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Botta A.,University of Naples Federico II | De Donato W.,NM2 SRL | Persico V.,NM2 SRL | Pescape A.,NM2 SRL
Future Generation Computer Systems | Year: 2016

Cloud computing and Internet of Things (IoT) are two very different technologies that are both already part of our life. Their adoption and use are expected to be more and more pervasive, making them important components of the Future Internet. A novel paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios. In this paper, we focus our attention on the integration of Cloud and IoT, which is what we call the CloudIoT paradigm. Many works in literature have surveyed Cloud and IoT separately and, more precisely, their main properties, features, underlying technologies, and open issues. However, to the best of our knowledge, these works lack a detailed analysis of the new CloudIoT paradigm, which involves completely new applications, challenges, and research issues. To bridge this gap, in this paper we provide a literature survey on the integration of Cloud and IoT. Starting by analyzing the basics of both IoT and Cloud Computing, we discuss their complementarity, detailing what is currently driving to their integration. Thanks to the adoption of the CloudIoT paradigm a number of applications are gaining momentum: we provide an up-to-date picture of CloudIoT applications in literature, with a focus on their specific research challenges. These challenges are then analyzed in details to show where the main body of research is currently heading. We also discuss what is already available in terms of platforms-both proprietary and open source-and projects implementing the CloudIoT paradigm. Finally, we identify open issues and future directions in this field, which we expect to play a leading role in the landscape of the Future Internet. © 2015 Elsevier B.V.


Marchetta P.,University of Naples Federico II | Montieri A.,NM2 S.r.l. | Persico V.,University of Naples Federico II | Pescape A.,University of Naples Federico II | And 2 more authors.
IEEE Workshop on Local and Metropolitan Area Networks | Year: 2016

Traceroute is largely considered as the number-one tool when troubleshooting the network, with innumerable applications, such as pinpointing the routing deficiencies or detecting and locating network outages. Previous works have extensively investigated pitfalls and flaws causing the measurements performed with this tool to be inaccurate or incomplete. In this paper, we show how, even in the absence of all these well-investigated pitfalls and flaws, our ability to properly troubleshoot the network with Traceroute is strongly limited. Indeed, by using state-of-the-art alias resolution techniques, we investigate how and how much the IP-level description provided by Traceroute can distort our understanding of the characteristics of Internet paths. We experimentally evaluate the impact on path properties like equal-cost multipaths, loops, routing cycles, load balancing, route prevalence and persistence. Our results confirm that researchers and network operators relying on Traceroute may poorly estimate (i) the number of multiple equal-cost routes to the destination; (ii) the presence of suboptimal routing in the network; (iii) the routing stability. © 2016 IEEE.


Mostafaei H.,Third University of Rome | Montieri A.,NM2 srl | Persico V.,University of Naples Federico II | Pescape A.,NM2 srl | Pescape A.,University of Naples Federico II
Proceedings - IEEE Symposium on Computers and Communications | Year: 2016

Wireless sensor networks (WSNs) are currently adopted in a vast variety of domains. Due to practical energy constraints, in this field minimizing sensor energy consumption is a critical challenge. Sleep scheduling approaches give the opportunity of turning off a subset of the nodes of a network - without suspending the monitoring activities performed by the WSN - in order to save energy and increase the lifetime of the sensing system. Our study focuses on partial coverage, targeting scenarios in which the continuous monitoring of a limited portion of the area of interest is enough. In this paper, we present PCLA, an efficient algorithm based on Learning Automata that aims at minimizing the number of sensors to activate, such that a given portion of the area of interest is covered and connectivity among sensors is preserved. Simulation results show how PCLA can select sensors in an efficient way to satisfy the imposed constraints, thus guaranteeing better performance in terms of both working-node ratio and WSN lifetime. Also, we show how PCLA outperforms state-of-the-art partial-coverage algorithms. © 2016 IEEE.


