Floods are the most common type of natural disaster, causing thousands of casualties every year. Among these events, urban flash floods are particularly deadly because of the short timescales on which they occur, and because of the high concentration of population in cities. Since most flash flood casualties are caused by a lack of information, it is critical to generate accurate and detailed warnings of flash floods. However, deploying an infrastructure that solely monitor flash floods makes little economic sense, since the average periodicity of catastrophic flash floods exceeds the lifetime of a typical sensor network. To address this issue, we propose a new sensing device that can simultaneously monitor urban flash floods and another phenomenon of interest (traffic congestion on the present case). This sensing device is based on the combination of an ultrasonic rangefinder with one or multiple remote temperature sensors. We show an implementation of this device, and illustrate its performance in both traffic flow and flash flood sensing. Field data shows that the sensor can detect vehicles with a 99% accuracy, in addition to estimating their speed and classifying them in function of their length. The same sensor can also monitor urban water levels with an accuracy of less than 2 cm. Two of the sensors have been deployed in a flood prone area, where they captured the only (minor) flash flood that occurred over the one-year test period, with no false detection, and an agreement in the estimated water level estimate (during the flash flood event) of about 2 cm.
{"title":"A Novel Dual Traffic/Flash Flood Monitoring System Using Passive Infrared/Ultrasonic Sensors","authors":"M. Mousa, Enas Odat, C. Claudel","doi":"10.1109/MASS.2015.61","DOIUrl":"https://doi.org/10.1109/MASS.2015.61","url":null,"abstract":"Floods are the most common type of natural disaster, causing thousands of casualties every year. Among these events, urban flash floods are particularly deadly because of the short timescales on which they occur, and because of the high concentration of population in cities. Since most flash flood casualties are caused by a lack of information, it is critical to generate accurate and detailed warnings of flash floods. However, deploying an infrastructure that solely monitor flash floods makes little economic sense, since the average periodicity of catastrophic flash floods exceeds the lifetime of a typical sensor network. To address this issue, we propose a new sensing device that can simultaneously monitor urban flash floods and another phenomenon of interest (traffic congestion on the present case). This sensing device is based on the combination of an ultrasonic rangefinder with one or multiple remote temperature sensors. We show an implementation of this device, and illustrate its performance in both traffic flow and flash flood sensing. Field data shows that the sensor can detect vehicles with a 99% accuracy, in addition to estimating their speed and classifying them in function of their length. The same sensor can also monitor urban water levels with an accuracy of less than 2 cm. Two of the sensors have been deployed in a flood prone area, where they captured the only (minor) flash flood that occurred over the one-year test period, with no false detection, and an agreement in the estimated water level estimate (during the flash flood event) of about 2 cm.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132873735","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}
Visible light communication (VLC), a novel technology that enables standard Light-Emitting-Diodes (LEDs) to transmit data, is gaining significant attention. In the near future, this technology could enable devices containing LEDs-such as car lights, city lights, screens and home appliances-to form their own networks. VLC, however, is currently limited to point-to-point communication. To unleash VLC's full potential, we need to provide it with more sophisticated networking capabilities. In this paper, we present the design and implementation of a novel platform aimed at distributed multi-hop visible light communication. Compared to the state-of-the-art, our platform provides similar data rates and coverage, but adds two unique characteristics: (i) 360° coverage, which is necessary to investigate an important property of LED communication: directionality, and (ii) a flexible design, which allows our platform to be connected to many experimental boards such as Arduino, Beagle bone, Raspberry Pi and sensor nodes. To quantify the communication capabilities of our board, we evaluate three key components: link quality, neighbor discovery and packet forwarding. Overall, we hope that our work will lower the entry barrier for members of the pervasive and networking communities to investigate and exploit future LED-based networks.
