• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.360-370
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• 2009

Using solar power in wireless sensor networks requires a different approach to energy optimization from networks with battery-based nodes. Solar energy is an inexhaustible supply which can potentially allow a system to run forever, but there are several issues to be considered such as the uncertainty of energy supply and the constraint of rechargeable battery capacity. In this paper, we present SolarSS: a reliable storage system for solar-powered sensor networks, which provides a set of functions, in separate layers, such as sensory data collection, replication to prevent failure-induced data loss, and storage balancing to prevent depletion-induced data loss. SolarSS adapts the level of layers activated dynamically depending on solar energy availability, and provides an efficient resource allocation and data distribution scheme to minimize data loss.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.269-276
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• 2021

Recently, smart sensors are used in various environments, and the implementation of ad-hoc sensor networks (ASNs) is a hot research topic. Unfortunately, traditional sensor network routing algorithms focus on specific control issues, and they can't be directly applied to the ASN operation. In this paper, we propose a new routing protocol by using the Q-learning technology, Main challenge of proposed approach is to extend the life of ASNs through efficient energy allocation while obtaining the balanced system performance. The proposed method enhances the Q-learning effect by considering various environmental factors. When a transmission fails, node penalty is accumulated to increase the successful communication probability. Especially, each node stores the Q value of the adjacent node in its own Q table. Every time a data transfer is executed, the Q values are updated and accumulated to learn to select the optimal routing route. Simulation results confirm that the proposed method can choose an energy-efficient routing path, and gets an excellent network performance compared with the existing ASN routing protocols.

• The Korean Journal of Ecology
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• v.16 no.4
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• pp.417-428
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• 1993

Branching growth pattern of Mugnolza denuduta is likely to be originated from two growth strategies: environment overcoming strategy and life maintenance strategy, which coexist in a tree. Growth rate of branches was strongly correlated with relative light intensity (P<0.001) and physical contact (P<0.01), however there is no significant correlation between growth rate and direction of branch. When relative light intensity is less than 1%, the growth was restricted by physical contact with the surrounding branches. In contrast, the growth was rarely restricted by physical contact when relative light intensitiy was 10% or more. The branching rate was significantly affected by the presence or absence of physical contact (P<0.05), but it was not significantly affected by relative light intensity nor by the direction of branch. In the beginning stage of the growth, the ratio of the material allocation from main branch to subbranch was large and varied with the influence of surrounding environment. These various growth rates, which implicate a variety of material allocation ratios (0.16~0.98), affect branch growth pattern through the optimum growth strategies. The growth and arrangement of branches of Magnolia denudata display the solar collectors to maximize the total amount of energy absorbed and to overcome the restriction of the environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2534-2542
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• 2011

In this paper, we show that performance can be improved by using multiple antennas in the conventional orthogonal code hopping multiplexing (OCHM) scheme, which was proposed for accommodating a larger number of users with low channel activities than the number of orthogonal codewords used in code division multiple access (CDMA)-based communication systems through downlink statistical multiplexing. First, we introduce two different types of OCHM systems together with orthogonal codeword allocation strategies, and then derive their mathematical expression for log-likelihood ratio (LLR) values according to the two different schemes. Next, when a turbo encoder based on the LLR computation is used, we evaluate performance on the frame error rate (FER) for the aformentioned OCHM system. For comparison, we also show performance for the existing symbol mapping method using multiple antennas, which was used in 3GPP standards. As a result, it is shown that our OCHM system with multiple antennas based on the proposed orthogonal codeword allocation strategy leads to performance gain over the conventional system---energy required to satisfy a target FER is significantly reduced.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.100-105
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• 2017

In this paper, we study an interference avoidance scenario in the presence of a interferer which can rapidly observe the transmit power of backscatter communications and effectively interrupt backscatter signals. We consider a power control with a sub-channel allocation to avoid interference attacks and a power-splitting ratio for backscattering and RF energy harvesting in sensors. We formulate the problem based on a Stackelberg game theory and compute the optimal transmit power, power-splitting ratio, and sub-channel allocation parameter to maximize a utility function against the interferer. We propose the utility maximization using Lagrangian dual decomposition for the backscatter communications and the interferer to prove the existence of the Stackelberg equilibrium. Numerical results show that the proposed algorithms effectively maximize the utility, compared to that of the algorithm based on the Nash game, so as to overcome a malicious interference in backscatter communications.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.330-343
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• 2017

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pregridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1200-1209
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• 2011

In this paper, we propose a novel energy efficient MAC protocol which is based on orthogonal frequency division multiple access (OFDMA) and exploits the physical characteristic that propagation loss of acoustic wave depends on the distance. In the proposed scheme, sensor nodes are grouped according to the distance to sink node. Then, each group uses a different frequency band. The proposed scheme not only enables all sensor nodes to maintain the signal-to-noise ratio above a certain required level (Accepted Minimum SNR, AMS), but also reduces overall transmission power consumption. In addition, the dynamic sub-channel allocation is employed in order to improve data transmission rate. Simulations show that proposed MAC protocol has better performance in a delay-tolerant underwater acoustic sensor networks.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.733-753
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• 2022

Korean government established the Nationally Determined Contribution (NDC) in 2015. After revising in 2019, the government updated an enhanced target at the end of last year. When the NDC is addressed, the emission targets of each sector, such as power generation, industry, and buildings, are also set. This paper analyzes the emission target of each sector by applying a claims problem or bankruptcy problem developed from cooperative game theory. The five allocation rules from a claims problem are introduced and the properties of each rule are considered axiomatically. This study applies the five rules on allocating carbon emission by sector under the NDC target and compares the results with the announced government target. For the power generation sector, the government target is set lower than the emissions allocated by the five rules. On the other hand, the government target for the industry sector is higher than the results of the five rules. In other sectors, the government's targets are similar to the results of the rule that allocates emissions in proportion to each claim.

• BMB Reports
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• v.51 no.11
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• pp.547-548
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• 2018

Phloem network integrates cellular energy status into post-embryonic growth, and development by tight regulation of carbon allocation. Phloem development involves complicated coordination of cell fate determination, cell division, and terminal differentiation into sieve elements (SEs), functional conduit. All of these processes must be tightly coordinated, for optimization of systemic connection between source supplies and sink demands throughout plant life cycle, that has substantial impact on crop productivity. Despite its pivotal role, surprisingly, regulatory mechanisms underlying phloem development have just begun to be explored, and we recently identified a novel translational regulatory network involving RNA G-quadruplex and a zinc-finger protein, JULGI, for phloem development. From this perspective, we further discuss the role of RNA G-quadruplex on post-transcriptional control of phloem regulators, as a potential interface integrating spatial information for asymmetric cell division, and phloem development.