• Title/Summary/Keyword: Power Resource Allocation

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A New High speed, Low Power TFT-LCD Driving Method (새로운 고속, 저전력 TFT-LCD 구동 방법)

  • Park, Soo-Yang;Son, Sang-Hee;Chung, Won-Sup
    • Journal of IKEEE
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    • v.10 no.2 s.19
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    • pp.134-140
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    • 2006
  • This paper proposed a low power resource allocation algorithm for the minimum switching activity of operators in high level synthesis. In this paper, the proposed method finds switching activity in circuit each functional unit exchange for binary sequence length and value bit are logic one value. To use the switching activity was found the allocation with minimal power consumption, the proposed method visits all control steps one by one and determines the allocation with minimal power consumption at each control step. As the existing method, the execution time can be fast according to use the number of operator and maximal control step. And it is the reduction effect from 8.5% to 9.3%.

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A New Resource Allocation with Rate Proportionality Constraints in OFDMA Systems (OFDMA 시스템에서 비율적 전송률 분배를 위한 자원 할당)

  • Han, Seung-Youp;Oh, Eun-Sung;Han, Myeong-Su;Hong, Dae-Sik
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.45 no.1
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    • pp.59-65
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    • 2008
  • In this paper, a new adaptive resource allocation scheme is proposed in orthogonal frequency-division multiple access(OFDMA) systems with rate proportionality constraints. The problem of maximizing the overall system capacity with constraints on bit error rate, total transmission power and rate-proportionality for user requiring different classes of service is formulated. Since the optimal solution to the constrained fairness problem is extremely complex to obtain, a low-complexity suboptimal algorithm that separates subchannel allocation and power allocation is proposed. Firstly, the number of subchannels to be assigned to each user is determined based on the users' average signal-to-noise ratio and rate-proportion. Subchannels are subsequently distributed according to the modified max-min criterion. Lastly, based on the subchannel allocation, the optimal power allocation by solving the Language dual problem is proposed. Additionally, in order to reduce the computational complexity, iterative rate proportionality tracking algorithm is proposed for maximizing the capacity together with maintaining the rate proportionality constraint.

A Novel Resource Allocation Algorithm in Multi-media Heterogeneous Cognitive OFDM System

  • Sun, Dawei;Zheng, Baoyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.5
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    • pp.691-708
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    • 2010
  • An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

A Low Power-Driven Data Path Optimization based on Minimizing Switching Activity (스위칭 동작 최소화를 통한 저전력 데이터 경로 최적화)

  • 임세진;조준동
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.4
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    • pp.17-29
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    • 1999
  • This paper presents a high level synthesis method targeting low power consumption for data-dominated CMOS circuits (e.g., DSP). The high level synthesis is divided into three basic tasks: scheduling, resource and register allocation. For lower power scheduling, we increase the possibility of reusing an input operand of functional units. For a scheduled data flow graph, a compatibility graph for register and resource allocation is formed, and then a special weighted network is then constructed from the compatibility graph and the minimum cost flow algorithm is performed on the network to obtain the minimum power consumption data path assignment. The formulated problem is then solved optimally in polynomial time. This method reduces both the switching activity and the capacitance in synthesized data path. Experimental results show 15% power reduction in benchmark circuits.

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Resource-efficient load-balancing framework for cloud data center networks

  • Kumar, Jitendra;Singh, Ashutosh Kumar;Mohan, Anand
    • ETRI Journal
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    • v.43 no.1
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    • pp.53-63
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    • 2021
  • Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

Joint Resource Allocation Scheme for OFDM Wireless-Powered Cooperative Communication Networks

  • Liang, Guangjun;Zhu, Qi;Xin, Jianfang;Pan, Ziyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1357-1372
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    • 2017
  • Energy harvesting techniques, particularly radio frequency energy harvesting (RF-EH) techniques, which are known to provide feasible solutions to enhance the performance of energy constrained wireless communication systems, have gained increasing attention. In this paper, we consider a wireless-powered cooperative communication network (WPCCN) for transferring energy in the downlink and forwarding signals in the uplink. The objective is to maximize the average transmission rate of the system, subject to the total network power constraint. We formulate such a problem as a form of wireless energy transmission based on resource allocation that searches for the joint subcarrier pairing and the time and power allocation, and this can be solved by using a dual approach. Simulation results show that the proposed joint optimal scheme can efficiently improve system performance with an increase in the number of subcarriers and relays.

