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IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING 2022年第2期7卷 371-385页

作者： Zhou, Zhou Li, Kenli Abawajy, Jemal Shojafar, Mohammad Chowdhury, Morshed Li, Fangmin Li, Keqin Hunan Univ Coll Informat Sci & Engn Changsha 410082 Hunan Peoples R China Changsha Univ Dept Comp Engn & Appl Math Changsha 410004 Hunan Peoples R China Deakin Univ Sch Informat Technol Geelong Vic 3216 Australia Univ Surrey Inst Commun Syst ICS GIC & 6GIC Guildford GU2 7XH Surrey England Changsha Univ Dept Math & Comp Sci Changsha 410004 Hunan Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Hunan Peoples R China SUNY Coll New Paltz Dept Comp Sci New Paltz NY 12561 USA

Virtualized networked datacenters (VNDCs) are gaining considerable attention for stochastic task execution under real-time constraints. However, the problem of efficiently minimizing the high energy consumption while ensuring high quality of service (QoS) in VNDCs has not been fully addressed. Although many solutions have been proposed to address this challenge, they are not efficient and only consider one or two of the energy consuming resources of VNDCs. To this end, an adaptive energy-aware algorithm, MCEC, that efficiently reduces the energy consumption of VNDCs while ensuring high QoS is proposed. Different from the existing approaches, the MCEC algorithm considers energy consumed by computing resources, virtual machine (VM) reconfiguration, communication resources and storage media resources while meeting user QoS requirements defined in the service level agreement (SLA). To validate the effectiveness of our algorithm, we carried out extensive experiments and compared the performance of our algorithm with existing baseline algorithms. The results of the experiments show that our algorithm substantially outperforms the baseline algorithms with respect to reducing energy consumption while respecting the service level agreement.

关键词： energy consumption Quality of service Resource management Virtualization Task analysis Servers Adaptation models Dynamic resource provisioning energy-aware algorithm optimization resource management virtualized networked datacenter (VNDC)

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Target-aware distributed coverage and connectivity algorithm for wireless sensor networks

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WIRELESS NETWORKS 2023年第4期29卷 1815-1830页

作者： Banoth, Sanjai Prasada Rao Donta, Praveen Kumar Amgoth, Tarachand MLR Inst Technol Dept Comp Sci & Engn Hyderabad 500043 Telangana India Indian Inst Technol Indian Sch Mines Dept Comp Sci & Engn Dhanbad India

One of the wireless sensor networks applications is to sense a discrete set of targets lying on the field and maintain connectivity with the sink for data transmission. In addition, it needs to minimize energy consumption to maximize the coverage lifetime. One such solution for coverage maximization is to group sensor nodes into cover sets. Each cover set remains active at a time to keep track of all the targets in the field until one of its active nodes depletes energy completely. Therefore, maximizing the number of cover sets and enhancing each set's coverage lifetime is a challenging issue. In this paper, we propose a new energy-aware algorithm for the coverage and connectivity of the sensor nodes. In the algorithm, we devise an energy-efficient strategy to maximize the number of cover sets and energy-aware connectivity. Extensive simulation runs show that the proposed algorithm outperforms the existing ones.

关键词： Wireless sensor networks Coverage and connectivity energy-aware algorithm Cover sets Coverage lifetime maximization

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A Lightweight Optimal Scheduling algorithm for energy-Efficient and Real-Time Cloud Services

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IEEE ACCESS 2022年 10卷 5697-5714页

作者： Sun, Joohyung Cho, Hyeonjoong Elect & Telecommun Res Inst Daejeon 34129 South Korea Korea Univ Dept Comp Convergence Software Sejong City 30019 South Korea

