Showing papers by "Djamel Sadok published in 2018"

Modeling the availability of an e-health system integrated with edge, fog and cloud infrastructures

Abstract: The Internet of Things has the potential of transforming health systems through the collection and analysis of patient physiological data via wearable devices and sensor networks. Such systems can offer assisted living services in realtime and offer a range of multimedia-based health services. However, lack of service availability, particularly in the cases of emergencies, can lead to adverse outcomes and in the worst case, death. In this paper, we propose an e-health monitoring architecture based on sensors and cloud and fog infrastructure scenarios. Further, we propose stochastic models to analyze how failures impact on the e-health system availability. We analyze four different scenarios and from results, we identify that the sensors and fog devices are the components that have the most significant impact on the availability of the entire e-health system in the scenarios analyzed.

A Survey on Efforts to Evolve the Control Plane of Inter-Domain Routing

Abstract: The Internet’s default inter-domain routing protocol is the Border Gateway Protocol (BGP). With the BGP, dozens of thousands of Autonomous Systems (ASs) exchange network layer reachability information to manage connectivity among them. The BGP was introduced in the early stages of the Internet, and although the BGP is one of the most successful protocols, new desirable features have been difficult to incorporate into the network over the decades. Thus, this paper classifies previous works to evolve the control plane of inter-domain routing into three types of approaches: brand new design; incremental improvement; inter-domain communication. The main goal of this paper is to provide an understanding of what approaches have been taken to evolve the inter-domain routing control plane. This survey also discusses why the control plane’s issues are hard to evolve and future perspectives for that topic.

SiMoNa: A Proof-of-concept Domain Specific Modeling Language for IoT Infographics

Abstract: The Internet of Things (IoT) has emerged as one of the prominent concepts in academic discourse in recent times reflecting a wider trend by industry to connect physical objects to the Internet and to each other. The IoT is already generating an unprecedented volume of data in greater varieties and higher velocities. Making sense of such data is an emerging and significant challenge. Infographics are visual representations that provide a visual space for end users to compare and analyze data, information, and knowledge in a more efficient form than traditional forms. The nature of loT requires a continuum modification in how end users see information to achieve such efficiency gains. Conceptualizing and implementing Infographics in an loT system can thus require significant planning and development for both data scientists, graphic designers and developers resulting in both costs in terms of time and effort. To address this problem, this paper presents SiMoNa, a domain-specific modeling language (DSML) to create, connect, interact, and build interactive infographic presentations for loT systems efficiently based on the model-driven develonment (MDD) naradiam.

MODC: A Pareto-Optimal Optimization Approach for Network Traffic Classification Based on the Divide and Conquer Strategy

Abstract: Network traffic classification aims to identify categories of traffic or applications of network packets or flows It is an area that continues to gain attention by researchers due to the necessity of understanding the composition of network traffics, which changes over time, to ensure the network Quality of Service (QoS) Among the different methods of network traffic classification, the payload-based one (DPI) is the most accurate, but presents some drawbacks, such as the inability of classifying encrypted data, the concerns regarding the users’ privacy, the high computational costs, and ambiguity when multiple signatures might match For that reason, machine learning methods have been proposed to overcome these issues This work proposes a Multi-Objective Divide and Conquer (MODC) model for network traffic classification, by combining, into a hybrid model, supervised and unsupervised machine learning algorithms, based on the divide and conquer strategy Additionally, it is a flexible model since it allows network administrators to choose between a set of parameters (pareto-optimal solutions), led by a multi-objective optimization process, by prioritizing flow or byte accuracies Our method achieved 9414% of average flow accuracy for the analyzed dataset, outperforming the six DPI-based tools investigated, including two commercial ones, and other machine learning-based methods

IMMS: IoT Management and Monitoring System

Abstract: The Internet of Things already comprehends billions of connected smart devices. The related issues are vast as well, ranging from the lack of standardized communication to big data management. This paper presents IoT Management and Monitoring System (IMMS), a solution focused on the management of big environments such as smart cities. The The proposed platform brings a novel database implementation to handle large volumes of data and provide quick responses to queries. Its design allows scalable and distributed deployments, while accepting diverse data types. The system was evaluated both in a real-world testbed, in a university campus, and a simulated environment. Results showed low CPU costs while consuming 1.1GB to store 21.5 million measurements. Besides, its scalability behaved as expected, maintaining its performance adequate as data volume increased.

Accountability for Federated Clouds

Abstract: The evolution of software service delivery has changed the way accountability is performed. The complexity related to cloud computing environments increases the difficulty in properly performing accountability, since the evidences are spread through the whole infrastructure, from different servers at physical, virtualization, and application layers. This complexity increases when we are considering cloud federation because besides the inherent complexity of the virtualized environment, the federation members may not implement the same security procedures and policies. The main objective of this chapter is to present concepts about cloud security, discussing why accountability in federated scenarios is important and hard to provide, and propose an accountability framework, named CloudAcc, that supports audit, management, planning and billing process in federated cloud environments.