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Multi-Users Cooperative Spectrum Sensing in Distributed Cognitive Radio networks with Energy Harvesting

Multi-Users Cooperative Spectrum Sensing in Distributed Cogn...

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2nd International Conference on Simulation and Modeling Methodologies,Technologies and Applications(SMTA 2015)

作者： H.Wang F.Z.Zeng Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University

In this paper we propose an improved sensing scheme in cognitive radio networks, which allows the secondary users to utilize the spectrum of primary users when these resources are not being used currently. We first apply multi-user cooperative spectrum sensing in cognitive radio networks to improve both energy efficiency and spectrum utility. Secondly, we investigate the energy harvesting communication model. Finally, we analysis the probability of the proposed spectrum sensing scheme, and obtain an optimal solution under the scenarios of non-energy harvesting scheme and energy harvesting scheme respectively. The simulation results demonstrate the high performance of our proposed scheme.

关键词： Multi-Users Cooperative Spectrum Sensing in Distributed Cognitive Radio networks with Energy Harvesting Radio

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Adaptive Compressed Classification for Energy Efficient Activity Recognition in Wireless Body Sensor networks

Adaptive Compressed Classification for Energy Efficient Acti...

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International Conference on Big Data computing and Communications (BIGCOM)

作者： Ling Xiao Yu Meng Kai Wu Key Laboratory for Embedded and Network Computing of Hunan Province China

Energy efficiency for activity recognition is a challenging task in the long-term health monitoring applications. To save the energy in wireless body sensor networks, the adaptive compressed classification framework for activity recognition is proposed. The proposed mechanism estimates the minimum activity-specific compression ratio subject to given recognition accuracy and adaptively adjusts the number of samples taken by sensor nodes based on the feedback from the result of activity recognition. A brute force algorithm is utilized to quickly find the optimal trade-off the power consumption and classification performance. With experiments on real-world activity datasets, we demonstrate 90.5% recognition accuracy with energy consumption reduced 28%.

关键词： Activity recognition Energy consumption Optimized production technology Wireless communication Base stations Body sensor networks

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Cyber-Physical Systems Design in An Uncertain Environment with Time Uncertainty Concern 29

Cyber-Physical Systems Design in An Uncertain Environment wi...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Chen, Si Huang, Lida Xiao, Xiongren Liu, Yan Xie, Guoqi Li, Renfa Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Changsha China Research Institute of Hunan University in Chongqing Center for Convergence of Automobile and Cyberspace Chongqing China

ISBN: (纸本)9798350330717

Multiple processors system on chip (MPSoC) has been the trend in cyber-physical systems (CPSs), and reasonable partitioning for MPSoC resources is a critical step in CPSs design. The uncertainties of environment and time are both important factors that need to be considered in the design, but none of the previous work pays attention to two uncertainties at the same time. The state-of-the-art work presented a detailed process of applying uncertain programming to solve the partitioning problem, which provides a solution for designing in an uncertain environment. However, this work only considers the bipartition scenario which cannot be directly applied to MPSoC, and it does not focus specifically on time uncertainty. In this paper, we propose a method for modeling the MPSoC partitioning problem in an uncertain environment, with the time uncertainty concern. We present the uncertain model that can be applied to the multiple optional resources scenario. We build the optimization model with the objective of minimizing time, analyze two different cases of minimizing the uncertain time, and finally prove a unified deterministic model to solve. We come up with three algorithms, including the heuristic algorithm, the genetic algorithm, and the exact algorithm, and experiments show that the heuristic algorithm and the genetic algorithm can obtain good approximate solutions compared with the exact algorithm. © 2023 IEEE.

关键词： Cyber-physical systems (CPSs) design multiple processors system on chip (MPSoC) partitioning time uncertainty uncertain environment

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New binary artificial bee colony for the 0-1 knapsack problem 9th

New binary artificial bee colony for the 0-1 knapsack proble...