Improved Resource Allocation Model for Reducing Interference among Secondary Users in TV White Space for Broadband Services

  • Marco P. Mwaimu;Mike Majham;Ronoh Kennedy;Kisangiri Michael;Ramadhani Sinde
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.55-68
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    • 2023
  • In recent years, the Television White Space (TVWS) has attracted the interest of many researchers due to its propagation characteristics obtainable between 470MHz and 790MHz spectrum bands. The plenty of unused channels in the TV spectrum allows the secondary users (SUs) to use the channels for broadband services especially in rural areas. However, when the number of SUs increases in the TVWS wireless network the aggregate interference also increases. Aggregate interferences are the combined harmful interferences that can include both co-channel and adjacent interferences. The aggregate interference on the side of Primary Users (PUs) has been extensively scrutinized. Therefore, resource allocation (power and spectrum) is crucial when designing the TVWS network to avoid interferences from Secondary Users (SUs) to PUs and among SUs themselves. This paper proposes a model to improve the resource allocation for reducing the aggregate interface among SUs for broadband services in rural areas. The proposed model uses joint power and spectrum hybrid Firefly algorithm (FA), Genetic algorithm (GA), and Particle Swarm Optimization algorithm (PSO) which is considered the Co-channel interference (CCI) and Adjacent Channel Interference (ACI). The algorithm is integrated with the admission control algorithm so that; there is a possibility to remove some of the SUs in the TVWS network whenever the SINR threshold for SUs and PU are not met. We considered the infeasible system whereby all SUs and PU may not be supported simultaneously. Therefore, we proposed a joint spectrum and power allocation with an admission control algorithm whose better complexity and performance than the ones which have been proposed in the existing algorithms in the literature. The performance of the proposed algorithm is compared using the metrics such as sum throughput, PU SINR, algorithm running time and SU SINR less than threshold and the results show that the PSOFAGA with ELGR admission control algorithm has best performance compared to GA, PSO, FA, and FAGAPSO algorithms.

Resource Allocation for Heterogeneous Service in Green Mobile Edge Networks Using Deep Reinforcement Learning

  • Sun, Si-yuan;Zheng, Ying;Zhou, Jun-hua;Weng, Jiu-xing;Wei, Yi-fei;Wang, Xiao-jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2496-2512
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    • 2021
  • The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

An Efficient Multi-User Resource Allocation Scheme for Future IEEE 802.11 LRLP Communications (미래 IEEE 802.11 LRLP 통신을 위한 효율적인 다중 사용자 자원할당 기법)

  • Ahn, Woojin;Kim, Ronny Yongho
    • Journal of Advanced Navigation Technology
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    • v.20 no.3
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    • pp.232-237
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    • 2016
  • As a possible standardization of wireless local area network (WLAN), IEEE 802.11 LRLP is under discussion in order to support long range and low power (LRLP) communication for internet of things (IoT) including drones and many other IoT devices. In this paper, an efficient adaptive resource unit allocation scheme for uplink multiuser transmission in IEEE 802.11 LRLP networks is proposed. In the proposed scheme, which adopts OFDMA random access based transmission scheme of IEEE 802.11ax, in order to enhance the efficiency of the slotted OFDMA random access, access point (AP) traces the history of the sizes of successfully transmitted uplink data, and adjusts the sizes of resource units for the next uplink multiuser transmission adaptively. Our simulation results corroborate that the proposed scheme significantly improves the system throughput.

Resource Allocation Based on Interference Awareness for Device-to-Device Communication in Cellular Networks (셀룰러 네트워크에서 간섭 인지 기반의 단말간 직접 통신 자원할당 방법)

  • Yang, Mochan;Shin, Oh-Soon;Shin, Yoan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.9
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    • pp.557-559
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    • 2014
  • We propose an efficient resource allocation scheme based on interference awareness for D2D (Device-to-Device) communication in cellular networks. Recently, many researchers have studied how to allocate frequency resources to DUE (D2D User Equipment) with full interference channel information. However, it is difficult to assume a scenario where instantaneous interference information between the CUE (Cellular UE) and DUE is known to the BS (Base Station). To tackle this problem, we proposed in this paper a new scheme in which the BS allocates a resource to CUE and DUE without a full channel information and can aware interference based on only transmit power and distance between UEs. Simulation results show effectiveness of the proposed scheme.