Ahmad H. Dehwah, S. B. Taieb, J. Shamma, C. Claudel
Solar powered wireless sensor networks are very adapted to smart city applications, since they can operate for extended durations with minimal installation costs. Nonetheless, they require energy management schemes to operate reliably, unlike their grid-powered counterparts. Such schemes require the forecasting of future solar power inputs for each wireless sensor node, over a time horizon. They also require the determination of battery energy parameters in real time. To address both requirements, we propose a collaborative solar power forecasting framework combined to a real time battery capacity estimation model, which can be used to optimize the node schedules over the corresponding horizon.
{"title":"Decentralized Energy and Power Estimation in Solar-Powered Wireless Sensor Networks","authors":"Ahmad H. Dehwah, S. B. Taieb, J. Shamma, C. Claudel","doi":"10.1109/DCOSS.2015.18","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.18","url":null,"abstract":"Solar powered wireless sensor networks are very adapted to smart city applications, since they can operate for extended durations with minimal installation costs. Nonetheless, they require energy management schemes to operate reliably, unlike their grid-powered counterparts. Such schemes require the forecasting of future solar power inputs for each wireless sensor node, over a time horizon. They also require the determination of battery energy parameters in real time. To address both requirements, we propose a collaborative solar power forecasting framework combined to a real time battery capacity estimation model, which can be used to optimize the node schedules over the corresponding horizon.","PeriodicalId":332746,"journal":{"name":"2015 International Conference on Distributed Computing in Sensor Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131670424","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}
Many real-world wireless sensor network applications such as environmental monitoring, structural health monitoring, and smart grid can be formulated as a least-squares problem. In distributed Cyber-Physical System (CPS), each sensor node observes partial phenomena due to spatial and temporal restriction and is able to form only partial rows of least-squares. Traditionally, these partial measurements were gathered at a centralized location. However, with the increase in sensors and their measurements, aggregation is becoming challenging and infeasible. In this paper, we propose distributed randomized kaczmarz that performs in-network computation to solve least-squares over the network by avoiding costly communication. As a case study, we present a volcano monitoring application on a distributed CORE emulator and use real data from Mt. St. Helens to evaluate our proposed method.
{"title":"Distributed Randomized Kaczmarz and Applications to Seismic Imaging in Sensor Network","authors":"Goutham Kamath, P. Ramanan, Wenzhan Song","doi":"10.1109/DCOSS.2015.27","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.27","url":null,"abstract":"Many real-world wireless sensor network applications such as environmental monitoring, structural health monitoring, and smart grid can be formulated as a least-squares problem. In distributed Cyber-Physical System (CPS), each sensor node observes partial phenomena due to spatial and temporal restriction and is able to form only partial rows of least-squares. Traditionally, these partial measurements were gathered at a centralized location. However, with the increase in sensors and their measurements, aggregation is becoming challenging and infeasible. In this paper, we propose distributed randomized kaczmarz that performs in-network computation to solve least-squares over the network by avoiding costly communication. As a case study, we present a volcano monitoring application on a distributed CORE emulator and use real data from Mt. St. Helens to evaluate our proposed method.","PeriodicalId":332746,"journal":{"name":"2015 International Conference on Distributed Computing in Sensor Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127475551","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}
The Internet of Things has enabled important applications such as traceability in food manufacturing, processing, distribution and disposal. However, different visions of this new paradigm have contributed to the emergence of architectures that include not widely quality attributes. Thus, this work proposes an architecture based on Internet of Things for traceability in the context of agribusiness which greatly admire the architecture quality attributes. The standard 25000 of the International Organization for Standardization is used as a parameter for setting the attributes of quality, technical visits will be held at a winery into a major wine producing regions of Brazil to requirements analysis and scenarios for using the architecture are simulated for validation of the proposal. We expect to achieve an architecture traceability scalable, secure, reliable and available to support the development of wine traceability applications from production to disposal.
{"title":"Towards an IoT-Based Architecture for Wine Traceability","authors":"L. B. Campos, C. Cugnasca","doi":"10.1109/DCOSS.2015.31","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.31","url":null,"abstract":"The Internet of Things has enabled important applications such as traceability in food manufacturing, processing, distribution and disposal. However, different visions of this new paradigm have contributed to the emergence of architectures that include not widely quality attributes. Thus, this work proposes an architecture based on Internet of Things for traceability in the context of agribusiness which greatly admire the architecture quality attributes. The standard 25000 of the International Organization for Standardization is used as a parameter for setting the attributes of quality, technical visits will be held at a winery into a major wine producing regions of Brazil to requirements analysis and scenarios for using the architecture are simulated for validation of the proposal. We expect to achieve an architecture traceability scalable, secure, reliable and available to support the development of wine traceability applications from production to disposal.","PeriodicalId":332746,"journal":{"name":"2015 International Conference on Distributed Computing in Sensor Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126789893","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}
Wireless Sensor Networks performing low-power data collection often suffer from uneven load distribution among nodes. Nodes close to the network root typically face a higher load, see their battery deplete first, and become prematurely unable to operate (both sensing and relaying other nodes' data). We argue that opportunistic routing, by making forwarding decision on a per-packet basis and at the receiver rather than the sender, has the potential to better balance the load across nodes. We extend ORPL, an opportunistic version of the standard routing protocol RPL, with support for load-balancing. In our protocol, ORPL-LB, nodes continuously adapt their wake-up interval in order to adjust their availability and attain a deployment-specific target duty cycle. We implement our protocol in Contikiand present our experimental validation in Indriya, a 93-nodestestbed. Our results show that ORPL-LB reduces significantly(by approximately 40%) the worst node's duty cycle, with little or no impact on packet delivery ratio and latency.
