Miguel Baguena

VACaMobil: VANET Car Mobility Manager for OMNeT++

The performance of communication protocols in vehicular networks highly depends on the mobility pattern. Therefore, one of the most important issues when simulating this kind of protocols is how to properly model vehicular mobility. In this paper we present VACaMobil, a VANET Car Mobility Manager for the OMNeT++ simulator which allows researchers to completely define vehicular mobility by setting the desired average number of vehicles along with its upper and lower bounds. We compare VACaMobil against other common methods employed to generate vehicular mobility. Results clearly show the advantages of the VACaMobil tool when distributing vehicles in a real scenario, becoming one of the best mobility generators to evaluate the performance of different communication protocols and algorithms in VANET environments.

An Adaptive Anycasting Solution for Crowd Sensing in Vehicular Environments

Vehicular networks can be seen as the new key enablers of the future networked society. Vehicles traveling can act as mobile sensors and collect a variety of information that can be used to enable various new services such as environment monitoring, traffic management, urban surveillance, and so on. In this paper, we present “adaptive Anycasting solution for Vehicular Environments” (AVE), which is a message delivery protocol that combines geographical and topological information to dynamically adapt its behavior to network conditions. We focus on vehicle-to-infrastructure connectivity for cloud services, where the vehicles send the sensed information as individual and independent messages to a cloud service in the Internet. This scenario requires access to any available close-by roadside unit, thus making anycasting the ideal delivery mechanism. Simulations results show that the hybrid and adaptive approach of AVE is able to improve network performance. For example, regarding delivery ratio, AVE outperforms DYMO by 10% in sparse scenarios and outperforms delay-tolerant networking techniques by 10% in dense scenarios.

Towards realistic vehicular network simulation models

Recently, testbed deployments using real IEEE 802.11p devices have allowed making performance measurements using this technology. The results obtained in those experiments evidence that lots of factors influence wireless communications: small obstacles like trees, small moving obstacles like cars, or large obstructions like buildings. All of them affect the transmission range, reducing the communication possibilities. Based on the insight provided by these results, in this work we propose a propagation model that attempts to replicate all these effects in simulation in order to increase the accuracy of experiments. Our solution combines (i) an attenuation model that replicates transmission range and fading behavior of real 802.11p devices, both in line-of-sight conditions and when obstructed by small obstacles, and (ii) a visibility model to deal with large architectonic obstacles, such as buildings. Our model was evaluated using the OMNeT++ platform, and results show that having the exact building positions and shapes is a critical parameter, introducing performance differences of up to 50% compared to simpler models.

RCDP: Raptor-based content delivery protocol for unicast communication in wireless networks for ITS

Recent advances in forward error correction (FEC) coding techniques were focused on addressing the challenges of multicast and broadcast delivery. However, FEC approaches can also be used for unicast content delivery in order to solve transmission control protocol issues found in wireless networks. In thispaper, we exploit the error resilient properties of Raptor codes by proposing Raptor-based content delivery protocol (RCDP) — a novel solution for reliable and bidirectional unicast communication in lossy links that can improve content delivery in situations where the wireless network is the bottleneck. RCDP has been designed, validated, optimized, and its performance has been analyzed in terms of throughput and resource efficiency. Experimental results show that RCDP is a highly efficient solution for environments characterized by high delays and packet losses making it very suitable for intelligent transport system oriented applications since it achieves significant performance improvements when compared to traditional transport layer protocols.

Towards enabling hyper-responsive mobile apps through network edge assistance

Poor Internet performance currently undermines the efficiency of hyper-responsive mobile apps such as augmented reality clients and online games, which require low-latency access to real-time backend services. While edge-assisted execution, i.e. moving entire services to the edge of an access network, helps eliminate part of the communication overhead involved, this does not scale to the number of users that share an edge infrastructure. This is due to a mismatch between the scarce availability of resources in access networks and the aggregate demand for computational power from client applications. Instead, this paper proposes a hybrid edge-assisted deployment model in which only part of a service executes on LTE edge servers. We provide insights about the conditions that must hold for such a model to be effective by investigating in simulation different deployment and application scenarios. In particular, we show that using LTE edge servers with modest capabilities, performance can improve significantly as long as at most 50% of client requests are processed at the edge. Moreover, we argue that edge servers should be installed at the core of a mobile network, rather than the mobile base station: the difference in performance is negligible, whereas the latter choice entails high deployment costs. Finally, we verify that, for the proposed model, the impact of user mobility on TCP performance is low.

