Servers are a key element of current IT infrastructures, and must often deal with large numbers of concurrent requests. The programming language used to construct the server has an important role in engineering efficient server software, and must support massive concurrency on multicore machines with low communication and synchronisation overheads.This paper investigates 12 highly concurrent programming languages suitable for engineering servers, and analyses three representative languages in detail: Erlang, Go, and Scala with Akka. We have designed three server benchmarks that analyse key performance characteristics of the languages. The benchmark results suggest that where minimising message latency is crucial, Go and Erlang are best; that Scala with Akka is capable of supporting the largest number of dormant processes; that for servers that frequently spawn processes Erlang and Go minimise creation time; and that for constantly communicating processes Go provides the best throughput.

Modern multi-robot systems often need to solve computationally intensive tasks but operate with limited compute resources and in the presence of failures. Cooperating to share computational tasks between robots at the edge reduces execution time. We introduce and evaluate a new computation load management technology for teams of robots: Reliable Autonomous Mobile Programs (RAMPs). RAMPs use information about the computational resources available in the team and a cost model to decide where to execute. RAMPs are implemented in ROS on a collection of Raspberry Pi-based robots. The performance of RAMPs is evaluated using route planning, a typical computationally-intensive robotics application. A systematic study of RAMPs demonstrates a high likelihood of optimal or near-optimal distribution and hence efficient resource utilisation. RAMPs successfully complete in the presence of simultaneous, or successive, robot failures and network failures, while preserving near-optimal distribution.