• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.20-23
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• 2019

Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12A
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• pp.959-965
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• 2011

As the usage of mobile stations increases thanks to various services, power saving mechanisms of mobile station operated by battery power have been gained much attention. This paper presents a power saving mechanism(PSM) of IEEE 802.16m, called Mobile WiMAX, for 4G mobile technology. This paper first presents different points of the PSM of IEEE 802.16m from IEEE 802.16e, which is a basis of IEEE 802.16m. This paper proposes a dynamic sleep cycle adjustment algorithm for improving the performance of IEEE 802.16m PSM by considering the arrival pattern of incoming packets from base station. Performance of the algorithm is analyzed in terms of energy consumption as well as waiting time of packets.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1347-1360
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• 2018

Owing to limited energy in wireless devices power saving is very critical to prolong the lifetime of the networks. In this regard, we designed a cross-layer optimization mechanism based on power control in which source node broadcasts a Route Request Packet (RREQ) containing information such as node id, image size, end to end bit error rate (BER) and residual battery energy to its neighbor nodes to initiate a multimedia session. Each intermediate node appends its remaining battery energy, link gain, node id and average noise power to the RREQ packet. Upon receiving the RREQ packets, the sink node finds node disjoint paths and calculates the optimal power vectors for each disjoint path using cross layer optimization algorithm. Sink based cross-layer maximal minimal residual energy (MMRE) algorithm finds the number of image packets that can be sent on each path and sends the Route Reply Packet (RREP) to the source on each disjoint path which contains the information such as optimal power vector, remaining battery energy vector and number of packets that can be sent on the path by the source. Simulation results indicate that considerable energy saving can be accomplished with the proposed cross layer power control algorithm.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1153-1155
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• 2008

Color dimming technology has been developed for high color gamut and aggressive power saving. In our new algorithm, we proposed a new concept of 'color class', with which it is possible to control RGB color luminance effectively and exactly. We reached color gamut of 155% of NTSC 1976 and reduced power consumption under 100 watt for 46 inch LCD.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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• pp.9-16
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• 2008

This paper presents a frequency selection algorithm for minimization power consumption of processor in Mobile System. The proposed algorithm has processor designed low power processor using clock gating method. Clock gating method has improved the power dissipation by control main clock through the bus which is embedded clock block applying the method of clock gating. Proposed method has compared power consumption considered the dynamic power for processor, selected frequency has considered energy gain and energy consumption for designed processor. Or reduced power consumption with decreased processor speed using slack time. This technique has improved the life time of the mobile systems by clock gating method, considered energy and using slack time. As an results, the proposed algorithm reduce average power saving up to 4% comparing to not apply processor in mobile system.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1156-1159
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• 2008

Local dimming driving has advantages in reducing power consumption and improving contrast ratio(CR). In an LED backlight unit(BLU), many small LED blocks are implemented in 2-dimmensional space, and luminance of the blocks is controlled by a local dimming algorithm. However, such a BLU can induce various recognizable artifacts. A new novel algorithm is proposed for exact block luminance calculation to correct local dimming artifacts. Also we discuss modified low-gray-level dimming to achieve much aggressive power saving in a local dimming BLU system.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.289-292
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• 2008

This paper represents the electric energy saving using light control system. Without Light Control System(LCS), it is very hard to classify the amount of electric energy saving for lighting, since it is determined by the end-user's preference in times. Typical LCS has an fixed algorithm to control each light's intensity by ON/Off Control, Step Control, or Dimming Control. We have studied the electric energy saving effect in a LCS equiped building with natural lighting. The electric power consumption at the peak power consumption time with LCS reduced up to 65% of the non-controled case.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2388-2390
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• 2002

Small type electric energy saving system is proposed in this paper. The system improves power factor fastly according to load variation of each customer. Phases of voltage and current are detected as 1[ms] unit. Phase coincident algorithm is applied for power factor improvement. Capacitance is controlled for optimal power factor correction. Series reactor is controlled for harmonics reduction. Non-contact device is used for fast response and long life. Test result shows the effect of this system. Power factor of 40[W] electric fan is improved from 95[%] to 100[%]. In the case of electric light, power factor is improved from 82[%] to 100[%]. Response time for load variation is less than 1[ms].

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.135-140
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• 2020

Recently, due to the rapid diffusion of intelligent systems and IoT technologies, power saving techniques in real-time embedded systems has become important. In this paper, we propose P-GA (Parallel Genetic Algorithm), a scheduling algorithm aims at reducing the power consumption of real-time systems in multi-core hybrid memory environments. P-GA improves the Proportional-Fairness (PF) algorithm devised for multi-core environments by combining the dynamic voltage/frequency scaling of the processor with the nonvolatile memory technologies. Specifically, P-GA applies genetic algorithms for optimizing the voltage and frequency modes of processors and the memory types, thereby minimizing the power consumptions of the task set. Simulation experiments show that the power consumption of P-GA is reduced by 2.85 times compared to the conventional schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.61-69
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• 2015

Through Virtual Machine technology(VM), VMs can be packed into much fewer number of physical servers than that of VMs. Since even an idle physical server wastes more than 60% of max power consumption, it has been considered as one of energy saving technologies to minimize the number of physical servers by using the knapsack problem solution based on the computing resources. However, this paper shows that this tightly packed consolidation may not achieve the efficient energy saving. Instead, a service pattern-based VM consolidation algorithm is proposed. The proposed algorithm takes the service time of each VM into account, and consolidates VMs to physical servers in the way to minimize energy consumption. The comprehensive simulation results show that the proposed algorithm gains more than 30% power saving.