M. Mousa, Mohammed Abdulaal, S. Boyles, C. Claudel
Probe vehicle data is currently generated using satellite navigation systems such as the GPS, GLONASS or Galileo systems. However, because of their high cost and relatively high position uncertainty and low sampling rate, satellite positioning systems have a relatively low penetration rate among users. In addition, such sensors do not provide context in the traffic measurements. To address these issues, we introduce a new traffic monitoring concept based on inexpensive inertial measurement units in conjunction with a wireless sensor network deployed inside a city. After discussing the sensing technique, we present a preliminary implementation of this system using an open source robotic platform. Preliminary results show that this system can be used to generate traffic measurement data.
{"title":"Wireless Sensor Network-Based Urban Traffic Monitoring Using Inertial Reference Data","authors":"M. Mousa, Mohammed Abdulaal, S. Boyles, C. Claudel","doi":"10.1109/DCOSS.2015.21","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.21","url":null,"abstract":"Probe vehicle data is currently generated using satellite navigation systems such as the GPS, GLONASS or Galileo systems. However, because of their high cost and relatively high position uncertainty and low sampling rate, satellite positioning systems have a relatively low penetration rate among users. In addition, such sensors do not provide context in the traffic measurements. To address these issues, we introduce a new traffic monitoring concept based on inexpensive inertial measurement units in conjunction with a wireless sensor network deployed inside a city. After discussing the sensing technique, we present a preliminary implementation of this system using an open source robotic platform. Preliminary results show that this system can be used to generate traffic measurement data.","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":"115885075","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}
C. Asensio-Marco, D. Alonso-Roman, B. Beferull-Lozano
The estimation of a parameter corrupted by noise is a common tasks in wireless sensor networks, where the deployed nodes cooperate in order to improve their own inaccurate observations. This cooperation usually involves successive data exchanges and local information updates until a global consensus value is reached. The quality of the final estimator depends on the amount of collected observations, hence the number of active nodes. Moreover, the inherent iterative nature of the consensus process involves a certain energy consumption. Since the devices composing the network are usually battery powered, nodes becoming inactive due to battery depletion emerges as a serious problem. In this work, we aim to maximize the lifetime of the most energy demanding nodes, such that the quality of the global estimator is maintained above a certain threshold. To this end, we optimize the network topology considering both the duration of each consensus process, given by the algebraic connectivity of the network, and the power consumption per iteration of the most demanding nodes. Numerical results are provided to demonstrate the validity and efficiency of our methodology.
{"title":"Ensuring High Performance of Consensus-Based Estimation by Lifetime Maximization in WSNs","authors":"C. Asensio-Marco, D. Alonso-Roman, B. Beferull-Lozano","doi":"10.1109/DCOSS.2015.11","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.11","url":null,"abstract":"The estimation of a parameter corrupted by noise is a common tasks in wireless sensor networks, where the deployed nodes cooperate in order to improve their own inaccurate observations. This cooperation usually involves successive data exchanges and local information updates until a global consensus value is reached. The quality of the final estimator depends on the amount of collected observations, hence the number of active nodes. Moreover, the inherent iterative nature of the consensus process involves a certain energy consumption. Since the devices composing the network are usually battery powered, nodes becoming inactive due to battery depletion emerges as a serious problem. In this work, we aim to maximize the lifetime of the most energy demanding nodes, such that the quality of the global estimator is maintained above a certain threshold. To this end, we optimize the network topology considering both the duration of each consensus process, given by the algebraic connectivity of the network, and the power consumption per iteration of the most demanding nodes. Numerical results are provided to demonstrate the validity and efficiency of our methodology.","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":"123934066","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}
Shaohan Hu, Shen Li, Shuochao Yao, Lu Su, R. Govindan, Reginald L. Hobbs, T. Abdelzaher
We develop data retrieval algorithms for crowd-sensing applications that reduce the underlying network bandwidth consumption or any additive cost metric by exploiting logical dependencies among data items, while maintaining the level of service to the client applications. Crowd sensing applications refer to those where local measurements are performed by humans or devices in their possession for subsequent aggregation and sharing purposes. In this paper, we focus on resource-limited crowd sensing, such as disaster response and recovery scenarios. The key challenge in those scenarios is to cope with resource constraints. Unlike the traditional application design, where measurements are sent to a central aggregator, in resource limited scenarios, data will typically reside at the source until requested to prevent needless transmission. Many applications exhibit dependencies among data items. For example, parts of a city might tend to get flooded together because of a correlated low elevation, and some roads might become useless for evacuation if a bridge they lead to fails. Such dependencies can be encoded as logic expressions that obviate retrieval of some data items based on values of others. Our algorithm takes logical data dependencies into consideration such that application queries are answered at the central aggregation node, while network bandwidth usage is minimized. The algorithms consider multiple concurrent queries and accommodate retrieval latency constraints. Simulation results show that our algorithm outperforms several baselines by significant margins, maintaining the level of service perceived by applications in the presence of resource-constraints.