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9th International Conference on Swarm Intelligence, ICSI 2018

作者： Nouioua, Mourad Li, Zhiyong Jiang, Shilong The College of Computer Science and Electronic Engineering Hunan University Changsha China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China PKU-HKUST Shenzhen-HongKong Institution Shenzhen China

ISBN: (纸本)9783319938141

The knapsack problem is one of the well known NP-Hard optimization problems. Because of its appearance as a sub-problem in many real world problems, it attracts the attention of many researchers on swarm intelligence and evolutionary computation community. In this paper, a new binary artificial bee colony called NB-ABC is proposed to solve the 0-1 knapsack problem. Instead of the search operators of the original ABC, new binary search operators are designed for the different phases of the ABC algorithm, namely the employed, the onlooker and the scout bee phases. Moreover, a novel hybrid repair operator called (HRO) is proposed to repair and improve the infeasible solutions. To assess the performance of the proposed algorithm, NB-ABC is compared with two other existing algorithms, namely GB-ABC and BABC-DE, for solving the 0-1 knapsack problem. Based on a set of 15 0-1 high dimensional knapsack problems classified in three categories. the experimental results in view of many criteria show the efficiency and the robustness of the proposed NB-ABC. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Repair

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ACWB: Access-characteristic write buffer management scheme for flash memory 21

ACWB: Access-characteristic write buffer management scheme f...

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21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Zhu, Lei Liu, Yan Zhang, Zaimei Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha Hunan410082 China School of Economics and Management Changsha University of Science and Technology Changsha Hunan410076 China

ISBN: (纸本)9781728120584

Compared with traditional hard disk drives (HDD), solid state drives (SDD) have distinct characteristics, such as efficient continuous access and random reading capability. Using of SSD is greatly limited due to the out-of-place update and endurance problem. Many flash-aware buffer schemes have been proposed to reduce write and erase operations. However, a good buffer management scheme should reduce the effects of random writes and suit access patterns. In this paper, we propose an access characteristic write buffer management scheme (ACWB) on flash memory that integrates write buffer and cost regulation based on access characteristic. Experimental results show that ACWB increases the response time by 35%, reduces erase times by 25%, and improves the hit ratio by 27% on the average compared with current flash-aware write buffer schemes. © 2019 IEEE.

关键词： Flash memory

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Discriminative hough-voting for object detection with parts

Discriminative hough-voting for object detection with parts

引用

International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Yaodong Chen Renfa Li Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China

ISBN: (纸本)9781479925667

Many detection models rely on sliding-window methods to search all possible candidates and then localize true instances by linear classifiers. Such exhaustive search involves massive computation. Hough voting scheme provides an alternative way to localize objects. Typical voting-based approaches, casting independent votes for a hypothesis, ignore the mutual relevance of features. The weights of the features for voting are learnt in a simple way. These two weaknesses limit the detection performance of the voting scheme. This paper introduces a novel voting-based model. We group the model features into parts. The features in one part are dependent and can cast consistent votes for a given hypothesis. For a given hypothesis we introduce an overall score function whose parameters can be optimized in a discriminative way. We apply a latent learning framework to deal with part-level weak supervision. The experiments evaluate the proposed model on two standard datasets. We demonstrate significant improvements in detection performance comparing the start-of-the-art detection models.

关键词： Object detection Computational modeling Shape Feature extraction Training Search problems Transforms

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RTISM: Real-Time Inter-VM Communication Based on Shared Memory for Mixed-Criticality Flows 44

RTISM: Real-Time Inter-VM Communication Based on Shared Memo...

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44th IEEE Real-Time Systems Symposium, RTSS 2023

作者： Li, Zonghong Xie, Guoqi Ma, Wenhong Xiao, Xiongren Xie, Yong Ren, Wei Chang, Wanli College of Computer Science and Electronic Engineering Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province China Research Institute of Hunan University Chongqing China Nanjing University of Posts and Telecommunications China Huawei Technologies China

ISBN: (纸本)9798350328578

Virtual machines (VMs) have been increasingly deployed in real-time systems to enhance heterogeneous resource sharing. Despite being isolated for security and prevention of failure propagation, VMs need to communicate with each other to complete certain tasks jointly. A real-time inter-VM communication framework has been proposed based on VirtIO, which is in essence a mechanism of message passing with high latency and low scalability on data amount. In contrary, IVSHMEM implements inter-VM communication with shared memory, which is generally fast and large in throughput. Unfortunately, IVSHMEM does not resolve resource contention between flows and hence cannot be applied in real-time scenarios. In this work, we propose a real-time inter-VM communication framework RTISM built upon shared memory and IVSHMEM. RTISM provides priority-based scheduling and supports mixed-criticality flows. Worst-Case Response Time (WCRT) analysis is reported to bound the end-to-end communication delay and a Limited Priority Assignment (LPA) algorithm is developed to enhance schedulability. Experimental evaluation shows that (i) RTISM has about 4 times higher throughput than the VirtIO-based inter-VM communication framework;(ii) LPA improves schedulability by over 25% compared to the state-of-the-art;(iii) WCRT produces a tight bound. © 2023 IEEE.