{"title":"Shine: A Step Towards Distributed Multi-Hop Visible Light Communication","authors":"L. Klaver, Marco Zúñiga","doi":"10.1109/MASS.2015.78","DOIUrl":"https://doi.org/10.1109/MASS.2015.78","url":null,"abstract":"Visible light communication (VLC), a novel technology that enables standard Light-Emitting-Diodes (LEDs) to transmit data, is gaining significant attention. In the near future, this technology could enable devices containing LEDs-such as car lights, city lights, screens and home appliances-to form their own networks. VLC, however, is currently limited to point-to-point communication. To unleash VLC's full potential, we need to provide it with more sophisticated networking capabilities. In this paper, we present the design and implementation of a novel platform aimed at distributed multi-hop visible light communication. Compared to the state-of-the-art, our platform provides similar data rates and coverage, but adds two unique characteristics: (i) 360° coverage, which is necessary to investigate an important property of LED communication: directionality, and (ii) a flexible design, which allows our platform to be connected to many experimental boards such as Arduino, Beagle bone, Raspberry Pi and sensor nodes. To quantify the communication capabilities of our board, we evaluate three key components: link quality, neighbor discovery and packet forwarding. Overall, we hope that our work will lower the entry barrier for members of the pervasive and networking communities to investigate and exploit future LED-based networks.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128833585","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 proposes a group-based emergency guiding system for mobile users using smartphones, called Go FAST, which can model the spatiotemporal mobility of indoor people. A dedicated path can be determined to provide the shortest evacuation time for each group of nearby people. The Go FAST system considers the corridor capacities and lengths, exit capacities, concurrent motion, distribution of indoor people, and dedicated escape path to accurately estimate the evacuation time for each group. Based on the estimated evacuation time, the evacuation load can evenly distributed among exits to minimize the total evacuation time. Go FAST can alleviate the congestion of all corridors and exits to reduce the total evacuation time as much as possible. An Android-based prototype with iBeacon indoor localization is implemented to verify the feasibility of our Go FAST system. Simulation results show that Go FAST outperforms existing schemes and can achieve the shortest evacuation time for group-based emergency guiding.
{"title":"GoFAST: A Group-Based Emergency Guiding System with Dedicated Path Planning for Mobile Users Using Smartphones","authors":"Lien-Wu Chen, Jhen-Jhou Chung, Jun-Xian Liu","doi":"10.1109/MASS.2015.35","DOIUrl":"https://doi.org/10.1109/MASS.2015.35","url":null,"abstract":"This paper proposes a group-based emergency guiding system for mobile users using smartphones, called Go FAST, which can model the spatiotemporal mobility of indoor people. A dedicated path can be determined to provide the shortest evacuation time for each group of nearby people. The Go FAST system considers the corridor capacities and lengths, exit capacities, concurrent motion, distribution of indoor people, and dedicated escape path to accurately estimate the evacuation time for each group. Based on the estimated evacuation time, the evacuation load can evenly distributed among exits to minimize the total evacuation time. Go FAST can alleviate the congestion of all corridors and exits to reduce the total evacuation time as much as possible. An Android-based prototype with iBeacon indoor localization is implemented to verify the feasibility of our Go FAST system. Simulation results show that Go FAST outperforms existing schemes and can achieve the shortest evacuation time for group-based emergency guiding.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124132321","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 exponential increase in mobile data demand, coupled with growing user expectation to be connected in all places at all times, have introduced novel challenges for researchers to address. Fortunately, the wide spread deployment of various network technologies and the increased adoption of multi-interface-enabled devices allow researchers to develop solutions for those challenges. Such solutions exploit available interfaces on these devices in both local and collaborative forms. These solutions, however, have faced a formidable deployment barrier. Therefore, in this paper, we present OSCAR, a multi-objective, incentive-based, collaborative, and deployable bandwidth aggregation system, designed to exploit multiple network interfaces on modern mobile devices. Oscar's architecture does not introduce any intermediate hardware nor require changes to current applications or legacy servers. This architecture estimates the interfaces characteristics and application requirements, schedules various connections and/or packets to different interfaces, and provides users with incentives for collaboration and bandwidth sharing. We formulate the OSCAR scheduler as a multi-objective scheduler that maximizes system throughput while achieving user-defined efficiency goals for both cost and energy consumption. We implement a small scale prototype of our OSCAR system, which we use to evaluate its performance. Our evaluation shows that we provide up to 150% enhancement in the throughput compared to current operating systems with only minor updates to the client devices.
