Big Data Sharing

Network sharing among mobile network operators (MNOs) is gaining popularity and currently discussed for standardization in the fifth-generation (5G) networks as a means to reduce MNOs' capital and operational expenditures, improve coverage, and address spectrum shortages. Sharing is a collaborative solution to the problem of resource shortages, allowing operators to reassign resources according to the state of the network and demand for network services. In particular, the advancement of ultra-low latency applications requires sharing of real-time “contextual data” on mobile users and the RAN to meet stringent quality of service (QoS) constraints. For example, user mobility data is utilized to optimize the placement of replicated instances for ultra-low latency edge service migrations. As a result, mobile subscribers' migration time is reduced, and the quality of their subscriber experience (QoE) is improved. This contextual data must be collected from network elements by MNO by paying for sensing, computation, communication, and storage costs, and therefore data can be considered scarce network resources. To deal with these scarcity issues, we investigate the incentives behind a data sharing agreement and consider a scenario where data may be voluntarily (i.e., without payment) exchanged between an MNO and an MVNO.

The Sharing Big Data project seeks to understand the impact of the data sharing on the downstream market prices and mobile users' economic welfare. If the MNO and MVNO have the same contextual data, both operators may be able to provide users a similar QoS for edge services, leading to fierce competition between operators and reduced profits. Thus, understanding how much data should be shared to maintain a competitive nature is an important question. On the other hand, if sharing improves an operator's data quality, subscribers QoS may increase, allowing the operator to increase profits by charge higher prices for improved services. Thus, the impact of data sharing on the user's welfare and downstream edge service market is not known apriori.