Sacrificing Energy Efficiency Research Articles

Accelerating urbanization serves to reduce income inequality without sacrificing energy efficiency – Evidence from the 78 countries

Income inequality refers to the uneven distribution of wealth among population, amongst the discussion it has generated, the issue of equality-based efficiency has become a development goal pursued by many countries. In order to better understand the relationship between income inequality and energy efficiency, the static threshold effect approach and the dynamic threshold effect approach were applied in this article based on panel data of 78 countries. In these approaches, income inequality is the explanatory variable, urbanization and industrialization are the threshold variables, while energy efficiency is the explained variable. The results show that there is a positive coefficient between income inequality and energy efficiency, and the coefficient of this positive relationship decreases when urbanization level rises above the two thresholds 42.68% and 93.16% respectively, and so does it when industrialization level rises above 12.76% and 19.12%. In addition, urbanization plays a greater role than industrialization in reducing the correlation between income inequality and energy efficiency. Therefore, accelerating industrialization, especially urbanization, can serve to reduce income inequality without sacrificing energy efficiency.

Secure and Energy-Efficient Network Topology Obfuscation for Software-Defined WSNs

Network topology obfuscation (NTO) is generally considered as a promising proactive mechanism to mitigate traffic analysis attacks. The main challenge is to strike a balance among energy consumption, reliable routing, and security levels due to resource constraints in sensor nodes. Furthermore, software-defined wireless sensor networks (WSNs) are more vulnerable to traffic analysis attacks due to the uncovered pattern of control traffic between the controller and the nodes. In this article, a new energy-aware NTO mechanism is proposed, which maximizes the attack costs and is efficient and practical to be deployed. Specifically, first, a route obfuscation method is proposed by utilizing ranking-based route mutation, based on four different critical criteria: 1) route overlapping; 2) energy consumption; 3) link costs; and 4) node reliability. Then, a sink node obfuscation method is introduced by selecting several fake sink nodes that are indistinguishable from actual sink nodes, according to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -anonymity model. As a result, the most suitable routes and sink nodes can be selected, and a highest obfuscation level can be reached without sacrificing energy efficiency. Finally, extensive simulation results demonstrate that the proposed methods can strongly mitigate traffic analysis attacks and achieve effective NTO for software-defined WSNs. In addition, the proposed methods can reduce the success rate of the attacks while achieving lower energy consumption and higher network lifetime.

High performance accelerators for deep neural networks: A review

AbstractThe availability of huge structured and unstructured data, advanced highly dense memory and high performance computing machines have provided a strong push for the development in artificial intelligence (AI) and machine learning (ML) domains. AI and machine learning has rekindled the hope of efficiently solving complex problems which was not possible in the recent past. The generation and availability of big‐data is a strong driving force for the development of AI/ML applications, however, several challenges need to be addressed, like processing speed, memory requirement, high bandwidth, low latency memory access, and highly conductive and flexible connections between processing units and memory blocks. The conventional computing platforms are unable to address these issues with machine learning and AI. Deep neural networks (DNNs) are widely employed for machine learning and AI applications, like speech recognition, computer vison, robotics, and so forth, efficiently and accurately. However, accuracy is achieved at the cost of high computational complexity, sacrificing energy efficiency and throughput like performance measuring parameters along with high latency. To address the problems of latency, energy efficiency, complexity, power consumption, and so forth, a lot of state of the art DNN accelerators have been designed and implemented in the form of application specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs). This work provides the state of the art of all these DNN accelerators which have been developed recently. Various DNN architectures, their computing units, emerging technologies used in improving the performance of DNN accelerators will be discussed. Finally, we will try to explore the scope for further improvement in these accelerator designs, various opportunities and challenges for the future research.

A CFD analysis on using a standardized blade in different mechanical draft cooling towers for geothermal power plants

The spare parts standardization without excessively sacrificing energy efficiency may reduce the maintenance costs of components in different geothermal power plants of the same company.This strategy may apply to the blades of the fan used in mechanical draft cooling towers, which usually come in different sizes and are numerous.The case study taken as a reference is a standardized blade, designed for a fan diameter of 8.6 m, used in a 9.2 m diameter fan.The results indicated a decrease in efficiency for the fan with standard blades. Nevertheless, some appendices proved to be effective in limiting the efficiency loss.

