Energy Consumption Optimization for Multihop Cognitive Cellular Networks

Li, Ming; Li, Pan; Huang, Xiaoxia; Fang, Yuguang; Glisic, Savo

doi:10.1109/tmc.2014.2320275

Cited by 52 publications

(15 citation statements)

References 55 publications

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“…For example, two links cannot share the same transmitter radio for simultaneous transmissions. The radio conflict is usually expressed as integer constraints in optimization problems [23], [27] or considered separately aside from other resource allocation [14]. In order to facilitate linear programming, we extend the definition of g ll ′ to cover the radio conflict relationship, and specifically redefine it as interference coefficient.…”

Section: A Network Modelmentioning

confidence: 99%

“…However, such a decomposition will lead to sub-optimality since scheduling and power control are indeed solved separately. A joint solution of scheduling, channel allocation and power control is proposed in [27], but the achievable data rate on links is assumed constant. This model cannot fully reflect the link capability, since the latter is characterized by the real-time SINR at the receiver.…”

Section: Introductionmentioning

confidence: 99%

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Joint Optimization of Scheduling and Power Control in Wireless Networks: Multi-Dimensional Modeling and Decomposition

Liu

Cheng

Cao

et al. 2019

IEEE Trans. on Mobile Comput.

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The energy efficiency of future networks is becoming a significant and urgent issue, calling for greener network designs. At the same time, rapid development of wireless networks shows a trend of increasing complexity in network structure and resource space, leading to that optimizing the energy efficiency of such networks requires a joint solution over multi-dimensional resource space. However, the coupled resource dimensions and growing problem scales bring great challenges in obtaining the optimal solutions. In this paper, we develop a multi-dimensional network model on the basis of tuple-links associated with transmission patterns (TPs) and formulate the optimization problem as a TP based scheduling problem which jointly solves transmission scheduling, routing, power control, radio and channel assignment. In order to tackle the complexity issues raised from coupled resource dimensions, we propose a novel algorithm that decomposes the coupling scheduling and power control by exploiting the delay column generation technique to recursively solve a master problem for scheduling and a sub-problem for power allocation. Further, we theoretically prove that the performance gap between the proposed algorithm and the optimum is upper bounded by that for the sub-problem solution, where the latter is derived by solving a relaxed version of the sub-problem. Numerical results demonstrate the effectiveness of the multi-dimensional framework and the benefit of the proposed joint optimization in improving network energy efficiency.

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Section: A Network Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint Optimization of Scheduling and Power Control in Wireless Networks: Multi-Dimensional Modeling and Decomposition

Liu

Cheng

Cao

et al. 2019

IEEE Trans. on Mobile Comput.

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“…In cellular network the multi hop cognitive cellular network (MC2N) architecture is facilitate the transmission of data exploding with minimum energy consumption. The maximum independent set (MIS) is formulated the optimization problem with energy consumption [2]. The mobile network will be in contacts between nodes and ensure the reliability of transmitting data between the source and destination.…”

Section: Related Workmentioning

confidence: 99%

LMP Congestion Management Using Enhanced STF-LODF in Deregulated Power System

Kumar¹,

Mohan²

2016

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Nowadays electricity market industry is become a major impact on power system for privatization and deregulation of power in global wise. As per the limitation of the transmission system, the complexity arises and the supply fact will be with demand at the time of balancing. The congestion of the power system is occurring based on the transmission limits of the power desire and amount for operating the system. In order to avoid transmission line congestion, enhanced STF-LODF method is proposed. It shows the regulated line transmission flow with generating units by implementing renewable energy resources (RER) based on enhanced STF-LODF in power systems. It avoids the congestion of transmission line frequently in the power system and manages price based on pricing and sensitivity approach, and also manages optimal location of congestion transmission and instability issues of voltage. The congestion management of Locational Marginal Pricing (LMP) is performed with minimum line loss, less cost, line flow, better sensitivity and better performances in optimal power flow and control flow. The efficiency of the proposed power system is analyzed and verified by the simulation results of tested IEEE 14 bus system.

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“…The novel method for optimizing the energy consumption of robotic manufacturing systems was proposed in [9], which embedded detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. Li M et.al [10] proposed a new multi-hop cognitive cellular network architecture to facilitate the ever exploding data transmissions in cellular networks. A novel power optimization utility software was proposed by Hazel T et.al [11], which considered the different energy costs across the pipeline pump/compressor stations, utility contracts, and pump/ compressor efficiency.…”

Section: Introductionmentioning

confidence: 99%

Energy consumption optimization management mechanism based on drug green crowd data in biological pharmaceutical cloud environment

Wang

Cheng

2017

J Embedded Systems

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For satisfying the network trend and intelligent demand of biopharmaceutical, we proposed the energy optimization consumption and management scheme of the drug green crowd data in the biological pharmaceutical cloud environment. First, the biopharmaceutical process are mapped to the cloud platform, which can not only adapt to the revolutionary changes in the way of biopharmaceutical research and but also build a network management platform for pharmaceutical research and development. Secondly, based on the green crowd, we reconstruct the organization structure of the cloud platform, production process, and value chain-driven portfolio, etc. Then, we divide the core of the cloud platform architecture into five substages. The green screening, reorganization, and crowd data processing will be completed by the cooperation of these stages. Finally, the drug green crowd architecture is embedded into the time domain conversion interface and the state transition interface. In addition, the state energy consumption model of the biological pharmaceutical cloud platform is constructed. The experimental results show that compared with the traditional task-driven energy consumption management mechanism, the proposed management mechanism can ensure higher throughput, higher effective flow rate, and higher effective energy consumption ratio.

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Energy Consumption Optimization for Multihop Cognitive Cellular Networks

Cited by 52 publications

References 55 publications

Joint Optimization of Scheduling and Power Control in Wireless Networks: Multi-Dimensional Modeling and Decomposition

Joint Optimization of Scheduling and Power Control in Wireless Networks: Multi-Dimensional Modeling and Decomposition

LMP Congestion Management Using Enhanced STF-LODF in Deregulated Power System

Energy consumption optimization management mechanism based on drug green crowd data in biological pharmaceutical cloud environment

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