C. D. Donne, K. Yıldırım, Amjad Yousef Majid, Josiah D. Hester, P. Pawełczak
Backscatter has emerged as the dominant paradigm for battery-free networking among the (potentially) trillions of devices in the future Internet of Things, partly because of the order of magnitude smaller energy consumption, but at the cost of collisions, low data rates, and short distances. This position paper explores the alternative approach: using low power, yet active radios to communicate among the battery-less swarm. We describe the challenges of using active radios in this context, including lack of tight time guarantees, high listening costs, and intermittent operation. While backscatter is promising, this paper hopes to broaden the conversation around alternative methods for networking the future IoT.
{"title":"Backing out of backscatter for intermittent wireless networks","authors":"C. D. Donne, K. Yıldırım, Amjad Yousef Majid, Josiah D. Hester, P. Pawełczak","doi":"10.1145/3279755.3279758","DOIUrl":"https://doi.org/10.1145/3279755.3279758","url":null,"abstract":"Backscatter has emerged as the dominant paradigm for battery-free networking among the (potentially) trillions of devices in the future Internet of Things, partly because of the order of magnitude smaller energy consumption, but at the cost of collisions, low data rates, and short distances. This position paper explores the alternative approach: using low power, yet active radios to communicate among the battery-less swarm. We describe the challenges of using active radios in this context, including lack of tight time guarantees, high listening costs, and intermittent operation. While backscatter is promising, this paper hopes to broaden the conversation around alternative methods for networking the future IoT.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122280636","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}
Tongda Wu, Lefan Zhang, Huazhong Yang, Yongpan Liu
Energy harvesting is an alternative to achieve maintenance-free IoT devices. However, the intermittent and low-intensity ambient power supply poses a great challenge to guarantee the quality of service (QoS) of these applications. Adequate QoS simulation is required to evaluate the system design before deployment. Unfortunately, existing simulators lack supports on neither system-level behaviors under power failure circumstances nor the modeling mechanism for peripheral functionality and energy-related parameters. This paper proposes a system-level simulator named AES to evaluate and assist the intermittently-powered system (IPS) design. Adopting a flexible energy message handling framework and an easily-configured virtual device interface, AES supports both functionality and energy-related behavior simulation of all hardware modules under intermittent power scenarios. A hardware prototype is established and validates that the deviation of AES is less than 6.4%, which is adequate for IoT applications. With AES, this paper also explores the impact and design space of the system parameters in an IPS and provides a group of design guidelines to improve the performance by 37.2% in average, which reveals the potential of AES on IPS design.
{"title":"An extensible system simulator for intermittently-powered multiple-peripheral IoT devices","authors":"Tongda Wu, Lefan Zhang, Huazhong Yang, Yongpan Liu","doi":"10.1145/3279755.3279756","DOIUrl":"https://doi.org/10.1145/3279755.3279756","url":null,"abstract":"Energy harvesting is an alternative to achieve maintenance-free IoT devices. However, the intermittent and low-intensity ambient power supply poses a great challenge to guarantee the quality of service (QoS) of these applications. Adequate QoS simulation is required to evaluate the system design before deployment. Unfortunately, existing simulators lack supports on neither system-level behaviors under power failure circumstances nor the modeling mechanism for peripheral functionality and energy-related parameters. This paper proposes a system-level simulator named AES to evaluate and assist the intermittently-powered system (IPS) design. Adopting a flexible energy message handling framework and an easily-configured virtual device interface, AES supports both functionality and energy-related behavior simulation of all hardware modules under intermittent power scenarios. A hardware prototype is established and validates that the deviation of AES is less than 6.4%, which is adequate for IoT applications. With AES, this paper also explores the impact and design space of the system parameters in an IPS and provides a group of design guidelines to improve the performance by 37.2% in average, which reveals the potential of AES on IPS design.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128942283","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}
For the past decade, the status-quo for energy harvesting sensors has been to buffer small amounts of energy in capacitors to intermittently work through a sensing task. While using capacitors for storage offers these systems indefinite lifetime, it comes at a cost - they must tolerate the decreased availability, lower energy utilization, and more complex programming models inherent to a volatile, intermittent design. We argue that many of these problems stem from insufficient energy storage and could be eliminated with the use of batteries. Recent advances in rechargeable battery technology weaken the historical arguments against their use. We believe that using batteries in energy harvesting sensors will push us closer to a class of reliable, general purpose devices that can better serve human-centric sensing applications than their capacitor-based counterparts at the cost of having a finite, but long, lifetime.