Botta A.,University of Naples Federico II | Botta A.,NM2 Srl | Avallone A.,University of Naples Federico II | Garofalo M.,University of Naples Federico II | Ventre G.,University of Naples Federico II
ICISSP 2016 - Proceedings of the 2nd International Conference on Information Systems Security and Privacy | Year: 2016

Network neutrality is a hot topic since a few years and involves different aspects of interest (e.g. economic, regulatory and privacy) for a wide range of stakeholders, including policy makers, researchers, economists, and service providers. When referring to video streaming, a killer web service of the Internet, much has been discussed regarding if and how video providers violate or may violate neutrality principles, in order to give users a "better" service compared to other services or to other providers. In this paper we provide a contribution to this discussion analyzing the performance of three main video hosting providers (i.e. YouTube, Vimeo, and Dailymotion) from an user viewpoint. We measure the throughput and RTT experienced by users watching real videos of different popularity, at different day hours and at several locations from around the world. We uncover the performance differences of these providers as a function of the different variables under control and move a step forward to understand what causes such differences. Our results allow to understand what are the real performance users currently get from these providers and if the performance differences observed can be due or to considered as a violation of network neutrality principles, providing a ground for people interested in legal and regulatory issues of web applications and services. Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.


Berger A.,Telecommunications Research Center Vienna | D'Alconzo A.,AIT Austrian Institute of Technology | Gansterer W.N.,University of Vienna | Pescape A.,University of Naples Federico II | Pescape A.,NM2 Srl
Computer Networks | Year: 2016

We consider the analysis of network traffic data for identifying highly agile DNS patterns which are widely considered indicative for cybercrime. In contrast to related approaches, our methodology is capable of explicitly distinguishing between the individual, inherent agility of benign Internet services and criminal sites. Although some benign services use a large number of addresses, they are confined to a subset of IP addresses, due to operational requirements and contractual agreements with certain Content Distribution Networks. We discuss DNSMap, a system which analyzes observed DNS traffic, and continuously learns which FQDNs are hosted on which IP addresses. Any significant changes over time are mapped to bipartite graphs, which are then further pruned for cybercrime activity. Graph analysis enables the detection of transitive relations between FQDNs and IPs, and reveals clusters of malicious FQDNs and IP addresses hosting them. We developed a prototype system which is designed for realtime analysis, requires no costly classifier retraining, and no excessive whitelisting. We evaluate our system using large data sets from an ISP with several 100,000 customers, and demonstrate that even moderately agile criminal sites can be detected reliably and almost immediately. © 2016 Elsevier B.V. All rights reserved.


Botta A.,University of Naples Federico II | de Donato W.,University of Naples Federico II | Persico V.,NM2 SRL | Pescape A.,NM2 SRL
Future Generation Computer Systems | Year: 2015

Cloud computing and Internet of Things (IoT) are two very different technologies that are both already part of our life. Their adoption and use are expected to be more and more pervasive, making them important components of the Future Internet. A novel paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios.In this paper, we focus our attention on the integration of Cloud and IoT, which is what we call the CloudIoT paradigm. Many works in literature have surveyed Cloud and IoT separately and, more precisely, their main properties, features, underlying technologies, and open issues. However, to the best of our knowledge, these works lack a detailed analysis of the new CloudIoT paradigm, which involves completely new applications, challenges, and research issues. To bridge this gap, in this paper we provide a literature survey on the integration of Cloud and IoT. Starting by analyzing the basics of both IoT and Cloud Computing, we discuss their complementarity, detailing what is currently driving to their integration. Thanks to the adoption of the CloudIoT paradigm a number of applications are gaining momentum: we provide an up-to-date picture of CloudIoT applications in literature, with a focus on their specific research challenges. These challenges are then analyzed in details to show where the main body of research is currently heading. We also discuss what is already available in terms of platforms-both proprietary and open source-and projects implementing the CloudIoT paradigm. Finally, we identify open issues and future directions in this field, which we expect to play a leading role in the landscape of the Future Internet. © 2015 Elsevier B.V.

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