Optimizing the Placement of Data Collection Services on Vehicle Clusters

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.