scholarly journals EE-ACML: Energy-Efficient Adiabatic CMOS/MTJ Logic for CPA-Resistant IoT Devices

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7651
Author(s):  
Zachary Kahleifeh ◽  
Himanshu Thapliyal
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Tunnel Junctions ◽  
Leakage Power ◽  
Side Channel ◽  
Clock Generator ◽  
Side Channel Attacks ◽  
Adiabatic Logic ◽  
Iot Devices

Internet of Things (IoT) devices have strict energy constraints as they often operate on a battery supply. The cryptographic operations within IoT devices consume substantial energy and are vulnerable to a class of hardware attacks known as side-channel attacks. To reduce the energy consumption and defend against side-channel attacks, we propose combining adiabatic logic and Magnetic Tunnel Junctions to form our novel Energy Efficient-Adiabatic CMOS/MTJ Logic (EE-ACML). EE-ACML is shown to be both low energy and secure when compared to existing CMOS/MTJ architectures. EE-ACML reduces dynamic energy consumption with adiabatic logic, while MTJs reduce the leakage power of a circuit. To show practical functionality and energy savings, we designed one round of PRESENT-80 with the proposed EE-ACML integrated with an adiabatic clock generator. The proposed EE-ACML-based PRESENT-80 showed energy savings of 67.24% at 25 MHz and 86.5% at 100 MHz when compared with a previously proposed CMOS/MTJ circuit. Furthermore, we performed a CPA attack on our proposed design, and the key was kept secret.

scholarly journals Energy Efficient Lighting Design Criteria: Cost-Effective Solutions in an Industrial Environment

2007 ◽  
Author(s):  
Frank J. Agraz ◽  
John Maneri
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Return On Investment ◽  
Energy Savings ◽  
Cost Effective ◽  
Lighting Design ◽  
Design Criteria ◽  
Lighting System ◽  
Light Levels

The continual rising cost of energy, existing outdated lighting technology, and inefficient lighting designs have given property owners the opportunity to improve their facilities by retrofitting their existing luminaires with an energy efficient lighting system. A lighting retrofit uses the existing electrical infrastructure to replace, relocate, or convert existing luminaires with the latest generation of cost-effective components. New lighting technology has emerged within the last 6 years that generates energy savings of 40% to 50% while maintaining existing light levels. These upgraded and field-tested solutions lower energy consumption, generate a healthy financial return on investment, and can improve both the quality and quantity of light in the task area. As with any other solution, a cost-effective lighting system must be designed and engineered carefully to accommodate the needs of each work space. Simply installing a new lamp into an existing luminaire will not necessarily guarantee substantial energy savings or an improved lighting environment. In any space that uses electric lighting, the lighting designer must evaluate potential solutions for energy consumption, maintenance concerns, delivered light levels, hostile environments, and the overall economic impact of installing and long-term operation of the new system. In this paper, the author will discuss energy efficient lighting design criteria and how a lighting designer properly engineers a retrofit project to deliver energy savings without sacrificing light levels. The discussion includes a summary of both traditional and emerging technologies, and the long-term impact on energy consumption, maintenance, return on investment, lighting quality, and delivered light levels. Paper published with permission.

Energy Efficient Schemes for Base Station Management in 4G Broadband Systems

2014 ◽  
pp. 100-120 ◽  
Author(s):  
Alexandra Bousia ◽  
Elli Kartsakli ◽  
Angelos Antonopoulos ◽  
Luis Alonso ◽  
Christos Verikoukis
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Base Station ◽  
Base Stations ◽  
Traffic Load ◽  
Network Resources ◽  
Load Variations ◽  
Mobile Cellular ◽  
Main Component

Reducing the energy consumption in wireless networks has become a significant challenge, not only because of its great impact on the global energy crisis, but also because it represents a noteworthy cost for telecommunication operators. The Base Stations (BSs), constituting the main component of wireless infrastructure and the major contributor to the energy consumption of mobile cellular networks, are usually designed and planned to serve their customers during peak times. Therefore, they are more than sufficient when the traffic load is low. In this chapter, the authors propose a number of BSs switching off algorithms as an energy efficient solution to the problem of redundancy of network resources. They demonstrate via analysis and by means of simulations that one can achieve reduction in energy consumption when one switches off the unnecessary BSs. In particular, the authors evaluate the energy that can be saved by progressively turning off BSs during the periods when traffic decreases depending on the traffic load variations and the distance between the BS and their associated User Equipments (UEs). In addition, the authors show how to optimize the energy savings of the network by calculating the most energy-efficient combination of switched off and active BSs.

scholarly journals Powertrain Optimization for Electric Buses under Optimal Energy-Efficient Driving

