Sun Mao

TL;DR: This paper investigates the fundamental tradeoff between Energy Efficiency (EE) and delay in a multi-user wireless powered MEC system and proposes the online computation offloading and resource allocation algorithm based on Lyapunov optimization theory.

TL;DR: A novel solution to jointly optimize the allocation of the communication, computing and energy resources in IoT, with the aid of some advanced wireless communication technologies including Wireless Energy Transfer, Mobile-Edge Computing and Full-Duplex is provided.

TL;DR: A consortium blockchain-based resource sharing paradigm in IoV is proposed, in which the resource sharing interactions are encapsulated as transactions and recorded by Road Side Units (RSUs) and a lightweight consensus mechanism named as Proof-of-Reputation is proposed to reduce computational power consumption and motivate vehicles involved in resource sharing.

TL;DR: An iterative algorithm is developed, in which the Dinkelbach-type method and block coordinate descent technique are utilized to tackle the fractional objective function and coupled optimization variables, respectively, and the closed-form expression for local computing frequencies optimization subproblem is derived.

TL;DR: This paper focuses on the energy-efficient resource allocation of a cognitive multiple-input single-output NOMA system with the aid of simultaneous wireless information and power transfer and proposes a penalty function-based algorithm to solve the non-convex problem.