Opportunistic routing (OR) has been showed efficient for the harsh and challenging scenarios of underwater wireless sensor networks (UWSNs). This routing paradigm leverages the broadcast nature of wireless communication, for improving data delivery. In contrast to traditional multi-hop routing, OR selects a subset of the neighboring nodes to be the next-hop candidate nodes, in which will participate forwarding data packets towards the destination. Hence, at each hop, a transmitted data packet is lost only if none of the next-hop candidate nodes receives it. Therefore, OR not only improves packet delivery rate, but also reduces network energy consumption since fewer retransmissions will be needed. However, the design of OR protocols for UWSNs is challenging, due to the characteristics of the underwater acoustic channel. For instance, the high and variable delay, multipath propagation, low bandwidth, and high energy consumption render impractical the use of the up to date protocols developed for wireless sensor and mesh networks. In this context, this tutorial gives a comprehensive review of the potentials and challenges of opportunistic routing in underwater sensor networks. In addition, based on an in-deep literature review, this tutorial will provide important guidelines for the design of novel protocols for different scenarios of UWSNs.
{"title":"Opportunistic Routing in Underwater Sensor Networks: Potentials, Challenges and Guidelines","authors":"Rodolfo W. L. Coutinho, A. Boukerche","doi":"10.1109/DCOSS.2017.42","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.42","url":null,"abstract":"Opportunistic routing (OR) has been showed efficient for the harsh and challenging scenarios of underwater wireless sensor networks (UWSNs). This routing paradigm leverages the broadcast nature of wireless communication, for improving data delivery. In contrast to traditional multi-hop routing, OR selects a subset of the neighboring nodes to be the next-hop candidate nodes, in which will participate forwarding data packets towards the destination. Hence, at each hop, a transmitted data packet is lost only if none of the next-hop candidate nodes receives it. Therefore, OR not only improves packet delivery rate, but also reduces network energy consumption since fewer retransmissions will be needed. However, the design of OR protocols for UWSNs is challenging, due to the characteristics of the underwater acoustic channel. For instance, the high and variable delay, multipath propagation, low bandwidth, and high energy consumption render impractical the use of the up to date protocols developed for wireless sensor and mesh networks. In this context, this tutorial gives a comprehensive review of the potentials and challenges of opportunistic routing in underwater sensor networks. In addition, based on an in-deep literature review, this tutorial will provide important guidelines for the design of novel protocols for different scenarios of UWSNs.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125350680","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}
Hessam Mohammadmoradi, Sirajum Munir, O. Gnawali, Charles Shelton
People counting has many applications in smart buildings. For example, adjusting HVAC systems based on the number of occupants in each room can save a significant amount of energy. In addition, security and safety of the building can be managed by determining the number and location of occupants. Different technologies and sensing platforms have proposed for accurate and efficient people counting. However, these solutions are expensive, hard to deploy, or privacy invasive. We investigate the possibility of placing an 8×8 IR array sensor at the doorways and counting the number of people inside rooms. Our solution is real-time, inexpensive, privacy preserving with much less deployment constraints compared to its competitors. The proposed solution deals with realistic and dynamic changes in the sensing environment by leveraging a combination of Otsus thresholding and modeling thermal noise distribution. We evaluated our solution via several controlled and uncontrolled real-world environments. The results show an average of 93% accuracy in estimating the number of occupants in rooms.
{"title":"Measuring People-Flow through Doorways Using Easy-to-Install IR Array Sensors","authors":"Hessam Mohammadmoradi, Sirajum Munir, O. Gnawali, Charles Shelton","doi":"10.1109/DCOSS.2017.26","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.26","url":null,"abstract":"People counting has many applications in smart buildings. For example, adjusting HVAC systems based on the number of occupants in each room can save a significant amount of energy. In addition, security and safety of the building can be managed by determining the number and location of occupants. Different technologies and sensing platforms have proposed for accurate and efficient people counting. However, these solutions are expensive, hard to deploy, or privacy invasive. We investigate the possibility of placing an 8×8 IR array sensor at the doorways and counting the number of people inside rooms. Our solution is real-time, inexpensive, privacy preserving with much less deployment constraints compared to its competitors. The proposed solution deals with realistic and dynamic changes in the sensing environment by leveraging a combination of Otsus thresholding and modeling thermal noise distribution. We evaluated our solution via several controlled and uncontrolled real-world environments. The results show an average of 93% accuracy in estimating the number of occupants in rooms.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121741852","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}
Passive radio-frequency (RF) energy harvesting collects the radiated energy from adjacent wireless information transmitters instead of using a dedicated wireless power source. In this paper, we investigate the scenario where a wireless transmitter communicates with its information receiver while intentionally focusing the radiated power to the RF energy harvesters. The wireless transceivers are equipped with multiple antennas, and each of the energy harvesters has one receive antenna. With an appropriate design of the transmit covariance matrix, the wireless transmitter transfers sufficient energy to the energy harvesters with a guarantee on the information rate to the communication receiver. When multiple RF energy harvesters are present, we address the trade-off between net energy harvesting rate and fairness with the dynamic of the energy harvesting network. Simulation results compare the algorithms and evaluate the performance of passive RF energy harvesting.
