• International journal of advanced smart convergence
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• v.9 no.4
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• pp.34-41
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• 2020

Nowadays, the advanced smart convergences of the artificial intelligence (AI) and the internet of things (IoT) have been more and more important, in the fifth generation (5G) and beyond 5G (B5G) mobile communication. In 5G and B5G mobile networks, non-orthogonal multiple access (NOMA) has been extensively investigated as one of the most promising multiple access (MA) technologies. In this paper, we investigate the achievable data rate for the asymmetric binary pulse amplitude modulation (2PAM), in non-orthogonal multiple access (NOMA). First, we derive the closed-form expression for the achievable data rate of the asymmetric 2PAM NOMA. Then it is shown that the achievable data rate of the asymmetric 2PAM NOMA reduces for the stronger channel user over the entire range of power allocation, whereas the achievable data rate of the asymmetric 2PAM NOMA increases for the weaker channel user improves over the power allocation range less than 50%. We also show that the sum rate of the asymmetric 2PAM NOMA is larger than that of the conventional standard 2PAM NOMA, over the power allocation range larger than 25%. In result, the asymmetric 2PAM could be a promising modulation scheme for NOMA of 5G systems, with the proper power allocation.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• Environmental Engineering Research
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• v.21 no.1
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• pp.91-98
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• 2016

Along with China's increasing share in global total $CO_2$ emissions, there is a necessity for China to shoulder large emission-mitigating responsibility. The appropriate allocation of $CO_2$ emission quotas can build up a solid foundation for future emissions trading. In views of originality, an optimized approach to determine $CO_2$ emissions allocation efficiency based on the zero sum gains data envelopment analysis (ZSG-DEA) method is proposed. This paper uses a non-radial ZSG-DEA model to allocate $CO_2$ emissions between different Chinese provinces by 2020 and treats $CO_2$ as the undesirable output variable. Through the calculation of efficiency allocation amounts of provincial $CO_2$ emissions, all provinces are on the ZSG-DEA efficiency frontier. The allocation results indicate that the cumulative optimal amounts of $CO_2$ emissions in 2020 were higher than the actual amounts in 13 provinces, and lower in other 17 provinces, and show that different provinces have to shoulder different mitigation burdens in terms of emission reduction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.165-175
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• 2016

A data allocation technique is essential to improve the performance of data broadcast systems. This paper explores the issues for allocating data items on broadcast channels to process multiple-data queries in the environment where query profiles and query request rates are given, and proposes a new data allocation scheme named QBDA. The proposed scheme allows the query with higher request rate to have higher priority to schedule its data items and introduces the concept of marking to reduce data conflicts. Simulation is performed to evaluate the performance of QBDA. The simulation results show that the proposed scheme outperforms other schemes in terms of the average response time since it can process queries with high request rate fast and show a very desirable characteristics in the aspects of query data adjacency and data conflict probability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2B
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• pp.146-153
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• 2006

It is required to have researches on efficient resource allocation schemes in an integrated voice and data CDMA system with the spreading of high-speed wireless internets. In this paper, we proposed a efficient resouce allocation scheme for providing a high speed data service in an integrated CDMA system. In an integrated voice/data CDMA system, resources for voice users are allocated with high priority and residual resources are allocated to the data service. In this case, it is necessary to use a resource allocation scheme for minimizing interference. In this paper, we first explain about a interference minimizing method and define QoS requirements. Based on the method, we proposed a efficient resource allocation scheme which satisfy the QoS requirements. The proposed scheme controls the transmission rate and delay of data users with a priority information such as the number of packets in a queue. From the simulation results, we show that the proposed scheme reduce the blocking probability and delay and improve the performance.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.166-171
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• 2003

In this paper, we propose a minimal power data path allocation algorithm for low power circuit design. The proposed algorithm minimizes switching activity for input variables in scheduled CDFG. Allocations are further divided into the tasks of register allocation and module allocation. The register allocation algorithm execute that it eliminate spurious switching activity in functional unit and minimize the numbers of multiplexer. Also, resource allocation method selects a sequence of operations for a module such that the switching activity is reduced. Therefore, the algorithm executes to minimize the switching activity of input values, sequence of operations and number of multiplexer. Experimental results using benchmarks show that power is reduction effect from 13% to 17% power consumption, when compared with the Genesis-lp high-level synthesis system.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.627-638
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• 2014

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and non-uniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.145-182
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• 2008

As the life expectancy increases resulting in the aged society, the post-retirement life became one of the most important concerns of people. The long-term investment vehicles such as retirement savings and pension plans have been introduced to meet such demand of society. This paper examines the impact of asset allocation strategies on the long-term investment performance. Because of the unusually long investment horizon and the compounding effect, a suboptimal asset mix in a retirement plan can be a very costly and irreversible mistake. Instead of relying on anecdotal evidence to evaluate the merits of different allocation strategies, this paper performs various tests including stochastic dominance tests using both actual data and Monte Carlo simulated data that best fit the historical experience. The results indicate 1) the long-term investments perform better than the short-term investments, 2) the optimal asset allocation strategy for the long-term investments should be highly equity dominated.

• Journal of KIISE
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• v.43 no.2
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• pp.152-162
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• 2016

Most traditional garbage collectors commonly use the language level metadata, which is designed for pointer type searching. However, because it is difficult to use this metadata in non-volatile memory allocation platforms, a new garbage collection technique is essential for non-volatile memory utilization. In this paper, we design new metadata for managing information regarding non-volatile memory allocation called "Allocation Tree". This metadata is comprised of tree data structure for fast information lookup and a node that holds an allocation address and an object ID pair in key-value form. The Garbage Collector starts collecting when there are insufficient non-volatile memory spaces, and it compares user data and the allocation tree for garbage detection. We develop this algorithm in a persistent heap based non-volatile memory allocation platform called "HEAPO" for demonstration.

• Journal of Communications and Networks
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• v.4 no.2
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• pp.136-147
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• 2002

In this paper, the maximal capacity of the data network link has attempted to be exploited by using the dynamic allocation strategy. We propose a new methodology based on the economic models for competing traffic classes (classes of sessions) in packet networks. As the demand for network services accelerates, users' satisfaction to the service level might decrease due to the congestion at the network nodes. To prevent this, efficient allocation of a networks resources, such as available bandwidth and switch capacity, is needed. By using the so-called user profile as well as the utility (e.g., data rate) functions, it is possible to allocate data rates and other utilities using the arbitrary number of QoS classes, say $0.01,...,$10.