关键词： Real time systems

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A High-performance DAG Task Scheduling Algorithm for Heterogeneous networked embedded Systems

A High-performance DAG Task Scheduling Algorithm for Heterog...

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IEEE International Conference on Advanced Information networking and Applications

作者： Guoqi Xie Renfa Li Xiongren Xiao Yuekun Chen Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China

ISBN: (纸本)9781479936311

A high-performance scheduling for a DAG (Directed Acyclic Graph) task graph on heterogeneous networked embedded systems or parallel and distributed systems is to maximize concurrency and minimize inter-processor communication. Most of the algorithms using upward rank value for task prioritizing and earliest finish time for processor assignment. But both approaches ignored the heterogeneity of system and could not create accurate and efficient schedules. Yet no one has doubled about and recognized that. A fully heterogeneous task scheduling algorithm is proposed to address the above problems in this paper. The fundamentals of DAG model and corresponding algorithms are investigated. New concepts called Heterogeneous Upward Rank Value (HURV) and Heterogeneous Priority Rank Value (HPRV) are defined. An algorithm called Heterogeneous Select Value (HSV) is proposed in paper. Both benchmark and extensive experimental evaluation demonstrate the significant improvements in proposed algorithm.

关键词： heterogeneous networked embedded systems heterogeneous upward rank value heterogeneous select value DAG

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Sequential channel selection for decentralized cognitive radio sensor network based on modified Q-Learning algorithm

Sequential channel selection for decentralized cognitive rad...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Fanzi Zeng Hanshan Liu Jisheng Xu Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China

Cognitive radio sensor network (CRSN) is a novel wireless sensor network, which can effectively alleviate the scarcity of spectrum resource by equipping the cognitive technology. Usually, CRSN deploys numerous sensor nodes around the monitoring area. But the energy and storage of those nodes are both limited. Compared with the centralized CRSN, we focus more on a decentralized situation without the control center or cluster in this paper, especially on a circumstance with few information exchanges among sensor nodes. In the case of that, our goal is to help each sensor node to find an optimal strategy of channel selection in the decentralized CRSN quickly, and then, we apply a Multi-Agent Best-Response Q-Learning algorithm based on Timesharing-Tracking Framework to sequential channel selection for the first time. The algorithm not only has a low storage cost, but also can overcome the poor convergence of strategy caused by Multi-Agent simultaneous learning. For comparison, the optimal channel assignment in centralized network, the Multi-Agent Independent Q-Learning and the Win-or-Learn-Fast Policy Hill Climbing these three algorithms are taken into account, and experimental data validates that our proposed algorithm is feasible in decentralized network.

关键词： Sensors Throughput Wireless sensor networks Convergence Algorithm design and analysis Cognitive radio Approximation algorithms

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A novel energy efficient cooperative spectrum sensing scheme for cognitive radio sensor network based on evolutionary game

A novel energy efficient cooperative spectrum sensing scheme...

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IEEE Workshop on Local and Metropolitan Area networks (LANMAN)

作者： Xiaolong Ma Fanzi Zeng Jisheng Xu Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China

ISBN: (纸本)9781467367639

In this paper, we focused on how to get CRs collaborate effectively as well as maximize energy savings in cognitive radio sensor network. We have established a model of evolutionary game between a cognitive sensors. In order to let cognitive sensors sense spectrum effectively, we designed a contribution-punishment mechanism, which can stimulate high SNR sensors to participate in spectrum sensing. Additionally, in order to reduce the wasted energy of sensors in idle, we introduced periodic sleep-listen mechanism. Finally, we simulated behavior dynamics for a 6-player polymorphic population game and compared our proposed scheme with non-periodic sleep-listen mechanism scheme. Result shows that our proposed scheme can stimulate high SNR sensors to participate in spectrum sensing effectively and can make the system more energy efficient.

关键词： Sensors Signal to noise ratio Games Sociology Statistics Energy consumption Energy efficiency

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