Abstract: Transportation authorities can take early action to control flow and prevent congestion with a short-term traffic flow prediction (STP) framework. Based on historical flow data and connected vehicle (CV) features like real-time feeds and…
Abstract: Mobile device caching and cooperative device-to-device (D2D) communications can support massive content delivery over wireless networks while minimizing interference. Device clustering must be considered to realistically demonstrate how cooperative communication affects cache-enabled D2D networks….
Abstract: Online car-hailing services can better schedule drivers with accurate citywide passenger demand forecasts. Previous research either uses passenger order history or grid region partition, which loses physical context. Mobile traffic analysis has improved city…
Abstract: Novel mobile apps are created to attract users of 5G-enabled vehicular networks. Computation offloading and adaptive task scheduling in high-dynamic networks are difficult to determine. Since vehicular users are rational and selfish to maximize…
Abstract: Participatory mobile crowdsensing (MCS) requires users to repeatedly choose between two options: whether to contribute to a task and which task to contribute to. The platform coordinating MCS campaigns often engineers these choices by…
Abstract: Next-generation mobile communication networks can provide high-speed and low-latency services by deploying small cell base stations (SBS) under a macro base station (MBS) and caching popular content at the SBSs. This project examines edge…
Abstract: Mobile data collection improves energy efficiency and load distribution in wireless sensor networks (WSNs). Complex networks make path design difficult. An objective-variable tour planning (OVTP) strategy for mobile data gathering in partitioned WSNs addresses…
Abstract: Understanding point-of-interest (POI) mobility patterns improves mobile business intelligence. While many studies have attempted this, most use POI check-ins to mine mobility patterns, which is ineffective due to data sparsity. This project directly annotates…
Abstract: Nanonetworks consist of interacting nano-nodes from several hundred cubic nanometers to several cubic micrometers. Nano-nodes’ limited computational resources, energy fluctuations caused by energy harvesting processes, and transmission range at Terahertz (THz)-band frequencies (0.1-10 THz)…
Abstract: Mobile users (MUs) buy wireless data services from ISPs to access the Internet and content services (e.g., online games) from CPs. Intelligent functions like AI and 3D modeling increase the computation-intensity of content services,…
Abstract: Mobile edge computing (MEC) could bring cloud services to mobile users at the network edge. Edge clouds reduce latency, operational cost, and network resource availability. NFV, like MEC, implements network service functions as software…
Abstract: Wearable sensors enable an active learning framework for activity recognition. Our work is unique because it considers the oracle’s limitations when selecting sensor data for annotation. Humans’ limited mobile device response time inspired our…
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