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Gamma Deployment is a metric for evaluating the distribution of roadside units in vehicular networks in terms of two parameters: a) the inter-contact time between vehicles and the infrastructure, and, b) the share of vehicles that must respect the inter-contact time guarantees. We envision the use of the Gamma Deployment metric when the network designer intends to distribute check-points along the...
In this work the allocation of Roadside Units (RSUs) in a V2I network is modeled as a Maximum Coverage Problem. The main objective is to maximize the number of distinct vehicles contacting the infrastructure. Two different approaches are presented to solve the problem. The first one is an ILP model that can found optimal solutions or give sharp upper and lower bounds for the problem. The second one...
In this work we propose Delta-r, a new greedy heuristic for solving the allocation of roadside units in order to meet a Δρ1ρ2-Deployment. The Δρ1ρ2-Deployment is a metric for specifying minimal levels of performance from the infrastructure supporting vehicular networks. As far as we are concerned, this is the first QoS-bounded deployment strategy considering both the contact probability, and the contact...
There are several kinds of envisioned vehicular applications: video delivery, accidents detection, dissemination of traffic announcements, and so forth. Such applications demand minimal (and possibly distinct) QoS guarantees that must couple the vehicular network. Given that vehicular networks will soon become reality, we demand strategies for planning and managing such networks. In this work we propose...
This work presents a probabilistic constructive heuristic to design the roadside infrastructure for information dissemination in vehicular networks. We formulate the problem as a Probabilistic Maximum Coverage Problem (PMCP) and we use them to maximize the number of vehicles in contact with the infrastructure. We compare our approach to a non-probabilistic MCP in simulated urban areas considering...
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