Machines controlled by cloud or edge resident coordinators are becoming an important trend for creating smart systems. The cloud provides a global perspective while the edge provides low latency and localized service to the machines. Coordinating these machines to work collectively to solve problems with strict timing requirements in the presence of disconnections is a challenge. Clock synchronization is necessary but not sufficient for such a system. We introduce a three-tiered hierarchical system model with the cloud at the top, devices at the leaf and fog in between. Tasks are differentiated into three categories: synchronous, asynchronous and local depending on the execution mode and requirements. We propose three scheduling algorithms; static, dynamic and batch synchronization scheduling algorithms, and evaluate the performance of the algorithms through simulations under varying operating conditions. Finally, we implement the dynamic synchronous scheduling algorithm on a polyglot programming platform for Cloud of Things to show its practicability and report initial findings.