2019 IEEE Sustainability through ICT Summit (StICT)最新文献

The Impact of Inter-Virtual Machine Traffic on Energy Efficient Virtual Machines Placement 虚拟机间流量对节能虚拟机布局的影响

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-08-08 DOI: 10.1109/STICT.2019.8789381

Hatem A. Alharbi, T. El-Gorashi, A. Lawey, J. Elmirghani

引用次数: 5

Environmental Assessment of Fluctuating Residential Electricity Demand 住宅电力需求波动的环境评估

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-18 DOI: 10.1109/STICT.2019.8789377

Julien Walzberg, Thomas Dandres, Nicolas Merveille, M. Cheriet, R. Samson

{"title":"Environmental Assessment of Fluctuating Residential Electricity Demand","authors":"Julien Walzberg, Thomas Dandres, Nicolas Merveille, M. Cheriet, R. Samson","doi":"10.1109/STICT.2019.8789377","DOIUrl":"https://doi.org/10.1109/STICT.2019.8789377","url":null,"abstract":"Including dynamic aspects in the environmental assessment of power systems allows computing the environmental benefits of demand-side management strategies for the smart grid which could not be assessed with static data such as shifting part of the demand from one period to another. Several methodological approaches have been developed in life cycle assessment to account for dynamic aspects, but none has given much attention to the demand side of the equation. However, demand is also prone to fluctuate in time and its misrepresentation may lead to additional errors. In this study, a stochastic approach was applied to model the fluctuating residential power demand of Canadians' homes. An hourly and a yearly average electricity mix were then used to compute the environmental impacts of the hourly or yearly average homes' electricity demand. Finally, an approach combining an average and a marginal hourly electricity mix was then proposed to assess the benefits of a simple demand side management strategy: the shifting of homes' dryers loads up to two hours later than usual. Results show that assuming a constant demand or electricity mix both leads to errors which may be as high as 150% depending on the period of the month assessed. Moreover, using an hourly average electricity mix to set up the demand side strategy increases climate change impact by 0.6% whereas using a marginal mix decreases climate change impact by 10%.","PeriodicalId":209175,"journal":{"name":"2019 IEEE Sustainability through ICT Summit (StICT)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123496331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Testbed for Adaptive Microphones in Ultra-Low-Power Systems 超低功耗系统中自适应麦克风的测试平台

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-18 DOI: 10.1109/STICT.2019.8789373

Evan Fallis, Mark Lipski, Andrew Mackey, Marc Jayson Baucas, M. James, P. Spachos, S. Gregori

引用次数: 5

A new routing metric for real-time applications in smart cities 智能城市实时应用的新路由度量

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-18 DOI: 10.1109/STICT.2019.8789379

Lamia Elgaroui, S. Chamberland, S. Pierre

{"title":"A new routing metric for real-time applications in smart cities","authors":"Lamia Elgaroui, S. Chamberland, S. Pierre","doi":"10.1109/STICT.2019.8789379","DOIUrl":"https://doi.org/10.1109/STICT.2019.8789379","url":null,"abstract":"Many interconnected smart devices manage and control different areas in cities using information and communication technologies. Such networked devices, exchanging information through real-time applications, are characterized by their high mobility, which require developing optimized routing metrics. In the literature, several solutions are proposed to solve such an information routing problem. Most of them use many network parameters in routing metrics calculation, such as the node position, the node speed, the link quality and the network density. However, the existing routing solutions may require combining simultaneously the end to end delay, the packet loss and the distance. This adds more efficiency in data transmission since the realtime applications require no packet loss and less delay. In this paper, we consider these parameters to propose a mathematical modeling of new multicriteria routing metric. Subsequently, we solve it with three different methods: exact method, A star method and A star with obstacles method. The simulation results show the efficiency of the A star method in terms of response time and iteration number.","PeriodicalId":209175,"journal":{"name":"2019 IEEE Sustainability through ICT Summit (StICT)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124006856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

[Copyright notice] (版权)

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-01 DOI: 10.1109/stict.2019.8789366

引用次数: 0

Energy Efficient Bike-Share Tracking System with BLE Beacons and LoRa Technology 基于BLE信标和LoRa技术的节能共享单车跟踪系统

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-01 DOI: 10.1109/STICT.2019.8789372

Andrew Mackey, P. Spachos, S. Gregori

{"title":"Energy Efficient Bike-Share Tracking System with BLE Beacons and LoRa Technology","authors":"Andrew Mackey, P. Spachos, S. Gregori","doi":"10.1109/STICT.2019.8789372","DOIUrl":"https://doi.org/10.1109/STICT.2019.8789372","url":null,"abstract":"Around the world, vast improvements in public transportation methods in urban environments have been made. However, in densely populated areas, the bicycle remains a very useful means of transportation. Its small size and minimal environmental impact are the critical factors that maintain its relevance. Moreover, the advancement of connected devices and sharing-based services have allowed private vendors to develop bike-sharing programs, giving millions access to bike transportation around the globe. These bike-sharing programs rely on the user to check out and return the bike to a designated bike-holding station. With the growth of Internet of Things (IoT) services and wirelessly connected devices, there is a major benefit in enabling vendors to track their bicycle assets. Satellite navigation has come a long way, however, it requires a large power overhead. This paper proposes an energy-efficient bicycle tracking system that utilizes bicycle powered Bluetooth Low Energy (BLE) beacons and Long Range (LoRa) type base-stations in order to track and maintain a real-time location-based inventory of all assets. The BLE beacons are used to track individual bicycle assets based on Received Signal Strength Indicator (RSSI) proximity and the LoRa base stations exploit longer range communication capabilities to transmit asset location information between each other, for added management capabilities. Preliminary proximity estimations using BLE beacons in an urban outdoor environment show promising results with proximity accuracy consistently under 2 meters.","PeriodicalId":209175,"journal":{"name":"2019 IEEE Sustainability through ICT Summit (StICT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127465717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Considering the temporal variability of power generation in the assessment of ICT emissions: presentation of the IEEE 1922.2 standard draft 在ICT排放评估中考虑发电的时间变异性:IEEE 1922.2标准草案的介绍

