Search

The arithmetic and logic unit (ALU) is a key element of complex circuits and an intrinsic part of the most widely recognized complex circuits in digital signal processing. Also, recent attention has been brought to reversible logic and quantum-dot cellular automata (QCA) because of their intrinsic capacity to decrease energy dissipation, which is a crucial need for low-power digital circuits. QCA will be the preferred technology for developing the subsequent generation of digital systems. These technologies played a substantial role in the design of the ALU for operations such as multiplication, subtraction, and division. In developing reversible logic and QCA technologies, the ALU is frequently studied as a central unit. Implementing an efficient ALU with low quantum cost and a small number of cells based on an efficient reversible block can solve all previous issues. Therefore, this research constructs a Feynman gate, a Fredkin gate, and full adder circuits using reversible logic and QCA technology. Using all of the specified circuits, a 20-operation ALU is constructed. The power consumption of the proposed ALU under various energy ranges demonstrated significant improvements over earlier designs. [ABSTRACT FROM AUTHOR]

Copyright of Frontiers of Information Technology & Electronic Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hadoop is a distributed framework for processing big data. One of the critical parts of Hadoop is YARN, which carries out scheduling and resource management. A scheduling algorithm should consider multiple objectives. However, YARN schedulers do not consider the Service Level Agreement (SLA) and the energy-related issues. The present paper proposes an energy-efficient deadline-aware model for the scheduling problem. The scheduling issue is an NP-hard problem regarding the deadline of applications and reducing energy. Hence, an Energy-efficient Deadline-aware Scheduling Algorithm based on the Moth-Flame Optimization algorithm (EDSA-MFO) is suggested to minimize the energy consumption and execute the application within a given soft deadline. Moreover, the earliest deadline first-based (EDF-based) heuristic approach is proposed to decode a moth into a scheduling solution. The algorithm is implemented for both static and dynamic scheduling. To evaluate the performance of the proposed algorithm, extensive simulations are conducted. The outcomes demonstrated that the suggested method could find near-optimal scheduling. It outperforms the YARN default FIFO scheduler, EDF, the energy-aware greedy algorithm (EAGA), and the deadline-aware energy-efficient MapReduce scheduling algorithm for YARN (EMRSAY) in total cluster energy consumption and meeting job deadline. [ABSTRACT FROM AUTHOR]