Reliable and efficient mobile edge computing in highly dynamic and volatile environments

By processing sensory data in the vicinity of its generation, edge computing reduces latency, improves responsiveness, and saves network bandwidth in data-intensive applications. However, existing edge computing solutions operate under the assumption that the edge infrastructure will comprise a set of pre-deployed, custom-configured computing devices, connected by a reliable local network. Although edge computing has great potential to provision the necessary computational resources in highly dynamic and volatile environments, including disaster recovery scenes and wilderness expeditions, extant distributed system architectures in this domain are not resilient against partial failure, caused by network disconnections. In this paper, we present a novel edge computing system architecture that delivers failure-resistant and efficient applications by dynamically adapting to handle failures; if the edge server becomes unreachable, device clusters start executing the assigned tasks by communicating P2P, until the edge server becomes reachable again. Our experimental results with the reference implementation show high responsiveness and resilience in the face of partial failure. These results indicate that the presented solution can integrate the individual capacities of mobile devices into powerful edge clouds, providing efficient and reliable services for end-users in highly dynamic and volatile environments.