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6451
Author(s):  
Alexander Koch ◽  
Olaf Teichert ◽  
Svenja Kalt ◽  
Aybike Ongel ◽  
Markus Lienkamp
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Ride Comfort ◽  
Programming Approach ◽  
Automated Driving ◽  
Dynamic Programming Approach ◽  
Optimal Energy ◽  
Driving Cycles ◽  
Powertrain Configuration

State of the art powertrain optimization compares the energy consumption of different powertrain configurations based on simulations with fixed driving cycles. However, this approach might not be applicable to future vehicles, since speed advisory systems and automated driving functions offer the potential to adapt the speed profile to minimize energy consumption. This study aims to investigate the potential of powertrain optimization with respect to energy consumption under optimal energy-efficient driving for electric buses. The optimal powertrain configurations of the buses under energy-efficient driving and their respective energy consumptions are obtained using powertrain-specific optimized driving cycles and compared with those of human-driven unconnected buses and buses with non-powertrain-specific optimal speed profiles. Based on the results, new trends in the powertrain design of vehicles under energy-efficient driving are derived. The optimized driving cycles are calculated using a dynamic programming approach. The evaluations were based on the fact that the buses under energy-efficient driving operate in dedicated lanes with vehicle-to-infrastructure (V2I) communication while the unconnected buses operate in mixed traffic. The results indicate that deviating from the optimal powertrain configuration does not have a significant effect on energy consumption for optimized speed profiles; however, the energy savings from an optimized powertrain configuration can be significant when ride comfort is considered. The connected buses under energy-efficient driving operating in dedicated lanes may reduce energy consumption by up to 27% compared to human-driven unconnected buses.

scholarly journals An evolutionary scheduling approach for trading-off accuracy vs. verifiable energy in multicore processors

2017 ◽  
Vol 25 (6) ◽  
pp. 1006-1019
Author(s):  
U Liqat ◽  
Z Banković ◽  
P Lopez-Garcia ◽  
M V Hermenegildo
Keyword(s):  
Energy Consumption ◽  
Energy Budget ◽  
Energy Efficient ◽  
Energy Savings ◽  
Multicore Processors ◽  
Work Load ◽  
Control Flow ◽  
Upper And Lower Bounds ◽  
Energy Bound ◽  
Energy Efficient Scheduling

Abstract This work addresses the problem of energy-efficient scheduling and allocation of tasks in multicore environments, where the tasks can allow a certain loss in accuracy in the output, while still providing proper functionality and meeting an energy budget. This margin for accuracy loss is exploited by using computing techniques that reduce the work load, and thus can also result in significant energy savings. To this end, we use the technique of loop perforation, that transforms loops to execute only a subset of their original iterations, and integrate this technique into our existing optimization tool for energy-efficient scheduling. To verify that a schedule meets an energy budget, both safe upper and lower bounds on the energy consumption of the tasks involved are needed. For this reason, we use a parametric approach to estimate safe (and tight) energy bounds that are practical for energy verification (and optimization applications). This approach consists in dividing a program into basic (‘branchless’) blocks, establishing the maximal (resp. minimal) energy consumption for each block using an evolutionary algorithm, and combining the obtained values according to the program control flow, by using static analysis to produce energy bound functions on input data sizes. The scheduling tool uses evolutionary algorithms coupled with the energy bound functions for estimating the energy consumption of different schedules. The experiments with our prototype implementation were performed on multicore XMOS chips, but our approach can be adapted to any multicore environment with minor changes. The experimental results show that our new scheduler enhanced with loop perforation improves on the previous one, achieving significant energy savings (31% on average for the test programs) for acceptable levels of accuracy loss.

scholarly journals A Simulation Approach for Optimising Energy-Efficient Driving Speed Profiles in Metro Lines

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6038
Author(s):  
Mariano Gallo ◽  
Marilisa Botte ◽  
Antonio Ruggiero ◽  
Luca D’Acierno
Keyword(s):  
Energy Consumption ◽  
Simulation Model ◽  
Travel Time ◽  
Energy Efficient ◽  
Energy Savings ◽  
Simulation Software ◽  
Gradient Algorithm ◽  
Simulation Approach ◽  
Driving Speed ◽  
Optimisation Model

We propose a model for optimising driving speed profiles on metro lines to reduce traction energy consumption. The model optimises the cruising speed to be maintained on each section between two stations; the functions that link the cruising speed to the travel time on the section and the corresponding energy consumption are built using microscopic railway simulation software. In addition to formulating an optimisation model and its resolution through a gradient algorithm, the problem is also solved by using a simulation model and the corresponding optimisation module, with which stochastic factors may be included in the problem. The results are promising and show that traction energy savings of over 25% compared to non-optimised operations may be achieved.

