A polynomial-time scheduling approach to minimise idle energy consumption: An application to an industrial furnace

Control system of industrial furnace is optimized based on the aspect of the combustion. General goal of the control system is to achieve the lowest fuel with the constraints of ensuring the target control temperature of the equipment. And in different output and different fuel quantity conditions, the air-fuel rate is automatically optimized to achieve the goal of energy consumption combined with gas temperature of furnace temperature, oxygen and many parameters.

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Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Energies ◽

10.3390/en11071833 ◽

2018 ◽

Vol 11 (7) ◽

pp. 1833 ◽

Cited By ~ 40

Author(s):

Tamás Bányai

Keyword(s):

Energy Efficiency ◽

Supply Chain ◽

Energy Consumption ◽

Real Time ◽

Real Time Scheduling ◽

Improve Energy Efficiency ◽

Increase Energy Efficiency ◽

Last Mile ◽

Time Scheduling ◽

Last Mile Delivery

Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

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Real Time Scheduling for CPU and Hard Disk Requirements-Based Periodic Task with the Aim of Minimizing Energy Consumption

International Journal of Information Technology and Computer Science ◽

10.5815/ijitcs.2015.10.07 ◽

2015 ◽

Vol 7 (10) ◽

pp. 54-60

Author(s):

Vahdaneh Kiani ◽

◽

Zeynab Mohseni ◽

Amir Masoud Rahmani

Keyword(s):

Energy Consumption ◽

Real Time ◽

Hard Disk ◽

Periodic Task ◽

Real Time Scheduling ◽

Time Scheduling

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Energy-Efficient Task Partitioning for Real-Time Scheduling on Multi-Core Platforms

Computers ◽

10.3390/computers10010010 ◽

2021 ◽

Vol 10 (1) ◽

pp. 10

Author(s):

Manal A. El Sayed ◽

El Sayed M. Saad ◽

Rasha F. Aly ◽

Shahira M. Habashy

Keyword(s):

Energy Consumption ◽

Real Time ◽

Bin Packing ◽

Shared Resources ◽

Energy Aware ◽

Task Partitioning ◽

Worst Case ◽

Real Time Scheduling ◽

Static Partitioning ◽

Time Scheduling

Multi-core processors have become widespread computing engines for recent embedded real-time systems. Efficient task partitioning plays a significant role in real-time computing for achieving higher performance alongside sustaining system correctness and predictability and meeting all hard deadlines. This paper deals with the problem of energy-aware static partitioning of periodic, dependent real-time tasks on a homogenous multi-core platform. Concurrent access of the tasks to shared resources by multiple tasks running on different cores induced a higher blocking time, which increases the worst-case execution time (WCET) of tasks and can cause missing the hard deadlines, consequently resulting in system failure. The proposed blocking-aware-based partitioning (BABP) algorithm aims to reduce the overall energy consumption while avoiding deadline violations. Compared to existing partitioning strategies, the proposed technique achieves more energy-saving. A series of experiments test the capabilities of the suggested algorithm compared to popular heuristics partitioning algorithms. A comparison was made between the most used bin-packing algorithms and the proposed algorithm in terms of energy consumption and system schedulability. Experimental results demonstrate that the designed algorithm outperforms the Worst Fit Decreasing (WFD), Best Fit Decreasing (BFD), and Similarity-Based Partitioning (SBP) algorithms of bin-packing algorithms, reduces the energy consumption of the overall system, and improves schedulability.

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Towards Improving TSCH Energy Efficiency: An Analytical Approach to a Practical Implementation

Sensors ◽

10.3390/s20216047 ◽

2020 ◽

Vol 20 (21) ◽

pp. 6047

Author(s):

Marcos A. Sordi ◽

Ohara K. Rayel ◽

Guilherme L. Moritz ◽

João L. Rebelatto

Keyword(s):

Energy Consumption ◽

Ieee 802.15.4 ◽

Practical Implementation ◽

Mac Layer ◽

Medium Access ◽

Energy Consumption Model ◽

Channel Hopping ◽

Time Scheduling ◽

Energy Constrained ◽

Iot Devices

The IEEE 802.15.4-2015 standard defines a number of Medium Access Control (MAC) layer protocols for low power wireless communications, which are desirable for energy-constrained Internet of Things (IoT) devices. Originally defined in the IEEE 802.15.4e amendment, the Time Slotted Channel Hopping (TSCH) has recently been attracting attention from the research community due to its reduced contention (time scheduling) and robustness against fading (channel hopping). However, it requires a certain level of synchronization between the nodes, which can increase the energy consumption. In this work, we implement the Guard Beacon (GB) strategy, aiming at reducing the guard time usually implemented to compensate for imperfect synchronization. Moreover, besides presenting a realistic energy consumption model for a Contiki Operating System-based TSCH network, we show through analytical and practical results that, without the proposed scheme, the power consumption can be more than 13% higher.

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Polynomial time scheduling of low level computer vision algorithms on networks of heterogeneous machines

Lecture Notes in Computer Science - EURO-PAR '95 Parallel Processing ◽

10.1007/bfb0020488 ◽

1995 ◽

pp. 501-512 ◽

Cited By ~ 1

Author(s):

Adam R. Nolan ◽

Bryan Everding

Keyword(s):

Computer Vision ◽

Polynomial Time ◽

Low Level ◽

Time Scheduling

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Energy-Efficient Real-Time Scheduling Algorithm for Fault-Tolerant Autonomous Systems

Scalable Computing Practice and Experience ◽

10.12694/scpe.v19i4.1438 ◽

2018 ◽

Vol 19 (4) ◽

pp. 387-400

Author(s):

Hussein El Ghor ◽

Julia Hage ◽

Nizar Hamadeh ◽

Rafic Hage Chehade

Keyword(s):

Energy Consumption ◽

Real Time ◽

Integrated Circuit ◽

Energy Efficient ◽

Fault Tolerant ◽

Scheduling Algorithm ◽

Autonomous Systems ◽

Scheduling Algorithms ◽

Real Time Scheduling ◽

Time Scheduling

For the past decades, we have experienced an aggressive technology scaling due to the tremendous advancements of Integrated Circuit technology. As massive integration continues, the power consumption of the IC chips exponentially increases which further degraded the system reliability. This in turn poses significant challenges to the design of real-time autonomous systems. In this paper, we target the problem of designing advanced real-time scheduling algorithms that are subject to timing, energy consumption and fault-tolerant design constraints. To this end, we first investigated the problem of developing scheduling techniques for uniprocessor real-time systems that minimizes energy consumption while still tolerating up to k transient faults to preserve the system's reliability. Two scheduling algorithms are proposed: the first scheduler is an extension of an optimal fault-free energy-efficient scheduling algorithm, named ES-DVFS. The second algorithm aims to enhance the energy saving by reserving adequate slack time for recovery when faults strike. We derive a necessary and sufficient condition that must be efficiently checked for the time and energy feasibility of aperiodic jobs in the presence of failures. Later, we formally prove that the proposed algorithm is optimal for a k-fault-tolerant model. Our simulation results demonstrate that the proposed schedulers can efficiently improve energy savings when compared with previous works.

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