| Title | Random motion nodes empowering opportunistic networks for smart cities |
|---|---|
| ID_Doc | 42635 |
| Authors | Corrente, G |
| Title | Random motion nodes empowering opportunistic networks for smart cities |
| Year | 2020 |
| Published | |
| Abstract | In this article we present an example of opportunistic networking system of communication for gathering and spreading information inside an urban area, trying to overcome obstacles to network efficacy. In this paper we consider a set of few terminals, not ever of the same type, in a smart city fractioned in zones that are interested in collecting the information originated from environment but possibly also other several sources by sensors, reading tags or communications. This set includes mobile nodes, two differently equipped type of them, pedestrian and vehicles, and fixed terminals. Also we aim to consider other nodes, for example also nodes with a completely random series of movements, regardless of their usefulness or natural real possibility. In particular, each terminal aims to retrieve the data items or environmental information in a limited region of interest (ROI). This is centred around the node position itself. The environment is supposed to be dynamic: data items may change over time. So all nodes must strive for updating or obtaining the latest data version. The objective of the paper is to evaluate the percentage of information each node gathers with policies based on a simple distributed data gathering and sharing through local broadcast communications. We study the diffusion of data items and information updates in the whole area, experimenting in different conditions the influence of adding to the scenario random motion of nodes. Some reflections are made so as that similar results may be obtained adding Unmanned Aerial Vehicles to a real urban scenario. The study we present in this paper has been done using computer simulation. We wrote a discrete event simulator working on the base of mobility and radio propagation traces obtained from the UDelModels tools. (C) 2020 Elsevier B.V. All rights reserved. |
Similar Articles
| ID | Score | Article |
|---|---|---|
37567
|
Almeida, R; Oliveira, R; Luís, M; Senna, C; Sargento, S Forwarding Strategies for Future Mobile Smart City Networks(2018) | |
| 36694
|
Bonola, M; Bracciale, L; Loreti, P; Amici, R; Rabuffi, A; Bianchi, G Opportunistic communication in smart city: Experimental insight with small-scale taxi fleets as data carriers(2016) | |
| 41529
|
Morelli, A; Stefanelli, C; Tortonesi, M; Suni, N Mobility Pattern Prediction to Support Opportunistic Networking in Smart Cities(2013) | |
| 41553
|
Amah, TE; Kamat, M; Abu Bakar, K; Moreira, W; Oliveira, A; Batista, MA Preparing opportunistic networks for smart cities: Collecting sensed data with minimal knowledge(2020) | |
| 38620
|
Naseer, S; Liu, W; Sarkar, NI; Shafiq, M; Choi, JG Smart City Taxi Trajectory Coverage and Capacity Evaluation Model for Vehicular Sensor Networks(2021)Sustainability, 13, 19 |