{"title":"What Goes Around Comes Around: Mobile Bandwidth Sharing and Aggregation","authors":"Karim Habak, Khaled A. Harras, M. Youssef","doi":"10.1109/MASS.2015.42","DOIUrl":"https://doi.org/10.1109/MASS.2015.42","url":null,"abstract":"The exponential increase in mobile data demand, coupled with growing user expectation to be connected in all places at all times, have introduced novel challenges for researchers to address. Fortunately, the wide spread deployment of various network technologies and the increased adoption of multi-interface-enabled devices allow researchers to develop solutions for those challenges. Such solutions exploit available interfaces on these devices in both local and collaborative forms. These solutions, however, have faced a formidable deployment barrier. Therefore, in this paper, we present OSCAR, a multi-objective, incentive-based, collaborative, and deployable bandwidth aggregation system, designed to exploit multiple network interfaces on modern mobile devices. Oscar's architecture does not introduce any intermediate hardware nor require changes to current applications or legacy servers. This architecture estimates the interfaces characteristics and application requirements, schedules various connections and/or packets to different interfaces, and provides users with incentives for collaboration and bandwidth sharing. We formulate the OSCAR scheduler as a multi-objective scheduler that maximizes system throughput while achieving user-defined efficiency goals for both cost and energy consumption. We implement a small scale prototype of our OSCAR system, which we use to evaluate its performance. Our evaluation shows that we provide up to 150% enhancement in the throughput compared to current operating systems with only minor updates to the client devices.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114967559","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}
Multi-robot systems (MRS) have many applications and the efficient operation of MRS relies on coordination of robots. However, it is difficult to build network connections among randomly distributed robots in the presence of robot movements and weak wireless channels. In this work, we propose to jointly exploit communications and motion control to efficiently establish robot connections. To achieve this goal, we concurrently use MUSIC and particle filter to more accurately and efficiently estimate robot signal directions, built on which signal strength-based potential field is formed to control robot motion to establish and maintain communication links. Our studies based on test bed and simulations demonstrate the effectiveness of our algorithm in networking robots, with much higher number of robots connected compared to peer algorithms.
{"title":"Connecting Robots with Concurrent Exploration of Control and Communications","authors":"Zhe Yan, Xin Wang, Daegeun Yoon, Dongliang Xie","doi":"10.1109/MASS.2015.32","DOIUrl":"https://doi.org/10.1109/MASS.2015.32","url":null,"abstract":"Multi-robot systems (MRS) have many applications and the efficient operation of MRS relies on coordination of robots. However, it is difficult to build network connections among randomly distributed robots in the presence of robot movements and weak wireless channels. In this work, we propose to jointly exploit communications and motion control to efficiently establish robot connections. To achieve this goal, we concurrently use MUSIC and particle filter to more accurately and efficiently estimate robot signal directions, built on which signal strength-based potential field is formed to control robot motion to establish and maintain communication links. Our studies based on test bed and simulations demonstrate the effectiveness of our algorithm in networking robots, with much higher number of robots connected compared to peer algorithms.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116796510","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}
Route discovery and node localization are two strongly correlated concepts in wireless sensor networks (WSNs) and many different techniques have been proposed for both challenges. However, many of these solutions assume homogeneous network conditions, e.g., Identical sensor hardware, fixed transmission powers, or uniform node deployment. In heterogeneous networks, where these parameters are allowed to differ or change over time, many of these solutions fail to ensure accurate localization and route discovery that covers the entire network. This paper introduces a new approach that combines both route discovery and sensor node localization into one protocol that considers the heterogeneous nature of many WSNs. The proposed approach does not require any extra hardware and performs both a probabilistic ad-hoc route discovery process (based on sensor transmission ranges) and energy-efficient localization of sensor nodes. The performance of this approach is evaluated in terms of localization accuracy, energy efficiency, and network coverage.
{"title":"Joint Route Discovery and Localization in Heterogeneous Wireless Sensor Networks","authors":"M. Golestanian, C. Poellabauer","doi":"10.1109/MASS.2015.102","DOIUrl":"https://doi.org/10.1109/MASS.2015.102","url":null,"abstract":"Route discovery and node localization are two strongly correlated concepts in wireless sensor networks (WSNs) and many different techniques have been proposed for both challenges. However, many of these solutions assume homogeneous network conditions, e.g., Identical sensor hardware, fixed transmission powers, or uniform node deployment. In heterogeneous networks, where these parameters are allowed to differ or change over time, many of these solutions fail to ensure accurate localization and route discovery that covers the entire network. This paper introduces a new approach that combines both route discovery and sensor node localization into one protocol that considers the heterogeneous nature of many WSNs. The proposed approach does not require any extra hardware and performs both a probabilistic ad-hoc route discovery process (based on sensor transmission ranges) and energy-efficient localization of sensor nodes. The performance of this approach is evaluated in terms of localization accuracy, energy efficiency, and network coverage.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"623 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123953692","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}
Intelligent transportation systems serve as important technologies to improve traffic safety, mobility, cost and environmental sustainability. Towards that end, a variety of applications and driver advisory tools have been developed. To work efficiently, many require knowledge of not only street maps but also elements affecting traffic flow. The most obvious elements are traffic lights and stop signs, which we shall henceforth call traffic regulators. Unfortunately, information on traffic regulators is not widely available in public databases such as Open Street Map (OSM). Prior work described crowd-sourcing solutions to predict regulator type and locations. In this paper, we improve the prediction by offering a combination of map-based modeling and crowd-sensing solutions. The modeling component reverse engineers rules for placement of traffic regulators, allowing it to predict their locations and type based on map information. Where available, crowd-sourced vehicular GPS traces are incorporated into the prediction function to improve the results. The approach is evaluated across multiple cities and is shown to outperform both crowd-sourcing alone and map-based modeling alone. It achieves a prediction accuracy level above 97% in detecting the existence and determining the type of traffic regulators in the cities considered.