Demo:: NOMAD: An Edge Cloud Platform for Hyper-Responsive Mobile Apps

Fast access to backend services is crucial for many mobile apps. For example, emerging augmented-reality devices such as Google Glass require fast access to powerful servers to achieve seamless interactivity with the real world; and online gaming clients need to communicate in real-time through centralised game services. A major obstacle to achieving this hyper responsiveness is the performance of the underlying network that interconnects mobile clients and services. Network e↵ects cannot be anticipated, let alone controlled, due to the unpredictability of wide-area networks and the fact that users roam between di↵erent networks. Over time, organisations have gone to great lengths to reduce access latency to backend services by moving them “closer” to end users. In 2010, Google spent

TGRP: Topological-Geographical adaptive Routing Protocol for vehicular environments

1.9 billion on a data centre in New York, despite real estate prices being amongst the highest in the world, to gain direct access to local and global networks [5]. Similarly, cloud service providers such as Amazon AWS have rolled out new infrastructure in edge locations. Proactive measures against high network latencies, however, are limited by the fact that network proximity in a mobile setting is unknown a priori. To enable hyper-responsive mobile apps, Balan et al. [1] first proposed cyber-foraging, i.e. the use of remote resources to augment smartphone capabilities. This led to proposals such as Cloudlets [7], which treat smartphones as thin clients served by virtual device clones, and systems such as MAUI [4] and CloneCloud [2], which apply a more finegrained app partitioning to reduce response times. In general, the above approaches can only improve application responsiveness to the extent that computation delays dominate performance. It remains a challenge to control the impact of high network latencies, especially when users roam between wireless networks of di↵erent operators.

Better Performance in LTE Networks with Edge Assistance: The World of Warcraft Case

Vehicular networks represent an extremely variable and unpredictable environment. Scenarios can vary from very dense and congested configurations to sparsely populated arrangements. Therefore, protocols designed for such a general scope may fail to efficiently behave in certain configurations. In this paper we propose the Topological-Geographical Routing Protocol (TGRP), a novel solution that presents an adaptive behavior by using a set of standard routing strategies. According to the scenario, TGRP chooses among four different routing approaches - two-hop direct delivery, Dynamic MANET On-demand (DYMO), greedy georouting, and store-carry-and-forward technique- to dynamically adapt its behavior to every situation. Performance evaluation shows that TGRP presents a more stable performance under different circumstances, being more adaptable to the changing characteristics of vehicular networks. In fact, TGRP outperforms DYMO by 10% in low density scenarios. In dense networks, TGRP also outperforms the Delay Tolerant Network (DTN) protocol by 10%.

Assessing the impact of obstacle modeling accuracy on IEEE 802.11p based message dissemination

To improve the performance of Massively Multiplayer Online Games (MMOGs) in mobile networks, we explore the potential benefits of an edge-assisted deployment model: part of the MMOG backend service executes closer to the end user at the edge of the LTE network. We investigate the impact on game latency of (1) the exact placement of such edge servers; (2) the number of cooperating game clients; (3) the amount of client requests served at the network edge; (4) the hardware capabilities of edge servers; and (5) user roaming. Based on our analysis, we show that edge assistance can in fact increase the performance of online games over LTE networks as long as at most 50% of the user requests are processed at the network edge. Furthermore, we argue that the Packet Data Network Gateway (PGW) is the most appropriate place for hosting edge servers and show that TCP performance in the proposed setting is not affected by user roaming.

RCDP: a novel content delivery solution for wireless networks based on raptor codes

Deploying real IEEE 802.11p vehicular network testbeds is a challenging but difficult option for most researchers. In these cases, the research community relies on simulation tools to test their protocols. However, since simulation accuracy is a critical issue, real testbed results should be used as a reference to improve simulation behavior. Our proposal adjusts common propagation models to mimic samples taken from real environments, and it uses a building aware model to achieve as much accuracy as possible in urban scenarios. We evaluate the performance differences obtained with this model against other usual simulation schemes, like line-of-sight propagation models, models where no building blockage is taken into account, and models where propagation is only allowed along streets, achieving differences of up to 70% in some measurements. Going a step further, the model is used to study the radio propagation behavior along different city layouts, showing that the actual building layout is one of the key factors affecting protocol performance in urban environments.