{"title":"On Exploiting Logical Dependencies for Minimizing Additive Cost Metrics in Resource-Limited Crowdsensing","authors":"Shaohan Hu, Shen Li, Shuochao Yao, Lu Su, R. Govindan, Reginald L. Hobbs, T. Abdelzaher","doi":"10.1109/DCOSS.2015.26","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.26","url":null,"abstract":"We develop data retrieval algorithms for crowd-sensing applications that reduce the underlying network bandwidth consumption or any additive cost metric by exploiting logical dependencies among data items, while maintaining the level of service to the client applications. Crowd sensing applications refer to those where local measurements are performed by humans or devices in their possession for subsequent aggregation and sharing purposes. In this paper, we focus on resource-limited crowd sensing, such as disaster response and recovery scenarios. The key challenge in those scenarios is to cope with resource constraints. Unlike the traditional application design, where measurements are sent to a central aggregator, in resource limited scenarios, data will typically reside at the source until requested to prevent needless transmission. Many applications exhibit dependencies among data items. For example, parts of a city might tend to get flooded together because of a correlated low elevation, and some roads might become useless for evacuation if a bridge they lead to fails. Such dependencies can be encoded as logic expressions that obviate retrieval of some data items based on values of others. Our algorithm takes logical data dependencies into consideration such that application queries are answered at the central aggregation node, while network bandwidth usage is minimized. The algorithms consider multiple concurrent queries and accommodate retrieval latency constraints. Simulation results show that our algorithm outperforms several baselines by significant margins, maintaining the level of service perceived by applications in the presence of resource-constraints.","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":"127235514","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}
This paper deals with one way to predict efficiency of despeckling for images acquired by a single-or multi-look synthetic aperture radar (SAR). A particular filter based on discrete cosine transform (DCT) and adapted to speckle characteristics is considered. Two quantitative criteria characterizing despeckling efficiency are analyzed. It is shown that even one parameter that can be calculated for image blocks sequentially or in parallel allows carrying out a rather accurate prediction. Moreover, such a prediction is possible for both spatially uncorrelated and correlated speckle.
{"title":"Prediction of Despeckling Efficiency of DCT-Based Filters Applied to SAR Images","authors":"Oleksii S. Rubel, V. Lukin, F. Medeiros","doi":"10.1109/DCOSS.2015.16","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.16","url":null,"abstract":"This paper deals with one way to predict efficiency of despeckling for images acquired by a single-or multi-look synthetic aperture radar (SAR). A particular filter based on discrete cosine transform (DCT) and adapted to speckle characteristics is considered. Two quantitative criteria characterizing despeckling efficiency are analyzed. It is shown that even one parameter that can be calculated for image blocks sequentially or in parallel allows carrying out a rather accurate prediction. Moreover, such a prediction is possible for both spatially uncorrelated and correlated speckle.","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":"134128055","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}
Hongkai Wen, Yiran Shen, Savvas Papaioannou, W. Churchill, A. Trigoni, P. Newman
Navigating autonomous ground vehicles with visual sensors has many advantages - it does not rely on global maps, yet is accurate and reliable even in GPS-denied environments. However, due to the limitation of the camera field of view, one typically has to record a large number of visual experiences for practical navigation. In this paper, we explore new avenues in linking together visual experiences, by opportunistically harvesting and sharing a variety of radio signals emitted by surrounding stationary access points and mobile devices. We propose a novel navigation approach, which exploits side-channel information of co-location to thread up visually-separated experiences with short exploration phases. The proposed approach empowers users to trade travel time for manual navigation effort, allowing them to choose the itinerary that best serves their needs. We evaluate the proposed approach with data collected from a typical urban area, and show that it achieves much better navigation performance in both reach ability and cost, comparing with the state of the arts that only use visual information.
