The Continuous increase in urban population causes enormous pressure on cities’ limited resources, including transport, energy, water, housing, public services, and others. Hence, the need to plan and develop smart cities based solutions for enhanced urban governance is becoming more evident. These solutions are motivated by innovations in Information and Communication Technology to support smart planning for the city and to facilitate enhanced services to its citizens. Important areas where smart city services can be offered include urban planning, transport planning, energy conservation, water management, waste management, environmental monitoring, public safety, healthcare, education, entertainment, and many other services. Hence, the enormous data collected from different networks and applications to facilitate the offering of smart city services requires efficient data scheduling, aggregation, and processing to ensure service quality (QoS). However, existing data scheduling approaches consider scheduling and processing data only in the cloud, while processing also in the data collecting devices is significantly essential. This paper first introduces the multi-layer network architecture comprising sensor/device networks and cloud. The paper then introduces a Multi-layer, Priority-based, Dynamic, and Time-sensitive data processing and Scheduling approach (MPDTS) in the proposed multi-layer networks. Simulation results show that the proposed MPDTS approach achieves lower latency and data processing time than existing traditional data scheduling approaches that work only in the cloud layer.

城市人口的持续增加给城市有限的资源，包括运输，能源，水，住房，公共服务等带来巨大压力。因此，规划和开发基于智能城市的解决方案以增强城市治理的需求变得越来越明显。这些解决方案受到信息和通信技术创新的推动，以支持该城市的明智规划并促进为其市民提供更好的服务。可提供智慧城市服务的重要领域包括城市规划，交通规划，节能，水管理，废物管理，环境监测，公共安全，医疗保健，教育，娱乐和许多其他服务。因此，为了从不同的网络和应用程序中收集大量数据以促进提供智慧城市服务，需要进行有效的数据调度，聚合和处理以确保服务质量（QoS）。但是，现有的数据调度方法仅考虑在云中调度和处理数据，而在数据收集设备中进行处理也非常重要。本文首先介绍了包含传感器/设备网络和云的多层网络体系结构。然后，本文在提出的多层网络中介绍了一种基于优先级的多层动态和时间敏感数据处理和调度方法（MPDTS）。