{"title":"Passive Radio-Frequency Energy Harvesting through Wireless Information Transmission","authors":"Yuan Xing, Liang Dong","doi":"10.1109/DCOSS.2017.33","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.33","url":null,"abstract":"Passive radio-frequency (RF) energy harvesting collects the radiated energy from adjacent wireless information transmitters instead of using a dedicated wireless power source. In this paper, we investigate the scenario where a wireless transmitter communicates with its information receiver while intentionally focusing the radiated power to the RF energy harvesters. The wireless transceivers are equipped with multiple antennas, and each of the energy harvesters has one receive antenna. With an appropriate design of the transmit covariance matrix, the wireless transmitter transfers sufficient energy to the energy harvesters with a guarantee on the information rate to the communication receiver. When multiple RF energy harvesters are present, we address the trade-off between net energy harvesting rate and fairness with the dynamic of the energy harvesting network. Simulation results compare the algorithms and evaluate the performance of passive RF energy harvesting.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132424941","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 presents a distributed serial data aggregation approach, called Spreading Aggregation~(SA), in which one packet hops sequentially over nodes and aggregates their data. The next hop of the aggregation packet is determined locally by each traversed node using only its one-hop neighborhood information, so no network topology information needs to be known by nodes, nor collisions are generated as only one node is communicating at any given time. This localized and distributed characteristic makes the proposed approach highly scalable and very efficient in terms of communication-reduction, energy conservation, and aggregation time, as confirmed by the numerous simulation results we obtained. These results confirm also the superiority of the proposed approach over the state-of-the-art serial approaches, particularly in very large scale network deployments.
{"title":"Distributed Collision-Free Data Aggregation Approach for Wireless Sensor Networks","authors":"M. Merzoug, A. Mostefaoui, Samir Chouali","doi":"10.1109/DCOSS.2017.9","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.9","url":null,"abstract":"This paper presents a distributed serial data aggregation approach, called Spreading Aggregation~(SA), in which one packet hops sequentially over nodes and aggregates their data. The next hop of the aggregation packet is determined locally by each traversed node using only its one-hop neighborhood information, so no network topology information needs to be known by nodes, nor collisions are generated as only one node is communicating at any given time. This localized and distributed characteristic makes the proposed approach highly scalable and very efficient in terms of communication-reduction, energy conservation, and aggregation time, as confirmed by the numerous simulation results we obtained. These results confirm also the superiority of the proposed approach over the state-of-the-art serial approaches, particularly in very large scale network deployments.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125898660","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}
We show that a multihop wireless network can achieve better bandwidth and routing stability when transmission power and routing topology are jointly and adaptively controlled. Our experiments show that the predominant 'fixed and uniform' transmission power strategy with 'link quality and hop distance'-based routing topology construction loses significant bandwidth due to hidden terminal and load imbalance problems. We design an adaptive and distributed control mechanism for transmission power and routing topology, PCRPL, within the standard RPL routing protocol. We implement PC-RPL on real embedded devices and evaluate its performance on a 49-node multihop testbed. PC-RPL reduces total end-to-end packet losses ~7-fold without increasing hop distance compared to RPL with the highest transmission power, resulting in 17% improvement in aggregate bandwidth and 64% for the worst-case node.
{"title":"Do Not Lose Bandwidth: Adaptive Transmission Power and Multihop Topology Control","authors":"Hyung-Sin Kim, Jeongyeup Paek, D. Culler, S. Bahk","doi":"10.1109/DCOSS.2017.23","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.23","url":null,"abstract":"We show that a multihop wireless network can achieve better bandwidth and routing stability when transmission power and routing topology are jointly and adaptively controlled. Our experiments show that the predominant 'fixed and uniform' transmission power strategy with 'link quality and hop distance'-based routing topology construction loses significant bandwidth due to hidden terminal and load imbalance problems. We design an adaptive and distributed control mechanism for transmission power and routing topology, PCRPL, within the standard RPL routing protocol. We implement PC-RPL on real embedded devices and evaluate its performance on a 49-node multihop testbed. PC-RPL reduces total end-to-end packet losses ~7-fold without increasing hop distance compared to RPL with the highest transmission power, resulting in 17% improvement in aggregate bandwidth and 64% for the worst-case node.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126750201","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}
We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.