{"title":"Opportunistic Radio Assisted Navigation for Autonomous Ground Vehicles","authors":"Hongkai Wen, Yiran Shen, Savvas Papaioannou, W. Churchill, A. Trigoni, P. Newman","doi":"10.1109/DCOSS.2015.22","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.22","url":null,"abstract":"Navigating autonomous ground vehicles with visual sensors has many advantages - it does not rely on global maps, yet is accurate and reliable even in GPS-denied environments. However, due to the limitation of the camera field of view, one typically has to record a large number of visual experiences for practical navigation. In this paper, we explore new avenues in linking together visual experiences, by opportunistically harvesting and sharing a variety of radio signals emitted by surrounding stationary access points and mobile devices. We propose a novel navigation approach, which exploits side-channel information of co-location to thread up visually-separated experiences with short exploration phases. The proposed approach empowers users to trade travel time for manual navigation effort, allowing them to choose the itinerary that best serves their needs. We evaluate the proposed approach with data collected from a typical urban area, and show that it achieves much better navigation performance in both reach ability and cost, comparing with the state of the arts that only use visual information.","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":"127735960","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 reduction of the consumption of energy, through its efficient use, is regarded as one of the ways of reducing the impact of mankind on the environment. Buildings consume a significant amount of energy, namely for heating, cooling and illumination. Over the last decades, more energy efficient equipment, new building materials and construction techniques have enabled more energy efficient buildings. However, human behaviour has a large impact on the energy consumption of each building, with similar buildings presenting very distinct energy footprints, due to their occupants' behaviour. The problem of creating more sustainable energy consumption habits has recently received a lot of attention from the research community. Systems capable of reducing energy consumption, by enforcing more correct behaviours, may reduce costs for companies and help improve the environmental outlook. This paper proposes a novel system to address the energy consumption problem and inadequate habits of people in office buildings. It's a highly flexible distributed office management system that can scale from an individual node in an office to the whole building. The goal is to reduce global building energy consumption without significantly affecting the users' comfort level. An approach is used where the building services are adjusted to its occupancy level and users' needs based on their location. Users are driven to better energy usage habits through access to information and feedback. Our proposal is presented in detail and validated in the context of an academic institution, more specifically at the Taguspark campus of Instituto Superior Técnico. The developed system is now operational and being used as a flexible, easily programmable, research platform.
{"title":"PerOMAS: Personal Office Management and Automation System","authors":"Artur Balanuta, R. Pereira, C. Silva","doi":"10.1109/DCOSS.2015.30","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.30","url":null,"abstract":"The reduction of the consumption of energy, through its efficient use, is regarded as one of the ways of reducing the impact of mankind on the environment. Buildings consume a significant amount of energy, namely for heating, cooling and illumination. Over the last decades, more energy efficient equipment, new building materials and construction techniques have enabled more energy efficient buildings. However, human behaviour has a large impact on the energy consumption of each building, with similar buildings presenting very distinct energy footprints, due to their occupants' behaviour. The problem of creating more sustainable energy consumption habits has recently received a lot of attention from the research community. Systems capable of reducing energy consumption, by enforcing more correct behaviours, may reduce costs for companies and help improve the environmental outlook. This paper proposes a novel system to address the energy consumption problem and inadequate habits of people in office buildings. It's a highly flexible distributed office management system that can scale from an individual node in an office to the whole building. The goal is to reduce global building energy consumption without significantly affecting the users' comfort level. An approach is used where the building services are adjusted to its occupancy level and users' needs based on their location. Users are driven to better energy usage habits through access to information and feedback. Our proposal is presented in detail and validated in the context of an academic institution, more specifically at the Taguspark campus of Instituto Superior Técnico. The developed system is now operational and being used as a flexible, easily programmable, research platform.","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":"115851135","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}
A. Bar-Noy, Matthew P. Johnson, Nooreddin Naghibolhosseini, Dror Rawitz, S. Shamoun
An important problem in the study of sensor networks is how to select a set of sensors that maximizes coverage of other sensors. Given pair wise coverage values, three commonly found functions give some estimate of the aggregate coverage possible by a set of sensors: maximum coverage by any selected sensor (MAX), total coverage by all selected sensors (SUM), and the probability of correct prediction by at least one sensor (PROB). MAX and SUM are two extremes of possible coverage, while PROB, based on an independence assumption, is in the middle. This paper addresses the following question: what guarantees can be made of coverage that is evaluated by an unknown sub-modular function of coverage when sensors are selected according to MAX, SUM, or PROB? We prove that the guarantees are very bad: In the worst case, coverage differs by a factor of sqrt(n), where n is the number of sensors. We show in simulations on synthetic and real data that the differences can be quite high as well. We show how to potentially address this problem using a hybrid of the coverage functions.
