An Efficient Data Scheduling Scheme for Cloud-based Big Data Framework for Smart City

Continuous increase in urban population causes enormous pressure on the limited resources of cities 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. The technological framework for smart cities services connect hundreds of data collecting device networks (e.g., sensor networks) with central server or cloud through Internet. Scheduling of these enormous data (or big data) both at the device networks and central server/cloud is significantly important to facilitate timely and priority-based smart city services. This paper introduces a cloud-based big data framework and Priority-based, Dynamic and Time sensitive data processing and Scheduling (PDTS) approach that works both for the device networks and cloud-based big data framework. Simulation results demonstrate that the proposed PDTS approach reduces the number of data transmission and data processing time as opposed to data scheduling only in cloud-based big data framework.