{"title":"Atomic Routing Mechanisms for Balance of Costs and Quality in Mobile Crowdsensing Systems","authors":"Julia Buwaya, J. Rolim","doi":"10.1109/DCOSS.2017.39","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.39","url":null,"abstract":"We study the problem of distributing loads in mobile crowdsensing systems (MCS). In this context, we present a multi-commodity network game, more explicitly, an atomic routing game, to depict the linking of several crowd participants into bundles that are capable of successfully completing desired sensing tasks. The nodes of the network correspond to the resources of the crowd participants and the players of our game are sensing service requesters that wish to route their demand along paths trough the network. One resource may serve several requests at the same time, which can be modeled efficiently using the network structure. Resource usage involves load-dependent costs. Our model caters for the uncertainty inherent from crowd involvement and mobility by incorporating certainty parameters in the model. These certainty parameters describe the quality of the partial result a participant can produce. Requesters may set a minimum certainty level for the successful completion of their overall sensing tasks that has to be met. In our model, we analyze four different solution concepts for balancing loads with respect to costs and quality of results: (1) a distributed brute force approach (engaging all suitable crowd participants), (2) a random selection of suitable crowd participants, (3) a Nash equilibrium (as result of decentralized selfish cost-minimizing game play) and (4) a (centralized) social optimum. All considered distributed solutions or an epsilon-approximation of a solution can be computed efficiently (for affine cost functions). Furthermore, well-known results for the price of anarchy of atomic routing games can be transfered to our model, i.e., the relative solution quality of a Nash equilibrium compared to a social optimum is provably bounded. In addition, we provide an extensive experimental study that supports theoretical results and gives further suggestions on the impact of uncertainty. We merge the findings of our analysis into a truthful distributed mechanism such that requesters have no incentive to deviate from an efficient solution.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116768949","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}
Reservation-based and contention-based MAC protocols have their own advantages in data transmissions under mobile sensor networks. This paper presents a quantitative analysis of two types of MAC protocols in throughput, delay, and energy efficiency under various traffic loads environments using queueing theory. The analytical and simulation results show the design strategies of hybrid MAC protocols for mobile dynamic traffic scenarios.
{"title":"Energy Efficiency of MAC Protocols in Wireless Sensor Networks","authors":"Xiaoli Zhou, A. Boukerche","doi":"10.1109/DCOSS.2017.37","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.37","url":null,"abstract":"Reservation-based and contention-based MAC protocols have their own advantages in data transmissions under mobile sensor networks. This paper presents a quantitative analysis of two types of MAC protocols in throughput, delay, and energy efficiency under various traffic loads environments using queueing theory. The analytical and simulation results show the design strategies of hybrid MAC protocols for mobile dynamic traffic scenarios.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190186","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 coverage problem of a three-dimensional (3D) space has similarity with the tiling problem in the same space, which can be formulated as follows: How can a 3D space be tiled by replicas of tiles? This is an instance of the second part of Hilbert's eighteenth problem [14], which is stated as follows: "What convex polyhedra exist for which a complete filling of all space is possible by juxtaposition of congruent copies?" In this paper, we propose a polyhedral framework to investigate the connected coverage problem in 3D homogeneous wireless sensor networks. First, we restrict the sensors' sensing sphere to a variety of convex polyhedral space-fillers. Our study aims to find the largest enclosed convex polyhedron space-filler in the sensors' sensing sphere, with a goal to maximize their utilized sensing volume. Second, based on this analysis, we select a minimum number of sensors to cover a 3D space for deterministic and random sensor deployment strategies. Third, we compute the ratio of the communication range to the sensing range of the sensors to ensure network connectivity. Fourth, we corroborate our analysis with various simulation results.