{"title":"Combining Map-Based Inference and Crowd-Sensing for Detecting Traffic Regulators","authors":"F. Saremi, T. Abdelzaher","doi":"10.1109/MASS.2015.18","DOIUrl":"https://doi.org/10.1109/MASS.2015.18","url":null,"abstract":"Intelligent transportation systems serve as important technologies to improve traffic safety, mobility, cost and environmental sustainability. Towards that end, a variety of applications and driver advisory tools have been developed. To work efficiently, many require knowledge of not only street maps but also elements affecting traffic flow. The most obvious elements are traffic lights and stop signs, which we shall henceforth call traffic regulators. Unfortunately, information on traffic regulators is not widely available in public databases such as Open Street Map (OSM). Prior work described crowd-sourcing solutions to predict regulator type and locations. In this paper, we improve the prediction by offering a combination of map-based modeling and crowd-sensing solutions. The modeling component reverse engineers rules for placement of traffic regulators, allowing it to predict their locations and type based on map information. Where available, crowd-sourced vehicular GPS traces are incorporated into the prediction function to improve the results. The approach is evaluated across multiple cities and is shown to outperform both crowd-sourcing alone and map-based modeling alone. It achieves a prediction accuracy level above 97% in detecting the existence and determining the type of traffic regulators in the cities considered.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129726707","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}
With the development of Location Based Services (LBSs), both academic researchers and industries have paid more attention to GPS-less mobile localization on mobile phones. The majority of the existing localization approaches have utilized signal-fingerprint as a metric for location determinations. However, one of the most challenging issues is the problem of uncertain fingerprints for building the fingerprint map, termed as the jigsaw puzzle problem. In this paper, for more accurate fingerprints of the mobile localization, we investigate the changes of Received Signal Strength Indication (RSSI) from the connected cell-towers over time along the mobile users' trajectories, termed as RSSI Time Series (RTS). Thus, we propose an RTS Assisted Localization System (RALS), which is a GPS-less outdoor mobile localization system. For localization, an RTS map is built on the back-end server, which consists of RTS harvested from the mobile phones, by the way of crowd sensing. The jigsaw puzzle problem slows down the map construction solely by the regular unintentional users with short-distance trajectories, and affects its efficiency. To speed up the map construction, we propose employing a few advanced intentional users with additional long-distance trajectories, at a higher cost than the regular user, this is called extra mile. Our extensional experiments verify the effectiveness of our localization system.