{"title":"Load-Balanced Data Collection through Opportunistic Routing","authors":"M. Michel, S. Duquennoy, B. Quoitin, T. Voigt","doi":"10.1109/DCOSS.2015.10","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.10","url":null,"abstract":"Wireless Sensor Networks performing low-power data collection often suffer from uneven load distribution among nodes. Nodes close to the network root typically face a higher load, see their battery deplete first, and become prematurely unable to operate (both sensing and relaying other nodes' data). We argue that opportunistic routing, by making forwarding decision on a per-packet basis and at the receiver rather than the sender, has the potential to better balance the load across nodes. We extend ORPL, an opportunistic version of the standard routing protocol RPL, with support for load-balancing. In our protocol, ORPL-LB, nodes continuously adapt their wake-up interval in order to adjust their availability and attain a deployment-specific target duty cycle. We implement our protocol in Contikiand present our experimental validation in Indriya, a 93-nodestestbed. Our results show that ORPL-LB reduces significantly(by approximately 40%) the worst node's duty cycle, with little or no impact on packet delivery ratio and latency.","PeriodicalId":332746,"journal":{"name":"2015 International Conference on Distributed Computing in Sensor Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127760580","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}
R. Vasconcelos, L. E. Talavera, I. Vasconcelos, Marcos Roriz, M. Endler, B. Gomes, F. Silva
The current ubiquity of smart phones with mobile Internet and several short-range wireless interfaces (NFC, Bluetooth, Bluetooth Smart) and the fact that these devices are carried almost anytime and anywhere by users, enables potentially new pervasive sensing applications where smartphones can act as universal hubs for interaction with sensors (or sensor networks) that have only short-range wireless connectivity. Thus, in next years we can expect an increasing number of long-term and large-scale deployments for various crowd-sourced monitoring applications, such as environment monitoring, domestic utility meter reading, urban monitoring, etc. In this paper, we present the implementation and initial performance results with our mobile-cloud middleware that enables such opportunistic mobile sensing. One of the singular features of our middleware is the capability to discover, dynamically download and install sensor-specific Transco ding modules on the mobile phone according to the encountered sensor type and make.
{"title":"An Adaptive Middleware for Opportunistic Mobile Sensing","authors":"R. Vasconcelos, L. E. Talavera, I. Vasconcelos, Marcos Roriz, M. Endler, B. Gomes, F. Silva","doi":"10.1109/DCOSS.2015.12","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.12","url":null,"abstract":"The current ubiquity of smart phones with mobile Internet and several short-range wireless interfaces (NFC, Bluetooth, Bluetooth Smart) and the fact that these devices are carried almost anytime and anywhere by users, enables potentially new pervasive sensing applications where smartphones can act as universal hubs for interaction with sensors (or sensor networks) that have only short-range wireless connectivity. Thus, in next years we can expect an increasing number of long-term and large-scale deployments for various crowd-sourced monitoring applications, such as environment monitoring, domestic utility meter reading, urban monitoring, etc. In this paper, we present the implementation and initial performance results with our mobile-cloud middleware that enables such opportunistic mobile sensing. One of the singular features of our middleware is the capability to discover, dynamically download and install sensor-specific Transco ding modules on the mobile phone according to the encountered sensor type and make.","PeriodicalId":332746,"journal":{"name":"2015 International Conference on Distributed Computing in Sensor Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115307348","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}
Leandro N. Balico, Horácio Oliveira, E. Nakamura, Raimundo S. Barreto, A. Loureiro
In this work, we study the impact of data aggregation in WSNs with mobile sink nodes that can move at higher speeds. In these cases, propagated queries cannot be answered by using the sink's position when the query was sent, since the sink node will probably be elsewhere. Therefore, conventional data aggregation schemes may not be appropriate due to this high speed. Thus, we propose and evaluate the performance of three new algorithms for data routing and aggregation in WSNs when the sink is moving at a high speed. These algorithms explore the sink movement to create a routing graph composed of the union paths that intersect the sink's trajectory. At each hop, the sink speed and current network delays are used as metric to guide in-network data aggregation. Our results clearly show significant energy savings and efficient data delivery achieved by the proposed algorithms in different scenarios.
{"title":"Routing and Data Aggregation toward a High Speed Sink in Wireless Sensor Networks","authors":"Leandro N. Balico, Horácio Oliveira, E. Nakamura, Raimundo S. Barreto, A. Loureiro","doi":"10.1109/DCOSS.2015.38","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.38","url":null,"abstract":"In this work, we study the impact of data aggregation in WSNs with mobile sink nodes that can move at higher speeds. In these cases, propagated queries cannot be answered by using the sink's position when the query was sent, since the sink node will probably be elsewhere. Therefore, conventional data aggregation schemes may not be appropriate due to this high speed. Thus, we propose and evaluate the performance of three new algorithms for data routing and aggregation in WSNs when the sink is moving at a high speed. These algorithms explore the sink movement to create a routing graph composed of the union paths that intersect the sink's trajectory. At each hop, the sink speed and current network delays are used as metric to guide in-network data aggregation. Our results clearly show significant energy savings and efficient data delivery achieved by the proposed algorithms in different scenarios.","PeriodicalId":332746,"journal":{"name":"2015 International Conference on Distributed Computing in Sensor Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116735916","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}
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