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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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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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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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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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Fairness-aware resource allocation in OFDM-based cognitive radio networks for energy efficiency

Fairness-aware resource allocation in OFDM-based cognitive r...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

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

ISBN: (纸本)9781509040940

In this paper, we presented a fairness-aware scheduling scheme in OFDM-based cognitive radio networks. Our objective is to maximize the systems energy efficiency while maintain the fairness among secondary users. In addition, many factors will be considered such as the channel quality, the interferences taken to the primary system and the total transmission power of the cognitive radio system. The resource allocation process consists of two steps. First, we use an improved heuristic algorithm to assign subcarriers to secondary users and then use an iterative algorithm to distribute power to each subcarrier. Simulation results demonstrate that our scheme is able to gain a higher level for energy efficiency and guarantee the minimum transmission requirements of secondary users.

关键词： Resource management Heuristic algorithms Interference OFDM Quality of service Cognitive radio Iterative methods

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A Power Model Combined of Architectural Level and Gate Level for Multicore Processors

A Power Model Combined of Architectural Level and Gate Level...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Manman Peng Yan Hu Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China

ISBN: (纸本)9781479914449

Low power consumption is becoming a critical factor for multicore processors. As the multicore processor design complexity increases, power estimation for multicore processors has gained more importance. This paper presents a new power model combined of architectural level and gate level for multicore processors. The model maps the multicore processors to a combination of building blocks, and estimates the gate-level power of these blocks using parameterized RTL. Then, the power numbers are made in the form of look-up tables, and integrated in architecture simulators. The experiments show that for peak power estimation, an excellent accuracy has been reached and simulation performance is greatly improved compared to the gate level.

关键词： Program processors Computational modeling Multicore processing Logic gates Random access memory Hardware Analytical models

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The EDF with Dual Virtual Deadline Algorithm for Mixed Criticality Task System

The EDF with Dual Virtual Deadline Algorithm for Mixed Criti...

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Lining Zeng Cheng Xu Renfa Li Key Laboratory for Embedded and Network Computing Hunan University Changsha Hunan Province China

ISBN: (纸本)9781538665664;9781538665657

In the area of real-time embedded systems, one of the hot topics is scheduling the mixed-criticality tasks to execute the LO tasks better when guaranteeing the correctness of HI tasks. In this paper, we research the schedule mechanism for dual-criticality tasks. Firstly, we modify the correctness condition of MC scheduling. Then, we present an optimized MC scheduling algorithm EDF -DVD, which assigns scale factors for both HI jobs and LO jobs. We analyze the different situation based on system utilizetion and present the strategy of calculating the value of scale factor corresponding to the utilization. The experiments show that our mechanism has better performance in scheduling the dual-criticality tasks.

关键词： Task analysis Schedules Scheduling embedded systems Switches Scheduling algorithms Real-time systems

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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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Schedule length minimization of parallel applications with energy consumption constraints using heuristics on heterogeneous distributed systems

Schedule length minimization of parallel applications with e...

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作者： Xie, Guoqi Xiao, Xiongren Li, Renfa Li, Keqin College of Computer Science and Electronic Engineering Hunan University Changsha China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China Department of Computer Science State University of New York AlbanyNY United States

Energy consumption is one of the primary design constraints in heterogeneous parallel and distributed systems ranging from small embedded devices to large-scale data centers. The problem of minimizing the schedule length of an energy consumption-constrained parallel application has been studied recently in homogeneous systems with a shared memory. To adopt the heterogeneity and distribution of high-performance computing systems, this study solves the problem of minimizing the schedule length of an energy consumption-constrained parallel application in heterogeneous distributed systems based on a dynamic voltage and frequency scaling energy-efficient design technique. The aforementioned problem is divided into 2 subproblems in this study, namely, satisfying energy consumption constraint and minimizing schedule length. The first subproblem is solved by transferring the energy consumption constraint of the application to that of each task, whereas the second subproblem is solved by heuristically scheduling each task with low time complexity. Experiments using both fast Fourier transform and Gaussian elimination parallel applications show that the actual energy consumption values do not always exceed but are close to the given energy consumption constraints. In addition, the minimum schedule lengths are generated using the proposed algorithm. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Energy utilization

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