To support ever-chainging user needs such as large storage volumes, web search, and highperformance computing, numerous companies have expanded their systems to cloud computing servers. Cloud environment systems generally consume large amounts of electrical power, leading to tremendously high operational costs. In addition, they require computing infrastructures to run various real-time applications such as financial analysis, cloud gaming, and web-based real-time services. To represent performance guarantees, the negotiated agreements in real-time computing, expressed as deadline (or latency), can be specified by service level agreements of cloud services between users and cloud server providers. Thus, a number of research works have started focusing on reducing the energy consumption and simultaneously satisfying the temporal constraint in a cloud environment. Although we previously proposed an optimal real-time scheduling algorithm for multiprocessors, it is difficult to use it for cloud environments handling a large number of cloud services because of the high computational complexity of Omega(N-3 logN), where N is the number of tasks. Thus, we introduce a real-time task scheduling algorithm for cloud computing servers, which alleviates the computational complexity of O(N-2) from the complexity of the previous algorithm using a novel flow network-based optimization method. To the best of our knowledge, our scheduling algorithm in a cloud environment, which ensures optimality for real-time tasks and achieves energy savings using dynamic power management simultaneously, is the first in the problem domain. We show that the proposed scheduling algorithm guarantees an optimal schedule for real-time tasks and achieves energy savings simultaneously. Our experimental results show that the proposed algorithm outperforms the latest existing algorithms in terms of both time complexity and energy efficiency.

关键词： Cloud computing dynamic power management energy-aware algorithm flow network problem optimal scheduling real-time computing

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Flow Network-Based Real-Time Scheduling for Reducing Static energy Consumption on Multiprocessors

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IEEE ACCESS 2019年 7卷 1330-1344页

作者： Sun, Joohyung Cho, Hyeonjoong Easwaran, Arvind Park, Ju-Derk Choi, Byeong-Cheol Korea Univ Dept Comp Convergence Software Sejong 30019 South Korea Nanyang Technol Univ Sch Comp Sci & Engn Singapore 639798 Singapore ETRI Hyper Connected Commun Res Lab Daejeon 34129 South Korea

The energy management for embedded real-time systems is crucial due to their restricted power supplies. With the advancement of technologies, the static energy consumption of the embedded systems that is caused by their leakage power is growing. Thus, a number of research works have started focusing on reducing the static energy consumption by making the systems transit into low-power states, wherein some hardware components are temporarily shut down. Specifically, when a processor is idling, they attempt to set the processor into one of several low-power states. To make a processor remain in the low-power state as long as possible to minimize the energy consumption, the idle time should be maximally clustered. At the same time, in order to satisfy the real-time constraints of the tasks, the length of the clustered idle time should be estimated accurately. To achieve our objective, we propose energy-efficient real-time scheduling algorithms on symmetric homogeneous multiprocessors with a dynamic power management scheme for periodic real-time tasks. The proposed algorithms rely on a flow network model that effectively helps to cluster the idle time while respecting the real-time constraints. In our experimental evaluation, the proposed algorithms consume a comparable static energy to an existing off-line scheme that is the only suitable existing algorithm in the problem domain. Furthermore, we show that the proposed algorithms consume less static energy than the existing one in a case where the total workload of the given task set is low and the task completion is earlier than expected.

关键词： Dynamic power management energy-aware algorithm flow network problem multiprocessor unit micro-controller unit real-time scheduling

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Development of an Event-Priority-Driven Dissemination (EPDD) Management algorithm for Self-powered Sensor Node

Development of an Event-Priority-Driven Dissemination (EPDD)...

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IEEE International Conference on Sensors and Nanotechnology (SN)

作者： Abdal-Kadhim, Ali Mohammed Leong, Kok Swee Univ Tekn Malaysia Melaka Fak Kejuruteraan Elekt & Kejuruteraan Komputer CeTRI Melaka Malaysia

ISBN: (纸本)9781538656198

This paper introduces a novel energy-aware Event-Priority-Driven Dissemination EPDD algorithm for low-power wireless sensor node;targeted to overcome event trigger flaws when powered by dual source energy harvester. The EPDD algorithm functions to keep the sensor node in low-power mode to conserve energy, and will wake up only to update the base-station, but only limited to three main cases: 1) internal timer has expired, 2) power supply status change triggers an external interrupt, or 3) an event of interest is captured by an external interrupt. Thus, the base-station will always be aware about the sensor node issues, and should easily differentiate between a non-triggered node and a down node. The findings in this study prove that the proposed EPDD can lower the node power consumption more effectively compared to the data push algorithm, since it can operate for 22 hours longer than the data push. Moreover, the proposed EPDD outpaces the event trigger algorithm in the base-station awareness as it is able to detect the offline EPDD sensor node with 1.5 hours less operating time than the event trigger.