{"title":"Connected Coverage in Three-Dimensional Wireless Sensor Networks Using Convex Polyhedral Space-Fillers","authors":"H. Ammari","doi":"10.1109/DCOSS.2017.12","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.12","url":null,"abstract":"The coverage problem of a three-dimensional (3D) space has similarity with the tiling problem in the same space, which can be formulated as follows: How can a 3D space be tiled by replicas of tiles? This is an instance of the second part of Hilbert's eighteenth problem [14], which is stated as follows: \"What convex polyhedra exist for which a complete filling of all space is possible by juxtaposition of congruent copies?\" In this paper, we propose a polyhedral framework to investigate the connected coverage problem in 3D homogeneous wireless sensor networks. First, we restrict the sensors' sensing sphere to a variety of convex polyhedral space-fillers. Our study aims to find the largest enclosed convex polyhedron space-filler in the sensors' sensing sphere, with a goal to maximize their utilized sensing volume. Second, based on this analysis, we select a minimum number of sensors to cover a 3D space for deterministic and random sensor deployment strategies. Third, we compute the ratio of the communication range to the sensing range of the sensors to ensure network connectivity. Fourth, we corroborate our analysis with various simulation results.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126022107","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}
Supporting sustainable development for the urban environment is crucial in the age of rapid urbanisation. Air pollution modelling is one of the key tools for researchers, scientists, and urban planners to understand pollution behaviour. Recent updates in air quality regulations are challenging the state-of-the-art air pollution modelling techniques by requiring accurate predictions on a high temporal level, i.e. predictions at the hourly level rather than the annual level. Current state-of-the-art models designed to have good prediction accuracy on the low temporal resolution by assuming that the pollution is in steady state. Making predictions on higher temporal resolution violates this assumption and causing inaccurate predictions. We introduce a novel statistical regression based air pollution model which produces accurate hourly predictions by using data with high temporal resolution and advanced regression algorithms. We conducted an analysis which shows that the state-of-the-art evaluation techniques (e.g. RMSE) do not describe the nature of the mispredictions of the models built on different data subsets. We carried out an extensive input data evaluation experiment where we concluded that our approach could achieve further accuracy improvement by training the models on a carefully selected subset of the input data.
{"title":"Signal Selection in a Complex Environmental Distributed Sensing Problem","authors":"Gabor Makrai, I. Bate","doi":"10.1109/DCOSS.2017.24","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.24","url":null,"abstract":"Supporting sustainable development for the urban environment is crucial in the age of rapid urbanisation. Air pollution modelling is one of the key tools for researchers, scientists, and urban planners to understand pollution behaviour. Recent updates in air quality regulations are challenging the state-of-the-art air pollution modelling techniques by requiring accurate predictions on a high temporal level, i.e. predictions at the hourly level rather than the annual level. Current state-of-the-art models designed to have good prediction accuracy on the low temporal resolution by assuming that the pollution is in steady state. Making predictions on higher temporal resolution violates this assumption and causing inaccurate predictions. We introduce a novel statistical regression based air pollution model which produces accurate hourly predictions by using data with high temporal resolution and advanced regression algorithms. We conducted an analysis which shows that the state-of-the-art evaluation techniques (e.g. RMSE) do not describe the nature of the mispredictions of the models built on different data subsets. We carried out an extensive input data evaluation experiment where we concluded that our approach could achieve further accuracy improvement by training the models on a carefully selected subset of the input data.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117257046","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}
Social sensing has emerged as a new data collection paradigm in networked sensing applications where humans are used as "sensors" to report their observations about the physical world. While many previous studies in social sensing focus on the problem of ascertaining the reliability of data sources and the correctness of their reported claims (often known as truth discovery), this paper investigates a new problem of critical source selection. The goal of this problem is to identify a subset of critical sources that can help effectively reduce the computational complexity of the original truth discovery problem and improve the accuracy of the analysis results. In this paper, we propose a new scheme, Critical Sources Selection (CSS) scheme, to find the critical set of sources by explicitly exploring both dependency and speak rate of sources. We evaluated the performance of our scheme and compared it to the state-of-the-art baselines using two data traces collected from a real world social sensing application. The results showed that our scheme significantly outperforms the baselines by finding more truthful information at a faster speed.
{"title":"Critical Source Selection in Social Sensing Applications","authors":"Chao Huang, Dong Wang","doi":"10.1109/DCOSS.2017.27","DOIUrl":"https://doi.org/10.1109/DCOSS.2017.27","url":null,"abstract":"Social sensing has emerged as a new data collection paradigm in networked sensing applications where humans are used as \"sensors\" to report their observations about the physical world. While many previous studies in social sensing focus on the problem of ascertaining the reliability of data sources and the correctness of their reported claims (often known as truth discovery), this paper investigates a new problem of critical source selection. The goal of this problem is to identify a subset of critical sources that can help effectively reduce the computational complexity of the original truth discovery problem and improve the accuracy of the analysis results. In this paper, we propose a new scheme, Critical Sources Selection (CSS) scheme, to find the critical set of sources by explicitly exploring both dependency and speak rate of sources. We evaluated the performance of our scheme and compared it to the state-of-the-art baselines using two data traces collected from a real world social sensing application. The results showed that our scheme significantly outperforms the baselines by finding more truthful information at a faster speed.","PeriodicalId":399222,"journal":{"name":"2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123870257","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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