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One of the main global challenges to cope with for a sustainable development is transport and mobility. They are undisputed key issues of modern life affecting people's well-being and quality of life, which are significantly impacting the environment. In this scenario, innovative self-driving car technologies and electric solutions, emerging sensing technologies, and interconnected infrastructure can lead to more efficient transport systems and innovative mobility services, keeping into account the urgent need to foster a sustainable development. This workshop aims to gather practitioners with different background and different perspective from both Academia and Industry to further the knowledge in the area of emerging smart technologies and infrastructures for Smart Mobility and Sustainability.

In the last several years the awareness about pollution levels and other natural hazards has risen significantly. Millions of citizens globally pay daily attention to air quality and other factors such as for instance UV index and pollens. This new need has been so far met by a plethora of smartphone applications that leverage data collected by the city-operated stations or, in some cases, community-based stations located at the user premises. In this work we exploit recent advances in micro-controllers and sensing technologies to design and implement a personal pollution awareness system tiny enough to be embedded into user accessories. In particular, we will introduce the concept and the architecture of our prototype and show the preliminary results we collected using this prototype.

The need for Internet access from moving vehicles has been steadily increasing in the past few years. Solutions that rely on cellular connectivity are becoming impractical to deploy due to technical and economic reasons. Car-Fi proposes an approach that leverages existing home Wi-Fi access points configured in dual-access mode, in order to offload all data traffic from the congested and expensive cellular infrastructure to whatever Wi-Fi network is available. Thanks to an improved scanning algorithm and numerous optimizations to the connection setup, Car-Fi makes downloading large amounts of data from a moving car feasible.

MoViT is a distributed software suite for the emulation of mobile wireless networks. MoViT provides researchers and developers with a virtualized environment for developing and testing mobile applications and protocols for any hardware and software platform that can be virtualized. The distributed nature of MoViT allows for the emulation of mobile networks of arbitrary size. Additionally, the network connectivity is shaped transparently such that the connectivity observed by each virtual node resembles that of a physical mobile network. In this paper we present the MoViT architecture, the models used to emulate the wireless channel, the details of our initial implementation and, finally, the results of our evaluation regarding the scalability, realism, and versatility of MoViT. © 2012 ACM.

Multicast streaming is gaining increasing importance in wireless ad hoc networks, in part because ad hoc scenarios often include team activities and the requirement for distribution of audio, video and situation awareness to the members. At the network level, techniques for routing the multimedia streams are quite mature. Much more challenging is the allocation of resources, the fair sharing among streams and the control of congestion. While in rate adaptive UNICAST streams congestion control and fair sharing are accomplished with end-to-end feedback techniques inspired to TCP, the feedback does not scale well in MULTICAST. In fact, it leads to the well knows ACK/NAK "implosion" problem and unfair penalties for heterogeneous receivers. These limitations can be overcome using backpressure from congestion points to the sources - but this approach suffers of latency and cannot rapidly adjust to changes in traffic. Another solution is multilayer adaptive coding. Namely, the encoding adaptation is done locally by dropping layers. It does not require end-to-end feedback nor changes in input rates. Multi-resolution codes are now becoming attractive due to the progress in technology; we expect these to become the prevalent techniques in large scale media distribution. One issue, however, that still remains to be resolved is the fair sharing among competing multicast streams. In this paper we address the congestion control AND fair sharing in a multilayer multicast scenario. We show that lack of proper fairness provisions in the "local adjustments" can lead to serious capture situations, especially in heterogeneous traffic mixes (e.g. voice and video). We then propose a FAIR local adjustment that targets a fair dropping of packets in each interference domain. We show that the scheme can be interpreted as a distributed implementation of a utility function minimization, where the utility is the packet loss subject to fairness bounds across flows. This formulation guarantees stability and convergence of the distributed algorithm. The main contributions of this paper are the low overhead design of the local fairness enforcement algorithm, the utility function framework and the demonstration of convergence via simulation in representative scenarios. Copyright 2008 ACM.

In an urban environment, vehicles can opportunistically exploit infrastructure through open Access Points (APs) to efficiently communicate with other vehicles. This is to avoid long wireless ad hoc paths, and to alleviate congestion in the wireless grid. Analytic and simulation models are used to optimize the communications and networking strategies. For realistic results, one important challenge is the accurate representation of traffic mobility patterns. In this paper we introduce realistic vehicular mobility traces of downtown Portland, Oregon, obtained fromextremely detailed large scale traffic simulations performed at the Los Alamos National Laboratories (LANL). To the best of our knowledge, these are among the most accurate synthetic motion traces available for study, with the exception of actual car trace measurements. The new mobility model is used to evaluate AODV [1] in flat and opportunistic infrastructure routing. To assess the importance of a realistic mobility model for this evaluation, we compare these results with those obtained with CORSIM [2] traces. The paper makes the following contributions: (a) introduction of efficient, opportunistic strategies for extending the AP infrastructure to use vehicle to vehicle paths, and (b) assessment of different mobility models - CORSIM traces and LANL's realistic vehicular traces - in the modeling of different routing strategies. Copyright 2007 ACM.