Notice of Violation of IEEE Publication Principles: Adaptive Energy Management in Mobile Devices Using Heterogeneous Energy Storage Units

Notice of Violation of IEEE Publication Principles

"Adaptive Energy Management in Mobile Devices Using Heterogeneous Energy Storage Units"
by S. M. Ikram, S. M. Abis Naqvi, Zhirong Shen, and Guanglin Zhang
in 2018 IEEE 19th International Conference on Communication Technology (ICCT), October 2018, pp. 973-977

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

This paper copied portions of text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

"Real-time operation of heterogeneous energy storage units"
by Sarthak Gupta and Vassilis Kekatos
in 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP), December 2016, pp.916-920


Energy storage unit is an imminent component for the long-lasting role of a smart mobile device (MD) to serve applications. Energy storage systems possess distinctive features regarding charging, discharging rates and capacities response times at different timescales. To this end, we consider mobile devices are operating on slow-and fast-responding energy storage units. Slow batteries are charged on an hourly basis at the same time decisions are consistent over multiple fast time slots, and fast batteries are operated by renewable energy resource, i.e., solar energy. The battery pair of each MD is charged using Lyapunov optimization scheme having quantifiable sub-optimality bounds. An energy optimization problem is formulated with the stability of batteries energy levels and application queues as constraints. We design an algorithm using Lyapunov optimization approach, introducing energy storage and quality-of-service (QoSE) virtual queues to assure system stability. We use trace-driven simulations to demonstrate the efficiency of the proposed energy algorithm.