Optimizing the Placement of Data Collection Services on Vehicle Clusters

By 1st January 2019 No Comments
Sharma Kanika, Butler Bernard, Jennings Brendan, Kennedy John, Loomba Radhika
Optimizing the Placement of Data Collection Services on Vehicle Clusters
2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
1800–1806
Sep.
2018
Sensors;Cloud computing;Computational modeling;Bandwidth;Vehicle dynamics;Data models;Logic gates
Vehicles are an important source of data, with embedded sensors including built-in cameras. Their data can be processed close to where it was generated, using computation and network resources on collaborating vehicles. Processing at the network edge helps to reduce end-to-end service latencies. However, such mobile virtual resource pools require effective management, especially if those resources are to be leased to third-party service providers. We address the problem of service placement on moving, connected, vehicle nodes (V2V) supported by roadside infrastructure (V2I). We formulate a distributed service model and optimize the placement of services, subject to constraints related to node resource capacity, link capacity, distributed application deployment (full deployment, anti-collocation and adjacency constraint) and vehicle mobility.
10.1109/PIMRC.2018.8581027