The Middleware for Edge Clouds & Cloudlets (MECC) workshop aims to address the increasing need for closer integration between the different tiers on modern cloud computing platforms.

There is a growing trend of interactive and resource-intensive (e.g., compute, storage, need for big data) applications on mobile devices today, and currently many such applications are provided using resources on infrastructural clouds. However, it is challenging to provide such applications using cloud resources when there is limited connectivity. Harvesting the resources present on nearby mobile devices and/or cloudlets is a viable solution to this problem.

Today, there is also increasing demand for middleware that offers higher level abstractions without hampering expressiveness and performance. However, many distributed systems today are designed for the datacenter, and their assumptions, such as that nodes use fast wired interconnects, no longer hold in edge environments. In particular, edge clouds, such as those made up of only mobile devices at the edge, use unreliable wireless links. These unreliable links directly translate into unavailability and churn. Simultaneously, since mobile devices have limited energy resources, heavyweight distributed algorithms, such as coordination using a leader-based consensus protocol, are impractical.

As an effort to offload computation from mobile devices, cloudlets were originally envisioned as server-class hardware deployed in a neighborhood, office building or more generally, in close physical proximity to any scenario with a high density of users, such as at large public events. It is now transitioning to a more lightweight approach where the offloading is done through multiple techniques besides the use of virtual machines, as originally proposed, and where cloudlets can also offer connectivity support to crowd-sourced mobile devices, i.e., edge clouds.

With this new trend in sight, there is a need to define the services that should be offered at each tier. For example, cloudlets can provide well-defined APIs to support multiple computation offloading methods. Furthermore, new modular and reconfigurable architectures have to be proposed in order to support a variety of deployment scenarios, such as edge clouds without cloudlet support, and scenarios with very limited access to infrastructural clouds.