{"title":"The Price of Incorrectly Aggregating Coverage Values in Sensor Selection","authors":"A. Bar-Noy, Matthew P. Johnson, Nooreddin Naghibolhosseini, Dror Rawitz, S. Shamoun","doi":"10.1109/DCOSS.2015.24","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.24","url":null,"abstract":"An important problem in the study of sensor networks is how to select a set of sensors that maximizes coverage of other sensors. Given pair wise coverage values, three commonly found functions give some estimate of the aggregate coverage possible by a set of sensors: maximum coverage by any selected sensor (MAX), total coverage by all selected sensors (SUM), and the probability of correct prediction by at least one sensor (PROB). MAX and SUM are two extremes of possible coverage, while PROB, based on an independence assumption, is in the middle. This paper addresses the following question: what guarantees can be made of coverage that is evaluated by an unknown sub-modular function of coverage when sensors are selected according to MAX, SUM, or PROB? We prove that the guarantees are very bad: In the worst case, coverage differs by a factor of sqrt(n), where n is the number of sensors. We show in simulations on synthetic and real data that the differences can be quite high as well. We show how to potentially address this problem using a hybrid of the coverage functions.","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":"114148935","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 requirements of safety-critical wireless sensor network (WSN) applications, such as closed-loop control and traffic safety, cannot be met by the IEEE 802.15.4-2006 standard nor its industrial WSN (IWSN) derivatives. The main problem in that respect is the communication reliability, which is seriously compromised by 2.4-GHz interference, as well as multipath fading and attenuation (MFA) at industrial facilities. Meanwhile, communication blackouts in critical WSN applications may lead to devastating consequences, including production halts, damage to production assets and can pose a threat to safety of human personnel. This work presents PREED, a method to improve the reliability by exploiting the determinism in IWSN communication. The proposed solution is based on the analysis of bit error traces collected in real transmissions at four different industrial environments. A case study on Wireless HART packet format shows that PREED recovers 42%-134% more packets than the competing approaches on links compromised by WLAN interference. In addition, PREED reduces one of the most trivial causes of packet loss in IWSN, i.e. The corruption of frame length byte, by 88% and 99%, for links exposed to WLAN interference and MFA, respectively.
{"title":"PREED: Packet REcovery by Exploiting the Determinism in Industrial WSN Communication","authors":"Filip Barac, M. Gidlund, Tingting Zhang","doi":"10.1109/DCOSS.2015.8","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.8","url":null,"abstract":"The requirements of safety-critical wireless sensor network (WSN) applications, such as closed-loop control and traffic safety, cannot be met by the IEEE 802.15.4-2006 standard nor its industrial WSN (IWSN) derivatives. The main problem in that respect is the communication reliability, which is seriously compromised by 2.4-GHz interference, as well as multipath fading and attenuation (MFA) at industrial facilities. Meanwhile, communication blackouts in critical WSN applications may lead to devastating consequences, including production halts, damage to production assets and can pose a threat to safety of human personnel. This work presents PREED, a method to improve the reliability by exploiting the determinism in IWSN communication. The proposed solution is based on the analysis of bit error traces collected in real transmissions at four different industrial environments. A case study on Wireless HART packet format shows that PREED recovers 42%-134% more packets than the competing approaches on links compromised by WLAN interference. In addition, PREED reduces one of the most trivial causes of packet loss in IWSN, i.e. The corruption of frame length byte, by 88% and 99%, for links exposed to WLAN interference and MFA, respectively.","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":"122388424","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 continuing proliferation of smartphones makes them an effective means to monitor the number of people within an area, for example, to gain insights into customer engagement in retail and to enable an intelligent traffic system in a city. However, current approaches to obtain this information are either invasive as they require to continuously run a dedicated smartphone app, or they compromise users' privacy by sniffing the MAC addresses of their smartphones. As a consequence, lawyers, authorities, and the population are very skeptical toward adopting such innovative systems. We present DevCnt, the first system that counts in real-time the number of Wi-Fi enabled smartphones in a non-invasive manner while preserving by design the privacy of the smartphone users. This paper details how DevCnt detects active Wi-Fi scans performed by smartphones on a ZigBee device, and how DevCnt uses the number of detected scans to estimate the number of Wi-Fi enabled smartphones. Results from controlled and real-world experiments show that DevCnt: (i) detects more than 99% of active Wi-Fi scans even under interference from multiple wireless technologies, (ii) achieves up to 91% accuracy in the estimated smartphone counts, and (iii) provides meaningful estimates in a real test run involving hundreds of Wi-Fi transmitters.