{"title":"RTS Assisted Mobile Localization: Mitigating Jigsaw Puzzle Problem of Fingerprint Space with Extra Mile","authors":"Chao Song, Jie Wu, Li Lu, Ming Liu","doi":"10.1109/MASS.2015.43","DOIUrl":"https://doi.org/10.1109/MASS.2015.43","url":null,"abstract":"With the development of Location Based Services (LBSs), both academic researchers and industries have paid more attention to GPS-less mobile localization on mobile phones. The majority of the existing localization approaches have utilized signal-fingerprint as a metric for location determinations. However, one of the most challenging issues is the problem of uncertain fingerprints for building the fingerprint map, termed as the jigsaw puzzle problem. In this paper, for more accurate fingerprints of the mobile localization, we investigate the changes of Received Signal Strength Indication (RSSI) from the connected cell-towers over time along the mobile users' trajectories, termed as RSSI Time Series (RTS). Thus, we propose an RTS Assisted Localization System (RALS), which is a GPS-less outdoor mobile localization system. For localization, an RTS map is built on the back-end server, which consists of RTS harvested from the mobile phones, by the way of crowd sensing. The jigsaw puzzle problem slows down the map construction solely by the regular unintentional users with short-distance trajectories, and affects its efficiency. To speed up the map construction, we propose employing a few advanced intentional users with additional long-distance trajectories, at a higher cost than the regular user, this is called extra mile. Our extensional experiments verify the effectiveness of our localization system.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128252997","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}
Even with modern physical-layer technologies in LTE networks, the capacity of cellular networks is still far from sufficient to satisfy the insatiable bandwidth demand of mobile applications. Owing to common interests among mobile users, Device-to-Device (D2D) communication has emerged as a viable alternative to offload cellular traffic, with the promise of substantially alleviating the need for cellular network bandwidth. In this paper, we first carry out an extensive theoretical analysis based on a game theoretic approach, and show that the objective of maximized cellular offloading is equivalent to maximizing the social welfare in a trading network, where the content to be shared is the commodity, and mobile users are buyers or sellers. We next design Rally, a set of distributed strategies that can converge to a sub game perfect Nash equilibrium in the content sharing game. Both our theoretical analyses and simulation results have shown the effectiveness of Rally, in that it can indeed maximize cellular traffic offloading through D2D communication.
{"title":"Rally: Device-to-Device Content Sharing in LTE Networks as a Game","authors":"Jingjie Jiang, Yifei Zhu, Bo Li, Baochun Li","doi":"10.1109/MASS.2015.77","DOIUrl":"https://doi.org/10.1109/MASS.2015.77","url":null,"abstract":"Even with modern physical-layer technologies in LTE networks, the capacity of cellular networks is still far from sufficient to satisfy the insatiable bandwidth demand of mobile applications. Owing to common interests among mobile users, Device-to-Device (D2D) communication has emerged as a viable alternative to offload cellular traffic, with the promise of substantially alleviating the need for cellular network bandwidth. In this paper, we first carry out an extensive theoretical analysis based on a game theoretic approach, and show that the objective of maximized cellular offloading is equivalent to maximizing the social welfare in a trading network, where the content to be shared is the commodity, and mobile users are buyers or sellers. We next design Rally, a set of distributed strategies that can converge to a sub game perfect Nash equilibrium in the content sharing game. Both our theoretical analyses and simulation results have shown the effectiveness of Rally, in that it can indeed maximize cellular traffic offloading through D2D communication.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127253048","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 database-driven spectrum access system recently attracted increasing amounts of attention. It has more benefits compared to the traditional sensing-based systems. To build a more practical and reliable system, a hybrid sensing-based and database-driven spectrum access system is a promising solution. In this paper, we consider the integration problem of the database information and sensing results, which is a very important factor in order in realizing the hybrid system. We propose the integration framework, which is implemented on the database engine. The framework is divided into two main components. The first one is to process the sensing results, which contains the predictions for locations without sensing results, and the fusion policy on the sensing samples. The second component is the dynamic integration process of the generated sensing results and the database information. We first model the evaluation of the integration results as a Partially Observable Markov Decision Process (POMDP), which enables the database engine to know its current status. Then, we propose an iterative algorithm for the database engine to dynamically adjust its integration policy. In this way, the balanced status of the generated spectrum map is maintained. Simulations are conducted to reveal the performance of our framework.
{"title":"Integration of Spectrum Database and Sensing Results for Hybrid Spectrum Access Systems","authors":"Ying Dai, Jie Wu","doi":"10.1109/MASS.2015.114","DOIUrl":"https://doi.org/10.1109/MASS.2015.114","url":null,"abstract":"The database-driven spectrum access system recently attracted increasing amounts of attention. It has more benefits compared to the traditional sensing-based systems. To build a more practical and reliable system, a hybrid sensing-based and database-driven spectrum access system is a promising solution. In this paper, we consider the integration problem of the database information and sensing results, which is a very important factor in order in realizing the hybrid system. We propose the integration framework, which is implemented on the database engine. The framework is divided into two main components. The first one is to process the sensing results, which contains the predictions for locations without sensing results, and the fusion policy on the sensing samples. The second component is the dynamic integration process of the generated sensing results and the database information. We first model the evaluation of the integration results as a Partially Observable Markov Decision Process (POMDP), which enables the database engine to know its current status. Then, we propose an iterative algorithm for the database engine to dynamically adjust its integration policy. In this way, the balanced status of the generated spectrum map is maintained. Simulations are conducted to reveal the performance of our framework.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132318888","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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