A5101661764- Age of Information Optimization
- IoT and Edge/Fog Computing
- Advanced Neural Network Applications
- Distributed systems and fault tolerance
- Parallel Computing and Optimization Techniques
- Advanced Data Storage Technologies
Telus (Canada)
2021
Griffith University
2002
Dunedin Public Hospital
1998
Mobile-edge computing (MEC) has been regarded as a promising paradigm to reduce service latency for data processing in the Internet of Things (IoT) by provisioning resources at network edges. In this work, we jointly optimize task partitioning and computational power allocation computation offloading dynamic environment with multiple IoT devices edge servers. We formulate problem Markov decision process constrained hybrid action space, which cannot be well handled existing deep reinforcement...
With the wave of Internet Things (IoT), a vast number IoT devices are connected to wireless networks. To better support Quality Service with constrained resources, mobile edge computing (MEC) provisions resources at network process their tasks in proximity. In this work, we investigate task partitioning and computation offloading collaborative MEC. Specifically, propose novel Deep Reinforcement Learning called Deterministic Dirichlet Policy Gradient (D3PG), which builds on partition perform...
<div> Mobile Edge Computing (MEC) has been regarded as a promising paradigm to reduce service latency for data processing in Internet of Things, by provisioning computing resources at network edge. In this work, we jointly optimize the task partitioning and computational power allocation computation offloading dynamic environment with multiple IoT devices edge servers. We formulate problem Markov decision process constrained hybrid action space, which cannot be well handled existing...
<div> Mobile Edge Computing (MEC) has been regarded as a promising paradigm to reduce service latency for data processing in Internet of Things, by provisioning computing resources at network edge. In this work, we jointly optimize the task partitioning and computational power allocation computation offloading dynamic environment with multiple IoT devices edge servers. We formulate problem Markov decision process constrained hybrid action space, which cannot be well handled existing...
<div> Mobile Edge Computing (MEC) has been regarded as a promising paradigm to reduce service latency for data processing in Internet of Things, by provisioning computing resources at network edge. In this work, we jointly optimize the task partitioning and computational power allocation computation offloading dynamic environment with multiple IoT devices edge servers. We formulate problem Markov decision process constrained hybrid action space, which cannot be well handled existing...