{"title":"Passive, Privacy-Preserving Real-Time Counting of Unmodified Smartphones via ZigBee Interference","authors":"R. Lim, Marco Zimmerling, L. Thiele","doi":"10.1109/DCOSS.2015.13","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.13","url":null,"abstract":"The continuing proliferation of smartphones makes them an effective means to monitor the number of people within an area, for example, to gain insights into customer engagement in retail and to enable an intelligent traffic system in a city. However, current approaches to obtain this information are either invasive as they require to continuously run a dedicated smartphone app, or they compromise users' privacy by sniffing the MAC addresses of their smartphones. As a consequence, lawyers, authorities, and the population are very skeptical toward adopting such innovative systems. We present DevCnt, the first system that counts in real-time the number of Wi-Fi enabled smartphones in a non-invasive manner while preserving by design the privacy of the smartphone users. This paper details how DevCnt detects active Wi-Fi scans performed by smartphones on a ZigBee device, and how DevCnt uses the number of detected scans to estimate the number of Wi-Fi enabled smartphones. Results from controlled and real-world experiments show that DevCnt: (i) detects more than 99% of active Wi-Fi scans even under interference from multiple wireless technologies, (ii) achieves up to 91% accuracy in the estimated smartphone counts, and (iii) provides meaningful estimates in a real test run involving hundreds of Wi-Fi transmitters.","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":"126773881","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}
Atis Elsts, Farshid Hassani Bijarbooneh, M. Jacobsson, Konstantinos Sagonas
Task Graph (ATaG) is a sensor network application development paradigm where the application is visually described by a graph where the nodes correspond to application-level tasks and edges correspond to data flows. We extend ATaG with the option to add non-functional requirements: constraints on end-to-end delay and packet delivery rate. Setting up these constraints at the design phase naturally leads to enabling run-time assurance at the deployment phase, when the conditions of the constraints are used as network's performance goals. We provide both run-time middleware that checks the conditions of these constraints and a central management unit that dynamically adapts the system by doing task reallocation and putting task copies on redundant nodes. Through extensive simulations we show that the system is efficient enough to enable adaptations within tens of seconds even in large networks.
{"title":"Enabling Design of Performance-Controlled Sensor Network Applications through Task Allocation and Reallocation","authors":"Atis Elsts, Farshid Hassani Bijarbooneh, M. Jacobsson, Konstantinos Sagonas","doi":"10.1109/DCOSS.2015.44","DOIUrl":"https://doi.org/10.1109/DCOSS.2015.44","url":null,"abstract":"Task Graph (ATaG) is a sensor network application development paradigm where the application is visually described by a graph where the nodes correspond to application-level tasks and edges correspond to data flows. We extend ATaG with the option to add non-functional requirements: constraints on end-to-end delay and packet delivery rate. Setting up these constraints at the design phase naturally leads to enabling run-time assurance at the deployment phase, when the conditions of the constraints are used as network's performance goals. We provide both run-time middleware that checks the conditions of these constraints and a central management unit that dynamically adapts the system by doing task reallocation and putting task copies on redundant nodes. Through extensive simulations we show that the system is efficient enough to enable adaptations within tens of seconds even in large networks.","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":"125452652","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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