Smart devices deployed across disparate communities require synchronisation in the ways which they use backend resources to ensure fairness of their provision to all users, in an ideal situation. Despite the variety of demands placed simultaneously across a network, services must be co-ordinated to avoid falling foul of the Service Level Agreements (SLA) agreed between user and service provider. Achieving this involves service brokerage, and subsequent configuration optimisation to manage the competing service demands in parallel for all stakeholders. Recognising the presence and mobility of humans in the loop is key to the design of SLAs at the front-end, and the optimised operation of technologies such as servers at the back. In this paper, we propose aspects of the design of a service orchestration engine created to fulfill competitive service needs from networked devices. This focuses on the service needs in and around a case study port ecosystem, due to the variety of service needs and the critical implications of reliable and guaranteeable operations in this ecosystem. The orchestration engine has been implemented using the Python programming language, and a port ecosystem is simulated through the modelling of device nodes, sensors, vehicles, and people. Simulation results demonstrate the resource cost of deploying a service architecture in support of informed autonomous decisions across the Internet of Things (IoT).