Abstract
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.