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Zheng Chang

Researcher at University of Jyväskylä

Publications -  150
Citations -  3532

Zheng Chang is an academic researcher from University of Jyväskylä. The author has contributed to research in topics: Resource allocation & Efficient energy use. The author has an hindex of 28, co-authored 137 publications receiving 2574 citations. Previous affiliations of Zheng Chang include Information Technology University & Xidian University.

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Journal ArticleDOI

Multiobjective Optimization for Computation Offloading in Fog Computing

TL;DR: In this article, the authors utilized queuing theory to bring a thorough study on the energy consumption, execution delay, and payment cost of offloading processes in a fog computing system, where three queuing models were applied, respectively, to the MD, fog, and cloud centers, and the data rate and power consumption of the wireless link were explicitly considered.
Proceedings ArticleDOI

IEEE 802.11ac: Enhancements for very high throughput WLANs

TL;DR: This paper introduces the key mandatory and optional PHY features, as well as the MAC enhancements of 802.11ac over the existing802.11n standard in the evolution towards higher data rates, and demonstrates that hybrid A-MSDU/A-MPDU aggregation yields the best performance for both 802.
Journal ArticleDOI

Learn to Cache: Machine Learning for Network Edge Caching in the Big Data Era

TL;DR: Big data analytics to advance edge caching capability is proposed, which is considered as a promising approach to improve network efficiency and alleviate the high demand for the radio resource in future networks.
Journal ArticleDOI

Energy-Efficient Edge Computing Service Provisioning for Vehicular Networks: A Consensus ADMM Approach

TL;DR: This paper studies the energy-efficient workload offloading problem and proposes a low-complexity distributed solution based on consensus alternating direction method of multipliers, which is validated based on a realistic road topology of Beijing, China.
Journal ArticleDOI

Joint Radio and Computational Resource Allocation in IoT Fog Computing

TL;DR: This work investigates a joint radio and computational resource allocation problem to optimize the system performance and improve user satisfaction, and proposes to use a matching game framework, in particular, student project allocation (SPA) game, to provide a distributed solution for the formulated joint resource allocationproblem.