Fehmi Ben Abdesslem

Design choices for the IoT in Information-Centric Networks

This paper outlines the tradeoffs involved in utilizing Information-Centric Networking (ICN) for Internet of Things (IoT) scenarios. It describes contexts and applications where the IoT would benefit from ICN, and where a host-centric approach would be better. Requirements imposed by the heterogeneous nature of IoT networks are discussed in terms of connectivity, power availability, computational and storage capacity. Design choices are then proposed for an IoT architecture to handle these requirements, while providing efficiency and scalability. An objective is to not require any IoT specific changes of the ICN architecture per se, but we do indicate some potential modifications of ICN that would improve efficiency and scalability for IoT and other applications.

Cacheability of YouTube videos in cellular networks

Video traffic now represents a growing proportion of the traffic on cellular networks, causing capacity problems for operators and increased delays for users. Studies have shown that deploying caches at the network level reduces the delay for the end-user and the overall traffic volume for the telecom operator. In this paper, we analyse a large nationwide dataset of real-life video requests sent by mobile users to a popular video streaming website. This analysis is the first to rely on such a large dataset, and sheds light on the optimal cacheability of video content with caches distributed in the cellular network, and how efficient some existing cache replacement algorithms are at reducing the number of requests sent to the video provider. We show that depending on the cache size and algorithm parameters, up to 20.33% of the requests can be served by a local cache.

Demo: mobile opportunistic system for experience sharing (MOSES) in indoor exhibitions

Information-Centric Networking (ICN) is an alternative architecture for computer networks, where the communication is focused on the data being transferred instead of the communicating hosts. This paper describes a demo of an experience sharing application for mobile phones built on an ICN platform designed for devices with intermittent connectivity. In particular, we detail how this application will be showcased in an indoor exhibition where experience is shared with media content that is geo-tagged using Bluetooth beacons and spread opportunistically to other users.

Looking Around First: Localized Potential-Based Clustering in Spontaneous Networks

We propose a new budget-based clustering algorithm for self-organizing networks. The basic idea behind our solution is that nodes first sense the environment using inherent Hello packets before starting forming clusters. In contrast with previous solutions that blindly distribute the budget to nearby nodes, our potential-based clustering algorithm applies a proportional budget distribution based on the connectivity degree of the nodes. This approach matches the principle that nodes in real networks are not uniformly distributed. Our simulation results show that the proposed approach outperforms previous ones.

Large scale characterisation of YouTube requests in a cellular network

Traffic from wireless and mobile devices is expected to soon exceed traffic from fixed devices. Understanding the behaviour of users on mobile devices is important in order to improve the offered services and the provision of the underlying network. Globally, more than 60% of consumer Internet traffic is estimated to be video traffic, and the most popular video website, YouTube, estimates that mobile access makes up nearly 40% of the global watch time. This paper presents the first work to study the characteristics of YouTube user requests on a nationwide cellular network. This study is based on the analysis of a large dataset generated by 3 million users and collected by a major telecom operator. We show for instance that 20% of the users generate 78% of the requests, and that over 80% of the requests target only 20% of the distinct videos accessed during the data collection period. Our results provide a comprehensive insight into the way people use YouTube on mobile devices, and show a very high potential for video cacheability on the cellular network.

The pursuit of 'appiness: Exploring Android market download behaviour in a nationwide cellular network

Mobile devices are now part of our everyday lives, and the emergence of online application marketplaces allow a rapid spread of new mobile applications to a large user base. Such user-installed mobile applications constitute a large part of our daily interaction with the devices. With more than one million available applications, Android Market, the online catalog for Android devices allows users to choose and download a large selection of disparate applications. Analysing and characterising the application marketplace download patterns provides a better insight on the needs and behaviour of users In this paper, we explore a large dataset collected by a major European telecom operator to study the downloads of Android applications on a nationwide scale. Our findings include that more than 43% of the application data downloaded is for games, and that a set of only 10 GB of applications is responsible for 88% of the 45 TB downloaded in total by all the users.

Team communication strategy for collaborative exploration by autonomous vehicles

Exploring a large area can be conveniently performed by a team of small autonomous vehicles for different applications, such as search and rescue, cleaning, or lawn mowing. The efficiency and performance of such autonomous exploration depends on the exploration algorithm implemented by the vehicles, and can be enhanced with a better communication and collaboration strategy within the team. In this paper, a new algorithm is proposed and evaluated where vehicles with a limited communication range pro-actively seek their teammates to exchange information about the explored area. Simulations show that this approach allows the vehicles to finish the exploration and return to their base station 18% faster, without consuming more energy.

Understanding usage and activity in cellular networks by investigating HTTP requests

The number of mobile devices is estimated to now exceed the worlds population, using more and more cloud services, and hence generating more and more traffic. Smartphones generate 95% of the total global handset traffic, and while approximately half of this traffic is sent to cellular networks, other handsets such as tablets are also using increasingly the cellular networks. This paper provides a closer look at the traffic generated on cellular networks by exploring billions of HTTP requests sent by millions of users to a nation-wide cellular network during 41 days. We confirm that - as in many other contexts - 20% of the users are responsible for more than 80% of the requests and provide a deeper analysis of the cellular network usage. Furthermore, we characterise the activity of users on their mobile device and which cloud services they use. For instance, almost 30% of the users use the cellular network frequently, mainly using search services and social networks, but 20% of their requests are sent to advertisement and tracking systems.

Fair and Flexible Budget-Based Clustering

An efficient way to bound the size of clusters in large-scale self-organizing wireless networks is to rely on a budget-based strategy. The side effect of conventional budget-based clustering approaches is that they generate a potentially large number of small, even single-node, clusters. The consequence is that while clusters are bounded, their average size may be far from the expected value (the budget), which negatively impacts the performance of the communication systems running on top of it. In contrast, we propose Fair and Flexible Budget-Based Clustering (FFBC) to form size-controlled clusters in large-scale self-organizing networks. For a given target cluster size, our approach outperforms previous budget-based algorithms by creating clusters of average size closer to the requested value and avoiding isolated nodes.