A Tilting-Rotor Unmanned Aerial Vehicle for Enhanced Aerial Locomotion and Manipulation Capabilities: Design, Control, and Applications

In this article, a novel multirotor unmanned aerial vehicle (UAV) is proposed for enhanced locomotion and manipulation in unstructured environments. The vehicle has a tilting-rotor architecture. Specifically, two pairs of rotors are mounted on two independently controlled tilting arms placed at two sides of the vehicle, forming an “H” configuration. Such a structure endows the vehicle with more degrees of freedom, improving the maneuverability without sacrificing energy efficiency at the cost of only two additional servos compared to traditional quadcopters. Based on this architecture, a dual-level adaptive robust control is developed to cope with inertial parametric uncertainties and uncertain nonlinearities for accurate motion tracking. To resolve the redundancy in actuation, a thrust force optimization problem minimizing power consumption while achieving the desired body force wrench is formulated and solved precisely and efficiently. With the novel design and control, the proposed aerial vehicle is capable of achieving superior maneuverability, better stability and motion accuracy in the presence of uncertainties, as well as improved power efficiency compared to traditional UAVs when performing dexterous aerial locomotion and manipulation. To demonstrate the advantage of the proposed new UAV design and control in real applications, we conduct four challenging experiments on aerial locomotion and manipulation: circular trajectory tracking, passing through a narrow tunnel, picking up an object from a cluttered shelf, and aerial hole drilling. Experimental results validate the applicability of the proposed innovation.

Maximizing throughput for low duty-cycled sensor networks

Sensing and communication are foundations of the Internet of Things(IoT). Although energy efficiency is an important issue in MAC protocol design for general energy limited sensor networks, throughput is non trivial for some specific sensor networks. In this paper, we propose a new duty cycling scheme called MaxPut that can maximize throughput without sacrificing energy efficiency through the appropriate combination of random and scheduled duty cycling schemes. MaxPut attempts to identify risky nodes and enables risky nodes to maximize the utilization of active periods of their neighbors such that MaxPut can avoid potential buffer overflow due to aggregation of bursty data. We obtain overall throughput in networks with homogeneous and heterogeneous event occurrence processes respectively. Further, we compare MaxPut against a fully random duty cycling scheme. The simulation results show that MaxPut outperforms prior work with respect to the network throughput, while energy consumption is almost equivalent to the existing duty cycling scheme.

A compact skyrmionic leaky-integrate-fire spiking neuron device.

Neuromorphic computing, which relies on a combination of a large number of neurons massively interconnected by an even larger number of synapses, has been actively studied for its characteristics such as energy efficiency, intelligence, and adaptability. To date, while the development of artificial synapses has shown great progress with the introduction of emerging nanoelectronic devices, e.g., memristive devices, the implementation of artificial neurons, however, depends mostly on semiconductor-based circuits via integrating many transistors, sacrificing energy efficiency and integration density. Here, we present a novel compact neuron device that exploits the current-driven magnetic skyrmion dynamics in a wedge-shaped nanotrack. Under the coaction of the exciting current pulse and the repulsive force exerted by the nanotrack edges, the dynamic behavior of the proposed skyrmionic artificial neuron device is in analogy to the leaky-integrate-fire (LIF) spiking function of a biological neuron. The tunable temporary location of the skyrmion in our artificial neuron behaves like the analog membrane potential of a biological neuron. The neuronal dynamics and the related physical interpretations of the proposed skyrmionic neuron device are carefully investigated via micromagnetic and theoretical methods. Such a compact artificial neuron enables energy-efficient and high-density implementation of neuromorphic computing hardware.

Leveraging Power-Performance Relationship of Energy-Efficient Modern DRAM Devices

Computer servers are equipped with an increasing number of memory modules each with more capacity, making main-memory systems now the second most energy-consuming component trailing only processors in big-memory servers. These big-memory servers and their main-memory systems should offer high energy efficiency. In pursuit of energy-efficient main-memory systems, prior work exploited mobile low power double data rate (LPDDR) devices' advantages (lower power than DDR devices) while attempting to surmount their limitations (longer latency, lower bandwidth, or both). However, we show that such main-memory architectures (based on the latest LPDDR4 devices) are no longer effective and even hurt overall energy efficiency of servers by 49% on memory-intensive workloads compared with ones based on DDR4 devices. The reason is that the power consumption of modern DDR4 devices has substantially reduced by adopting the strength of mobile and graphics memory whereas LPDDR4 has focused more on increasing data transfer rates while sacrificing energy efficiency; the power consumption of DDR4 devices can significantly vary across manufacturers in this analysis. Moreover, exploring new energy-saving features of DDR4 devices in depth, we show that activating these features often hurts overall energy efficiency of servers because of their performance penalties. Subsequently, we propose a simple but effective scheme that adaptively exploits DRAM power-down modes and hence improves the system energy-delay product by 4.0%.