{"title":"Reconsidering batteries in energy harvesting sensing","authors":"Neal Jackson, Joshua Adkins, P. Dutta","doi":"10.1145/3279755.3279757","DOIUrl":"https://doi.org/10.1145/3279755.3279757","url":null,"abstract":"For the past decade, the status-quo for energy harvesting sensors has been to buffer small amounts of energy in capacitors to intermittently work through a sensing task. While using capacitors for storage offers these systems indefinite lifetime, it comes at a cost - they must tolerate the decreased availability, lower energy utilization, and more complex programming models inherent to a volatile, intermittent design. We argue that many of these problems stem from insufficient energy storage and could be eliminated with the use of batteries. Recent advances in rechargeable battery technology weaken the historical arguments against their use. We believe that using batteries in energy harvesting sensors will push us closer to a class of reliable, general purpose devices that can better serve human-centric sensing applications than their capacitor-based counterparts at the cost of having a finite, but long, lifetime.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126473759","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}
Batteryless, energy harvesting sensing devices enable new applications and deployment scenarios with their promise of zero maintenance, long lifetime, and small size. These devices fail often and for variable lengths of time because of the unpredictability of the energy harvesting source; be it solar, thermal, RF, or kinetic, making prediction and planning difficult. This paper explores ways to make sense of energy harvesting behaviors. We take known energy harvesting datasets, and create a few of our own, then classify energy harvesting behavior into modes. Modes are periodic or repeated elements caused by systematic or fundamental attributes of the energy harvesting environment. We show the existence of these Energy Harvesting Modes using real world data and IV surfaces created with the Ekho emulator, and then discuss how this powerful abstraction could increase robustness and efficiency of design and development on intermittently powered and energy harvesting computing devices.
{"title":"Making sense of intermittent energy harvesting","authors":"A. Bakar, Josiah D. Hester","doi":"10.1145/3279755.3279762","DOIUrl":"https://doi.org/10.1145/3279755.3279762","url":null,"abstract":"Batteryless, energy harvesting sensing devices enable new applications and deployment scenarios with their promise of zero maintenance, long lifetime, and small size. These devices fail often and for variable lengths of time because of the unpredictability of the energy harvesting source; be it solar, thermal, RF, or kinetic, making prediction and planning difficult. This paper explores ways to make sense of energy harvesting behaviors. We take known energy harvesting datasets, and create a few of our own, then classify energy harvesting behavior into modes. Modes are periodic or repeated elements caused by systematic or fundamental attributes of the energy harvesting environment. We show the existence of these Energy Harvesting Modes using real world data and IV surfaces created with the Ekho emulator, and then discuss how this powerful abstraction could increase robustness and efficiency of design and development on intermittently powered and energy harvesting computing devices.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"1287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116488197","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}
Dimitris Patoukas, K. Yıldırım, Amjad Yousef Majid, Josiah D. Hester, P. Pawełczak
Energy harvesting and battery-free sensing devices show great promise for revolutionizing computing in the home, in the wild, and on the body. The promise of cheap, dense, and ubiquitous sensing technology brings new applications for the Internet of Things. However, the future programming model is blurry and complex. With a potential for trillions of devices, and thousands of devices per person on earth, programming languages and associated operating systems must be usable, flexible, and resource efficient. Because of the thousands of applications and fine grained differences in requirements, multi-tenancy may be a part of the solution to solving this programming model crisis. This paper explores the energy and resources costs, feasibility, and motivation for multi-tenancy on these tiniest of computing devices---namely the difficulties in scheduling tasks fairly, efficiently, and simply. Because of intermittent power, resources and energy must be mostly devoted towards user tasks, we implement a rudimentary operating system with low overhead to conduct experiments and test time-sharing and scheduling protocols. We close with a discussion on challenges to implementing a multi-tenant run-time on battery-free tags, and proposals for future work.
{"title":"Feasibility of multi-tenancy on intermittent power","authors":"Dimitris Patoukas, K. Yıldırım, Amjad Yousef Majid, Josiah D. Hester, P. Pawełczak","doi":"10.1145/3279755.3279761","DOIUrl":"https://doi.org/10.1145/3279755.3279761","url":null,"abstract":"Energy harvesting and battery-free sensing devices show great promise for revolutionizing computing in the home, in the wild, and on the body. The promise of cheap, dense, and ubiquitous sensing technology brings new applications for the Internet of Things. However, the future programming model is blurry and complex. With a potential for trillions of devices, and thousands of devices per person on earth, programming languages and associated operating systems must be usable, flexible, and resource efficient. Because of the thousands of applications and fine grained differences in requirements, multi-tenancy may be a part of the solution to solving this programming model crisis. This paper explores the energy and resources costs, feasibility, and motivation for multi-tenancy on these tiniest of computing devices---namely the difficulties in scheduling tasks fairly, efficiently, and simply. Because of intermittent power, resources and energy must be mostly devoted towards user tasks, we implement a rudimentary operating system with low overhead to conduct experiments and test time-sharing and scheduling protocols. We close with a discussion on challenges to implementing a multi-tenant run-time on battery-free tags, and proposals for future work.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"72 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128475546","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}
Sivert T. Sliper, Domenico Balsamo, A. Weddell, G. Merrett
Intermittent computing is a new paradigm enabling battery-less computing devices to be powered directly from energy harvesting, enabling IoT devices that are free from the cost, size and lifetime constraints of batteries. To cope with frequent power interruptions, intermittent computing systems save computational progress before power is lost, and restore it when power returns. Recent research in power-neutral operation of multiprocessor system-on-chips (MPSoCs), where performance scaling is used to instantaneously match power consumption with supply, motivates the need for intermittent computing on high-performance systems. Existing works provide solutions for microcontrollers, but with the increased complexity of high-performance SoCs, new challenges such as hierarchical memory and dependence on large existing libraries emerge. In this paper, we provide a taxonomy of published intermittent computing methods and identify the most suitable method for high-performance SoCs. The chosen method is then implemented and experimentally validated on an Arm A9 out-of-order application processor. Results show that state can be saved/restored correctly in 8.6 ms for a minimal bare-metal application, which is an order of magnitude faster than the platform's hardware boot time.
