Abstract: An order server operated by a restaurant service communicates with a restaurant server and a driver to retrieve incentive based food preparation and delivery time frames for an order. Using the time frames, the order server formulate a list of incentive based delivery plans, and provides the list to a diner device. From the diner device, the order server receives a selected incentive based delivery plan for the order from the list.

Abstract: In an approach, load balancing is performed in a distributed system of nodes representing computational resources such as clients, servers, server clusters, virtual machines, and so forth. Each node within the distributed system is responsible for processing requests associated with one or more districts in a geographical area. In order to perform load balancing each node is programmed or configured to autonomously perform a set of actions on a periodic basis which includes checking neighbors for updates, determining whether to spawning a new node, determining whether to terminate, and balancing load with neighbors. As a result, the number of nodes and the districts for which each node is responsible dynamically changes over time to minimize the load placed on each node and to constrain the number of nodes that need to be active within the distributed system to reduce resource costs.

Abstract: A customer service system operated by a restaurant service provides a restaurant service server. From a database, the restaurant service server retrieves a ticket that is generated by a restaurant service server application. The restaurant service server applies a diner credit policy to the ticket, and issues a diner credit for the diner associated with the ticket.