Browsing by Keyword "Vehicular networks"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Cost-efficient selective network caching in large-area vehicular networks using multi-objective heuristics(Springer Verlag, 2017) Bilbao, Miren Nekane; Perfecto, Cristina; Del Ser, Javier; Del Ser, Javier; IAIn the last decade the interest around network caching techniques has augmented notably for alleviating the ever-growing demand of resources by end users in mobile networks. This gained momentum stems from the fact that even though the overall volume of traffic retrieved from Internet has increased at an exponential pace over the last years, several studies have unveiled that a large fraction of this traffic is usually accessed by multiple end users at nearby locations, i.e. content demands are often local and redundant across terminals close to each other, even in mobility. In this context this manuscript explores the application of multi-objective heuristics to optimally allocate cache profiles over urban scenarios with mobile receivers (e.g. vehicles). To this end we formulate two conflicting objectives: the utility of the cache allocation strategy, which roughly depends on the traffic offloaded from the network and the number of users demanding contents; and its cost, given by an cost per unit of stored data and the rate demanded by the cached profile. Simulations are performed and discussed over a realistic vehicular scenario modeled over the city of Cologne (Germany), from which it is concluded that the proposed heuristic solver excels at finding caching solutions differently balancing the aforementioned objectives.Item Wireless network optimization for massive V2I data collection using multiobjective harmony search heuristics(Springer Verlag, 2017) Sobron, Iker; Alonso, Borja; Vélez, Manuel; Del Ser, Javier; Del Ser, Javier; IAThis paper proposes to improve the efficiency of the deployment of wireless network infrastructure for massive data collection from vehicles over regional areas. The increase in the devices that are carried by vehicles makes it especially interesting being able to gain access to that data. From a decisional point of view, this collection strategy requires defining a wireless Vehicular-to-Infrastructure (V2I) network that jointly optimizes the level of service and overall CAPEX/OPEX costs of its deployment. Unfortunately, it can be intuitively noted that both optimization objectives are connecting with one another: adding more equipment will certainly increase the level of service (i.e. coverage) of the network, but costs of the deployment will rise accordingly. A decision making tool blending together both objectives and inferring therefrom a set of Pareto-optimal deployments would be of utmost utility for stakeholders in their process of provisioning budgetary resources for the deployment. This work will explore the extent to which a multi-objective Harmony Search algorithm can be used to compute the aforementioned Pareto-optimal set of deployment by operating on two different optimization variables: the geographical position on which wireless receivers are to be deployed and their type, which determines not only their coverage range but also their bandwidth and cost. In particular we will utilize a non-dominated sorting strategy criterion to select the harmonies (solution vectors) evolved by Harmony Search heuristics.