Context-Aware Broadcast in Duty-Cycled Wireless Sensor Networks

As the energy efficiency remains a key issue in wireless sensor networks, duty-cycled mechanisms acquired much interest due to their ability to reduce energy consumption by allowing sensor nodes to switch to the sleeping state whenever possible. The challenging task is to authorize a sensor node to adopt a duty-cycle mode without inflicting any negative impact on the performance of the network. A context-aware paradigm allows sensors to adapt their functional behavior according to the context in order to enhance network performances. In this context, the authors propose an enhanced version the Efficient Context-Aware Multi-hop Broadcasting (E-ECAB) protocol, which combines the advantages of context awareness by considering a multi criteria and duty-cycle technique in order to optimize resources usage and satisfy the application requirements. Simulation results show that E-ECAB achieves a significant improvement in term of throughput and end-to-end delay without sacrificing energy efficiency.

Optimization of power density and metal-to-adsorbent weight ratio in coated adsorbers for adsorptive heat transformation applications

Heat transformation systems such as gas adsorption heat pumps will be one cornerstone in reducing the carbon footprint of the building sector. Their development calls for an increase in power density without sacrificing energy efficiency. For the adsorber component this translates to small ratio of heat exchanger to adsorbent mass. Possibilities to achieve this have been investigated on small scale samples as well as on full scale adsorbers. Different samples and adsorbers with varying adsorbent to metal ratios where produced and characterized using the large pressure jump and large temperature jump method. Under certain conditions it could be shown that in small scale and full scale the power can be kept on a high level while increasing the adsorbent to metal ratio. Here the heat and mass transfer in the coating layer is not limiting the adsorber power.

Performance evaluation of a combined variable refrigerant volume and cool thermal energy storage system for air conditioning applications

In recent years, the growing needs for fulfilling the comfort cooling requirements with efficient refrigerating and air conditioning systems have gained impetus. In this work, the performance of a combined variable refrigerant volume (VRV) and cool thermal energy storage (CTES) air conditioning (A/C) system was experimentally investigated for summer and winter design conditions. Experimental results suggest that the VRV-CTES A/C system (combined A/C system) precisely maintained the indoor temperature at 24 °C for year-round operational conditions. The PCM being applied has exhibited good latent heat capacity (~160.81 kJ kg−1) with congruent phase transition characteristics (~9.92 °C), even after 1000 repeated thermal cycles. Furthermore, the reduced cooling capacities and reduced combined power consumption were attributed to the improved performance of the combined A/C system. In total, this system would be beneficial in terms of accomplishing comfort cooling needs for conditioning applications without sacrificing energy efficiency.

27-3:Invited Paper: Quantum Rod Containing Film Development for Display Applications

Quantum materials have advantages for display application1,2), such as narrow emission spectra and ability of color tuning by their sizes. Narrow emission spectra lead to expanding color gamut and color tuning leads to wide color gamut without sacrificing energy efficiency. We have developed quantum rod (Q-Rod) containing films for (1) Liquid Crystal Display Device (LCD) backlight application and (2) Color Filter (CF) application. For the LCD backlight application, small reabsorption of the green light by the red material is important, and for the color filter application photo-patternable film is necessary. In this paper, the effect of re-absorption is estimated for the LCD backlight application and fabricated fine photopatterns are shown for CF application. The out-coupling efficiency difference between quantum dot (Q-Dot) and Q-Rrod is also estimated using dipole moment emission model. It has been shown that the dipole moment emission (Q-Rod) gives twice as large out-coupling efficiency as the spherical wave propagation (Q-Dot).

Self organising cloud cells: a resource efficient network densification strategy

AbstractNetwork densification is envisioned as the key enabler for 2020 vision that requires cellular systems to grow in capacity by hundreds of times to cope with unprecedented traffic growth trends being witnessed since advent of broadband on the move. However, increased energy consumption and complex mobility management associated with network densifications remain as the two main challenges to be addressed before further network densification can be exploited on a wide scale. In the wake of these challenges, this paper proposes and evaluates a novel dense network deployment strategy for increasing the capacity of future cellular systems without sacrificing energy efficiency and compromising mobility performance. Our deployment architecture consists of smart small cells, called cloud nodes, which provide data coverage to individual users on a demand bases while taking into account the spatial and temporal dynamics of user mobility and traffic. The decision to activate the cloud nodes, such that certain performance objectives at system level are targeted, is carried out by the overlaying macrocell based on a fuzzy‐logic framework. We also compare the proposed architecture with conventional macrocell only deployment and pure microcell‐based dense deployment in terms of blocking probability, handover probability and energy efficiency and discuss and quantify the trade‐offs therein.© 2014 The Authors. Transactions on Emerging Telecommunications Technologies published by John Wiley &amp; Sons, Ltd.

