adio conditions, a solution based on cooperative information reporting and route-specific predictions is being con- sidered. It utilizes the concept of radio measurement information partitioning in the MEC based on routes to obtain journey-specific QoS predictions. 6.4.2 Market Drivers Most of the work on latency reduction (in research, standardization, and implementation) SO far has been focused on air interface improvements, while the "end-to-end" (E2E) aspect has often been overlooked. Although air interface latency reduction is very important, 6.4 Multi-Access Edge Computing improving true system-level performance is only possible with the introduction of edge computing, as the application level communication endpoint is on the edge, thus providing benefits for all services requiring extremely low latencies, e.g. AR, virtual reality (VR), industry 4.0, etc. MEC is commonly recognized as the main way to ensure E2E low latency in communication systems. However, latency is not the only key performance indicator (KPI) targeted by MEC. Client application offloading (i.e. from UE to MEC) is another example where moving processing load from a UE to the edge can potentially increase battery life at the terminal side. While such a scenario, which is unrealistic with cloud deployments, becomes possible with MEC, it comes at the cost of increased complexity and latency. From a deployment point of view, MEC provides an opportunity for operators and infras- tructure owners to expand their business and offer edge hosting services to application vendors and cloud service providers, thus opening up new markets and business models. Most of these stakeholders in fact recognize that the 5G market will not only bring value due to enhanced connectivity and network performance, but also will provide some suit- able means to offer new revenue streams. According to some estimations (Ericsson5G), edge computing is opening up 25% of the total 5G market potential. From a market perspective, vertical market stakeholders (e.g. from the a