SmartParcels

Abstract

The emergence of IoT-aided smart communities has created the need for a new set of urban planning tools. The extra design process includes instrumenting infrastructures (sensing, networking, and computing devices) in smartspaces to generate information units (from data analytics) to realize a range of required services. In this paper, we propose SmartParcels, a framework that generates a comprehensive and cost-effective plan for instrumenting designated regions of smart communities (often called parcels). SmartParcels embeds an approach to solve the cross-layer IoT planning problem (shown to be NP-hard) that must consider applications, information/data, infrastructure, and geophysical layout as interdependent layers in the overall design. We develop a suite of algorithms (optimal, partial optimal, heuristic) for the problem; urban planners can compose these techniques in a plug-and-play manner to achieve performance trade-offs (optimality, timeliness). SmartParcels can be utilized for clean-slate planning (from scratch) or for retrofit of communities with existing smart infrastructure. We evaluate Smart-Parcels in two real-world settings: National Tsing Hua University in Taiwan and Irvine in California, USA, for clean-slate and retrofit. The evaluation results reveal that SmartParcels can enable a 2X -7X improvement in cost/performance metrics as compared to the baseline algorithm in the clean-slate and retrofit cases.