of data that needs to be transmitted to or from mobile devices. Furthermore, novel applications, e.g., augmented reality games or autonomous driving, require low latency and high bandwidth at the same time. To address these challenges, the paradigm of edge computing has been proposed. It brings computing closer to the users and takes advantage of the capabilities of telecommunication infrastructures, e.g., cellular base stations or wireless access points, but also of end user devices such as smartphones, wearables, and embedded systems. However, edge computing introduces its own challenges, e.g., economic and business-related questions or device mobility. Being aware of the current situation, i.e., the domain-specific interpretation of environmental information, makes it possible to develop approaches targeting these challenges. In this thesis, the novel concept of situation-aware edge computing is presented. It is divided into three areas: situation-aware infrastructure edge computing, situation-aware device edge computing, and situation-aware embedded edge computing. Therefore, the concepts of situation and situation-awareness are introduced. Furthermore, challenges are identified for each area, and corresponding solutions are presented. In the area of situation-aware infrastructure edge computing, economic and business-related challenges are addressed, since companies offering services and infrastructure edge computing facilities have to find agreements regarding the prices for allowing others to use them. In the area of situation-aware device edge computing, the main challenge is to find suitable nodes that can execute a service and to predict a node’s connection in the near future. Finally, to enable situation-aware embedded edge computing, two novel programming and data analysis approaches are presented that allow programmers to develop situation-aware applications. To show the feasibility, applicability, and importance of situation-aware edge computing, two case studies are presented. The first case study shows how situation-aware edge computing can provide services for emergency response applications, while the second case study presents an approach where network transitions can be implemented in a situation-aware manner