关键词： wireless sensor network energy-aware algorithm EPDD energy harvesting network integrity

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An energy-aware Data Offloading Scheme in Cloud Radio Access Networks

An Energy-Aware Data Offloading Scheme in Cloud Radio Access...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Chen, Yuh-Shyan Hsu, Chih-Shun Juang, Tong-Ying Lin, Hsin-Han Natl Taipei Univ Dept Comp Sci & Informat Engn Taipei Taiwan Shih Hsin Univ Dept Informat Management Taipei Taiwan

ISBN: (纸本)9781479984060

Mobile data offloading has become an important issue for mobile cellular network in recent years. Existing energy-aware data offloading scheme for mobile cellular network makes the offloading decision only according to the current local information of the user equipment (UE) and thus the UE cannot switch to a more efficient way to offload even other UEs have released their transmission resources later on. Hence, in this paper, a centralized offloading scheme based on cloud radio access networks (C-RAN) is proposed so as to make the offloading more efficient. The C-RAN based centralized offloading scheme considers all the situation of UEs of a baseband unit (BBU) at the same time and thus the BBU can do a better offloading decision for those UEs. At the beginning, each UE, who needs offloading, sends an offloading request to the BBU. When there is any UE released the transmission resource, the corresponding BBU will try to fulfill the pending offloading requests of the UEs. The corresponding BBU considers the pending UEs' transmission rate and energy consumption of the cellular network as well as the Wi-Fi network, and then makes offloading decisions for those UEs so as to save more energy and achieve higher throughput at the macroscopic level. Extensive simulations have been conducted to illustrate that the proposed energy-aware data offloading scheme can reduce the energy consumption and turnaround time, and enhance the transmission throughput.

关键词： C-RAN offloading heterogeneous network energy-aware algorithm energy-saving

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A Distributed Self-Healing algorithm for Virtual Backbone Construction and Maintenance in Wireless Sensor Networks

A Distributed Self-Healing Algorithm for Virtual Backbone Co...

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IEEE International Conference on Wireless for Space and Extreme Environments

作者： Al-Nabhan, Najla Al-Rodhaan, Mznah Al-Dhelaan, Abdullah King Saud Univ Dept Comp Sci Riyadh Saudi Arabia

ISBN: (纸本)9781479929597

Future Wireless Sensor Networks (WSNs) will be composed of a large number of densely deployed sensors. A key feature of such networks is that their nodes are untethered and unattended. Distributed techniques are expected in WSNs. Computing Connected Dominating Sets (CDSs) have been widely used for virtual backbone construction in WSNs to control topology, facilitate routing, and extend network lifetime. This paper proposes a new distributed algorithm for CDS construction in WSNs. The algorithm is intended to construct a CDS with the smallest ratio when compared to its centralized version. Moreover, this paper proposes a localized algorithm that efficiently maintains the backbone when some backbone nodes decide to enter the energy saving sleep mode. We attempt to prolong the lifetime of the constructed CDS by allowing nodes with higher residual energy to have more chances to be part of the constructed and maintained backbone. Simulation shows that our distributed approach has a maximum ratio of 1.53 to the centralized approach, and it satisfies all of the geometrical properties of its canalized version. Based on this ratio, this distributed algorithm has an approximation factor of 7.65 to the optimal CDS. To the best of our knowledge, this approximation is the smallest among all existing distributed CDS construction algorithms.

关键词： wireless sensor network energy-aware algorithm distributed algorithm virtual backbone connected dominating set

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