Abstract: Mobile image recognition services are changing our lives. Most cloud/edge-based approaches have two major drawbacks: low recognition accuracy and high network bandwidth pressure, and difficulty extracting features from mobile device resources. This project proposes…
Abstract: Future small cell networks could use flying platforms like UAVs. Aerial base stations (BSs) can improve wireless network coverage, capacity, and reliability with UAVs. Self interference cancellation (SIC) techniques in full-duplex (FD) systems have…
Abstract: This project proposes a reinforcement learning approach to collision avoidance and optimal trajectory planning for unmanned aerial vehicle (UAV) communication networks. Each UAV delivers objects forward and collects data from heterogeneous ground IoT devices…
Abstract: In tactical networks, a hierarchy of queues complements each other to handle changing communication scenarios. Command and control QoS-constrained messages are in the first queue. These messages are fragmented into IP packets and stored…
Abstract: Augmented reality apps use resource-rich edge servers in mobile edge computing. Mobile users competing for limited communication and computation resources can negatively impact user experience. Task offloading’s biggest technical challenge is ensuring application QoS….
Abstract: Gesture control for ubiquitous sensing and interaction has grown with smart devices and their applications. Acoustic signals track hand movement and recognize gestures in recent work. Frequency selective fading, interference, and insufficient training data…
Abstract: We propose a pricing scheme, PRIME, for mobile Sensors-as-a-Service (mSe-aaS) in the mobile sensor-cloud (MSC) architecture to optimally distribute financial profit among MSC actors. MSC introduces the device owner, whose mobile device hosts the…
Abstract: IoT devices are growing rapidly worldwide. Distributed fog computing deployments at the network edge can provide computing resources for latency-sensitive applications in next-generation networks. The heterogeneous needs of 5G networks necessitate network function virtualization…
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…
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