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-01 DOI: 10.1109/STICT.2019.8789371

Thomas Dandres, A. C. Riekstin, M. Cheriet

{"title":"Considering the temporal variability of power generation in the assessment of ICT emissions: presentation of the IEEE 1922.2 standard draft","authors":"Thomas Dandres, A. C. Riekstin, M. Cheriet","doi":"10.1109/STICT.2019.8789371","DOIUrl":"https://doi.org/10.1109/STICT.2019.8789371","url":null,"abstract":"A large fraction of the ICT life cycle impacts are related to the ICT use phase because of electricity consumption. Environmental evaluations of the ICT sector suggests that this sector contributes now to 3% of the global anthropic greenhouse gas (GHG) emissions. It is anticipated that ICT could be used to mitigate the GHG emissions of the other sectors by 12% by 2030. These numbers are however uncertain due to simplifications made in the emission assessment. Especially, the use of annual average emission factors to model the GHG emissions related to the ICT electricity consumption that varies in time is expected to be a large source of uncertainty on the ICT emission assessment. Therefore, in this paper, we present the proposed IEEE 1922.2 standard to include the temporal variation of the power generation and electricity consumption in the computing of ICT emissions. The methodological framework is developed around a series of scopes and considerations to cover most of the situations that could be encountered when assessing ICT emissions. Consequently, the standard is flexible and methodological choices must be made by the user according to its context. Such choices must then be reported and documented to ensure the robustness and transparency of the ICT emission calculation.","PeriodicalId":209175,"journal":{"name":"2019 IEEE Sustainability through ICT Summit (StICT)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126035625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Greening The Network Using Traffic Prediction and Link Rate Adaptation 利用流量预测和链路速率自适应实现网络绿化

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-01 DOI: 10.1109/STICT.2019.8789375

A. Bayati, K. Nguyen, M. Cheriet

引用次数: 1

Power Consumption and Delay in Wired Parts of Fog Computing Networks 雾计算网络有线部分的功耗和延迟

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-01 DOI: 10.1109/STICT.2019.8789374

Bartosz Kopras, F. Idzikowski, P. Kryszkiewicz

{"title":"Power Consumption and Delay in Wired Parts of Fog Computing Networks","authors":"Bartosz Kopras, F. Idzikowski, P. Kryszkiewicz","doi":"10.1109/STICT.2019.8789374","DOIUrl":"https://doi.org/10.1109/STICT.2019.8789374","url":null,"abstract":"In the last decade Cloud computing has seen a surge of popularity. Clouds, with their scale and high functionality, are used to outsource various infrastructure, platform, and software services. However, relaying solely on distant Cloud Data Centers (DCs) can be inefficient for many applications concerning mobile devices and Internet of Things (IoT) in general. A more decentralized Fog computing paradigm has been proposed to augment Cloud availability and execution. This work addresses latency and power consumption in Fog computing networks. Models for power consumption and delay are proposed. Performance of Fog computing is estimated using parameters setting based on real-world equipment and traffic. Our results tackle the balance between Fog and Cloud. Applications requiring heavy computations (relative to size of offloaded data) are best served by Cloud DCs, while it is faster (and more power-efficient) to compute “lighter” requests in the Fog Nodes (FNs). However, where is the trade-off between power consumption and delay in the context of Fog and Cloud? We answer this question modeling multiple architectures and using various network scenarios.","PeriodicalId":209175,"journal":{"name":"2019 IEEE Sustainability through ICT Summit (StICT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133324364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

ALTM: Adaptive learning-based thermal model for temperature predictions in data centers ALTM:用于数据中心温度预测的基于自适应学习的热模型

2019 IEEE Sustainability through ICT Summit (StICT) Pub Date : 2019-06-01 DOI: 10.1109/STICT.2019.8789370

SeyedMorteza MirhoseiniNejad, Fernando Martinez-Garcia, Ghada H. Badawy, D. Down

{"title":"ALTM: Adaptive learning-based thermal model for temperature predictions in data centers","authors":"SeyedMorteza MirhoseiniNejad, Fernando Martinez-Garcia, Ghada H. Badawy, D. Down","doi":"10.1109/STICT.2019.8789370","DOIUrl":"https://doi.org/10.1109/STICT.2019.8789370","url":null,"abstract":"To design effective control schemes for energy efficiency in data centers, it is crucial to have a thermal model of the system. Constructing thermal models of data centers for temperature prediction is extremely challenging, due to inherent complexity. Computational fluid dynamics (CFD) simulations or physical heat transfer equations are conventionally used to construct such thermal models. More recent approaches combine physical heat transfer rules and data-driven methods in an effort to obtain more accurate models. Our proposed adaptive learning-based thermal model (ALTM) is fast, adapts to thermal changes in the data center environment, and does not require prior knowledge of heat transfer rules between data center entities. Unlike other methods, ALTM is a holistic thermal model that predicts temperature of critical zones using data center operational variables as inputs. The operational variables are the controllable parameters and easily obtained measurements from IT and cooling units. A key use case for ALTM is that it can be effectively used for thermal-aware workload schedulers or cooling system controllers. Our results confirm the accuracy and adaptability of the model.","PeriodicalId":209175,"journal":{"name":"2019 IEEE Sustainability through ICT Summit (StICT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133665587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8