{"title":"Enabling intermittent computing on high-performance out-of-order processors","authors":"Sivert T. Sliper, Domenico Balsamo, A. Weddell, G. Merrett","doi":"10.1145/3279755.3279759","DOIUrl":"https://doi.org/10.1145/3279755.3279759","url":null,"abstract":"Intermittent computing is a new paradigm enabling battery-less computing devices to be powered directly from energy harvesting, enabling IoT devices that are free from the cost, size and lifetime constraints of batteries. To cope with frequent power interruptions, intermittent computing systems save computational progress before power is lost, and restore it when power returns. Recent research in power-neutral operation of multiprocessor system-on-chips (MPSoCs), where performance scaling is used to instantaneously match power consumption with supply, motivates the need for intermittent computing on high-performance systems. Existing works provide solutions for microcontrollers, but with the increased complexity of high-performance SoCs, new challenges such as hierarchical memory and dependence on large existing libraries emerge. In this paper, we provide a taxonomy of published intermittent computing methods and identify the most suitable method for high-performance SoCs. The chosen method is then implemented and experimentally validated on an Arm A9 out-of-order application processor. Results show that state can be saved/restored correctly in 8.6 ms for a minimal bare-metal application, which is an order of magnitude faster than the platform's hardware boot time.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129572849","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}
Francesco Fraternali, Bharathan Balaji, Rajesh E. Gupta
With the advent of the Internet of Things (IoT), an increasing number of energy harvesting methods are being used to supplement or supplant battery based sensors. Energy harvesting sensors need to be configured according to the application, hardware, and environmental conditions to maximize their usefulness. As of today, the configuration of sensors is either manual or heuristics based, requiring valuable domain expertise. Reinforcement learning (RL) is a promising approach to automate configuration and efficiently scale IoT deployments, but it is not yet adopted in practice. We propose solutions to bridge this gap: reduce the training phase of RL so that nodes are operational within a short time after deployment and reduce the computational requirements to scale to large deployments. We focus on configuration of the sampling rate of indoor solar panel based energy harvesting sensors. We created a simulator based on 3 months of data collected from 5 sensor nodes subject to different lighting conditions. Our simulation results show that RL can effectively learn energy availability patterns and configure the sampling rate of the sensor nodes to maximize the sensing data while ensuring that energy storage is not depleted. The nodes can be operational within the first day by using our methods. We show that it is possible to reduce the number of RL policies by using a single policy for nodes that share similar lighting conditions.
{"title":"Scaling configuration of energy harvesting sensors with reinforcement learning","authors":"Francesco Fraternali, Bharathan Balaji, Rajesh E. Gupta","doi":"10.1145/3279755.3279760","DOIUrl":"https://doi.org/10.1145/3279755.3279760","url":null,"abstract":"With the advent of the Internet of Things (IoT), an increasing number of energy harvesting methods are being used to supplement or supplant battery based sensors. Energy harvesting sensors need to be configured according to the application, hardware, and environmental conditions to maximize their usefulness. As of today, the configuration of sensors is either manual or heuristics based, requiring valuable domain expertise. Reinforcement learning (RL) is a promising approach to automate configuration and efficiently scale IoT deployments, but it is not yet adopted in practice. We propose solutions to bridge this gap: reduce the training phase of RL so that nodes are operational within a short time after deployment and reduce the computational requirements to scale to large deployments. We focus on configuration of the sampling rate of indoor solar panel based energy harvesting sensors. We created a simulator based on 3 months of data collected from 5 sensor nodes subject to different lighting conditions. Our simulation results show that RL can effectively learn energy availability patterns and configure the sampling rate of the sensor nodes to maximize the sensing data while ensuring that energy storage is not depleted. The nodes can be operational within the first day by using our methods. We show that it is possible to reduce the number of RL policies by using a single policy for nodes that share similar lighting conditions.","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117094332","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}
{"title":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","authors":"G. Merrett, C. Renner, D. Brunelli","doi":"10.1145/3279755","DOIUrl":"https://doi.org/10.1145/3279755","url":null,"abstract":"","PeriodicalId":376211,"journal":{"name":"Proceedings of the 6th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116856574","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：