Biblio

Fog computing is a new paradigm which extends cloud computing services into the edge of the network. Indeed, it aims to pool edge resources in order to deal with cloud's shortcomings such as latency problems. However, this proposal does not ensure the honesty and the good behavior of edge devices. Thus, security places itself as an important challenge in front of this new proposal. Authentication is the entry point of any security system, which makes it an important security service. Traditional authentication schemes endure latency issues and some of them do not satisfy fog-computing requirements such as mutual authentication between end devices and fog servers. Thus, new authentication protocols need to be implemented. In this paper, we propose a new efficient authentication scheme for fog computing architecture. Our scheme ensures mutual authentication and remedies to fog servers' misbehaviors. Moreover, fog servers need to hold only a couple of information to verify the authenticity of every user in the system. Thus, it provides a low overhead in terms of storage capacity. Finally, we show through experimentation the efficiency of our scheme.

In this paper we present a framework for Quality of Information (QoI)-aware networking. QoI quantifies how useful a piece of information is for a given query or application. Herein, we present a general QoI model, as well as a specific example instantiation that carries throughout the rest of the paper. In this model, we focus on the tradeoffs between precision and accuracy. As a motivating example, we look at traffic video analysis. We present simple algorithms for deriving various traffic metrics from video, such as vehicle count and average speed. We implement these algorithms both on a desktop workstation and less-capable mobile device. We then show how QoI-awareness enables end devices to make intelligent decisions about how to process queries and form responses, such that huge bandwidth savings are realized.