SW-MAC: A Low-Latency MAC Protocol with Adaptive Sleeping for Wireless Sensor Networks

A low duty-cycle operation medium access control (MAC) protocol is very important to conserve energy for resource-constrained wireless sensor networks. Traditional sleep-wake scheduling mechanisms of MAC protocols either require periodic synchronization beacons or bring high end-to-end delivery latency due to the lack of any synchronization. In this paper, we propose a low latency MAC protocol by adjusting the sleep window (SW-MAC) considering traffic patterns. Nodes in SW-MAC transmit a sequence of scout packets to wake up the next hop and estimate the traffic arrival time from upstream nodes to sleep adaptively. For the large variance traffic, we adjust the sleep window using additive increase/multiplicative decrease mechanism. And then we design a scout-based scheduling mechanism with the above algorithms to shorten the delivery latency. Simulation results indicate that SW-MAC could significantly reduce the end-to-end packet delivery latency without sacrificing energy efficiency.

Power Control and Coding Formulation for State Estimation With Wireless Sensors

Technological advances have made wireless sensors cheap and reliable enough to be brought into industrial use. A major challenge arises from the fact that wireless channels introduce random packet dropouts. Power control and coding are key enabling technologies in wireless communications to ensure efficient communications. In the present work, we examine the role of power control and coding for Kalman filtering over wireless correlated channels. Two estimation architectures are considered: In the first, the sensors send their measurements directly to a single gateway. In the second scheme, wireless relay nodes provide additional links. The gateway decides on the coding scheme and the transmitter power levels of the wireless nodes. The decision process is carried out on-line and adapts to varying channel conditions in order to improve the trade-off between state estimation accuracy and energy expenditure. In combination with predictive power control, we investigate the use of multiple-description coding, zero-error coding and network coding and provide sufficient conditions for the expectation of the estimation error covariance matrix to be bounded. Numerical results suggest that the proposed method may lead to energy savings of around 50 %, when compared to an alternative scheme, wherein transmission power levels and bit-rates are governed by simple logic. In particular, zero-error coding is preferable at time instances with high channel gains, whereas multiple-description coding is superior for time instances with low gains. When channels between the sensors and the gateway are in deep fades, network coding improves estimation accuracy significantly without sacrificing energy efficiency.

Preparation, thermal and rheological properties of hybrid nanocomposite phase change material for thermal energy storage

This paper presents the experimental investigation on the thermal properties and viscosity of the new organic ester phase change material embedded with the silver–titania hybrid nanocomposite (HyNPCM) with the mass proportions ranging from 0.1% to 1.5%. The HyNPCM embedded with the surface functionalized hybrid nanocomposite exhibited improved thermal conductivity from 0.286W/mK to 0.538W/mK, congruent phase change temperature (6.8°C), high latent heat capacity (90.81kJ/kg), substantial reduction in the supercooling degree (1.82°C), thermal stability (191°C) and chemical stability, while compared to the pure PCM. Experimental results reveal that, the freezing and the melting times of the HyNPCM were reduced by 23.9% and 8.5% respectively, when compared to the pure PCM. The increased mass proportion of HyNC resulted in the increased viscosity up to 3.89%, which suggests the existence of relative dependencies between the thermal properties and the viscosity of the HyNPCM. In total, the improved thermal properties and the heat storage potential of the HyNPCM has facilitated them to be considered as a viable candidate for the cool thermal energy storage applications in buildings without sacrificing energy efficiency.

Energy conservative air conditioning system using silver nano-based PCM thermal storage for modern buildings

This work aims at improving the thermal performance and energy efficiency of chilled water based variable air volume air conditioning system integrated with the silver nanoparticles embedded latent thermal energy storage system. The latent thermal energy storage air conditioning system incorporated with the demand controlled ventilation and the economizer cycle ventilation schemes were experimentally investigated for the year-round building air conditioning application. Phase change material embedded with silver nanoparticles enabled it to exhibit improved heat transfer mechanisms in charging and discharging cycles. Experimental results suggest that the proposed air conditioning system achieved an on-peak and per day average energy savings potential of 36–58% and 24–51%, respectively, for year round operation while compared to the conventional air conditioning system. Similarly, while compared with a basically similar variable air volume air conditioning system, the proposed air conditioning system yielded 7.5–18.6% and 7.9–17.8% of on-peak and per day average energy conservative potential, respectively. Furthermore, test results infer that the combined effects produced by the silver nanoparticles embedded latent thermal energy storage system with the ventilation techniques augmented the overall thermal performance of the system. In total, the combined air conditioning system would be beneficial in terms of accomplishing good thermal comfort, acceptable indoor air quality and energy redistribution needs in buildings without sacrificing energy efficiency.