scholarly journals Energy-Efficient Clusters for Object Tracking Networks

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2015 ◽  
Author(s):  
Yang-Hsin Fan
Keyword(s):  
Energy Consumption ◽  
Object Tracking ◽  
Energy Efficient ◽  
Energy Savings ◽  
Smart Cities ◽  
Tracking System ◽  
Cluster Structure ◽  
Equivalent Model ◽  
Save Energy ◽  
Tracking Devices

Smart cities have hundreds of thousands of devices for tracking data on crime, the environment, and traffic (such as data collected at crossroads and on streets). This results in higher energy usage, as they are recording information persistently and simultaneously. Moreover, a single object tracking device, on a corner at an intersection for example has a limited scope of view, so more object tracking devices are added to broaden the view. As an increasing number of object tracking devices are constructed on streets, their efficient energy consumption becomes a significant issue. This work is concerned with decreasing the energy required to power these systems, and proposes energy-efficient clusters (EECs) of object tracking systems to achieve energy savings. First, we analyze a current object tracking system to establish an equivalent model. Second, we arrange the object tracking system in a cluster structure, which facilitates the evaluation of energy costs. Third, the energy consumption is assessed as either dynamic or static, which is a more accurate system for determining energy consumption. Fourth, we analyze all possible scenarios of the object’s location and the resulting energy consumption, and derive a number of formulas for the fast computation of energy consumption. Finally, the simulation results are reported. These results show the proposed EEC is an effective way to save energy, compared with the energy consumption benchmarks of current technology.

Near-Threshold Flip-Flops Using Clocked Adiabatic Logic in Nanometer CMOS Processes

2011 ◽  
Vol 460-461 ◽  
pp. 837-842 ◽  
Author(s):  
Hai Yan Ni ◽  
Jian Ping Hu
Keyword(s):  
Single Phase ◽  
Energy Savings ◽  
Logic Circuits ◽  
Sequential Circuits ◽  
Clock Generator ◽  
Nanometer Cmos ◽  
Wide Range ◽  
Adiabatic Logic ◽  
Auxiliary Signal ◽  
Near Threshold

This paper presents adiabatic flip-flops operating on near-threshold supply voltages. The near-threshold adiabatic flip-flops and sequential circuits are realized with improved CAL (Clocked Adiabatic Logic) circuits using a single-phase power clock. An auxiliary clock generator is used to obtain the non-overlap sinusoidal auxiliary signal pair. A near-threshold mode-10 counter is implemented. All circuits are simulated using Predictive Technology Model (PTM) 45nm process. The near-threshold adiabatic circuits attain large energy savings over a wide range of frequencies, as compared with conventional static CMOS logic circuits.

scholarly journals Variety of Scalable Shuffling Countermeasures against Side Channel Attacks

2016 ◽  
Author(s):  
Nikita Veshchikov ◽  
Stephane Fernandes Medeiros ◽  
Liran Lerman
Keyword(s):  
Block Cipher ◽  
Fixed Number ◽  
Side Channel ◽  
Small Data ◽  
Side Channel Attacks ◽  
Side Channel Analysis ◽  
Cryptographic System ◽  
Channel Analysis ◽  
Iot Devices ◽  
Time Overhead

IoT devices have very strong requirements on all the resources such as memory, randomness, energy and execution time. This paper proposes a number of scalable shuffling techniques as countermeasures against side channel analysis. Some extensions of an existing technique called Random Start Index (RSI) are suggested in this paper. Moreover, two new shuffling techniques Reverse Shuffle (RS) and Sweep Swap Shuffle (SSS) are described within their possible extensions. Extensions of RSI, RS and SSS might be implemented in a constrained environment with a small data and time overhead. Each of them might be implemented using different amount of randomness and thus, might be fine-tuned according to requirements and constraints of a cryptographic system such as time, memory, available number of random bits, etc. RSI, RS, SSS and their extensions are described using SubBytes operation of AES-128 block cipher as an example, but they might be used with different operations of AES as well as with other algorithms. This paper also analyses RSI, RS and SSS by comparing their properties such as number of total permutations that might be generated using a fixed number of random bits, data complexity, time overhead and evaluates their resistance against some known side-channel attacks such as correlation power analysis and template attack. Several of proposed shuffling schemes are implemented on a 8-bit microcontroller that uses them to shuffle the first and the last rounds of AES-128.  

scholarly journals Energy-aware strategy for data forwarding in IoT ecosystem

2020 ◽  
Vol 10 (5) ◽  
pp. 4863 ◽  
Author(s):  
K. Nagarathna
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Selection Process ◽  
Path Selection ◽  
Destination Node ◽  
Data Forwarding ◽  
Energy Aware ◽  
Energy Efficient Routing ◽  
Research Attention ◽  
Iot Devices

The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay.

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