Energy efficient hybrid nanocomposite-based cool thermal storage air conditioning system for sustainable buildings

The quest towards energy conservative building design is increasingly popular in recent years, which has triggered greater interests in developing energy efficient systems for space cooling in buildings. In this work, energy efficient silver–titania HiTES (hybrid nanocomposites-based cool thermal energy storage) system combined with building A/C (air conditioning) system was experimentally investigated for summer and winter design conditions. HiNPCM (hybrid nanocomposite particles embedded PCM) used as the heat storage material has exhibited 7.3–58.4% of improved thermal conductivity than at its purest state. The complete freezing time for HiNPCM was reduced by 15% which was attributed to its improved thermophysical characteristics. Experimental results suggest that the effective energy redistribution capability of HiTES system has contributed for reduction in the chiller nominal cooling capacity by 46.3% and 39.6% respectively, under part load and on-peak load operating conditions. The HiTES A/C system achieved 27.3% and 32.5% of on-peak energy savings potential in summer and winter respectively compared to the conventional A/C system. For the same operating conditions, this system yield 8.3%, 12.2% and 7.2% and 10.2% of per day average and yearly energy conservation respectively. This system can be applied for year-round space conditioning application without sacrificing energy efficiency in buildings.

Circuit-Level Timing-Error Acceptance for Design of Energy-Efficient DCT/IDCT-Based Systems

An intrinsic notion of quality floors present in typical digital signal processing circuits can be used to strategically accept some runtime errors in exchange for a reduction in energy consumption. Conventional very large scale integration design strategies do not exploit this degree of error tolerance and aim to guarantee timing correctness, thereby sacrificing energy efficiency. In this paper, we propose techniques for timing error acceptance to improve the quality-energy tradeoff in image and video processing systems under scaled $V_{DD}$ . The basic philosophy is to prevent signal quality from severe degradation, on average, by using data statistics. The introduced innovations include techniques for carefully controlling possible errors and exploiting the specifics of error patterns for low-cost postprocessing to minimize quality degradation. We demonstrate the effectiveness of the proposed techniques on a 2-D inverse discrete cosine transform (IDCT) and a 2-D DCT design. The designs were synthesized using a 45-nm standard cell library, with energy and delay evaluated using NanoSim and VCS. Experiments show that direct applications of controlled error-acceptance techniques allow up to 59% and 71% energy savings by permitting fewer than 1-dB peak signal-to-noise ratio (PSNR) decrease for the 2-D IDCT and DCT designs, respectively. The resulting PSNR remains above 30dB, which is a commonly accepted value for lossy image and video compression. Achieving such energy savings by direct $V_{DD}$ scaling without the proposed transformations results in a 12-dB PSNR loss. The area overhead for the needed control logic is about 4.8% of the original design. To further minimize quality degradation caused by accepted errors in the IDCT, we introduce postfiltering on the output image. The significant improvement of the perceived image quality allows further voltage scaling leading to overall energy savings of 70% for the 2-D IDCT, while costing an additional 1.1% in area.

Breakdown delay-based depletion mode silicon modulator with photonic hybrid-lattice resonator

A compact silicon electro-optic modulator that operates in the breakdown delay based depletion mode is introduced. This operation mode has not previously been utilized for optical modulators, and represents a way to potentially achieve much higher modulation speeds and carrier extraction efficiencies without sacrificing energy efficiency, which is a critical criterion for realizing miniaturized sub-THz modulation components in silicon. Our study shows a speed of at least 238 GHz modulation is achievable along with an ultra-low energy consumption of 26.6 fJ/bit in a simple planar P+PNN+ diode example structure, which is embedded in a 2D hybrid photonic lattice mode gap resonator. The optical resonator itself is only 69 µm2 in footprint and is designed for optimized electro-optic sensitivity and conversion efficiency with reduced carrier scattering. Both the static and dynamic device performance are backed up by fully integrated 3D optical and 3D electrical numerical results. The compact device dimensions and low energy consumption are favorable to high density photonic integration.