Stratos Keranidis, Kostas Chounos, T. Korakis, I. Koutsopoulos, L. Tassiulas
In this work, we present the AGILE Spectrum Adaptation system that is able to dynamically tune the channel central frequency and bandwidth of wireless links in an adaptive to the interference and traffic conditions way. The developed system is able to detect under-utilised spectrum fragments and optimally adjust the occupied spectrum. Through the online execution of 3 specifically designed experimental scenarios, we demonstrate the ability to implement distributed spectrum adaptation in commercial WLAN deployments, along with the obtained performance benefits.
{"title":"Demo: enabling AGILE spectrum adaptation in commercial 802.11 WLAN deployments","authors":"Stratos Keranidis, Kostas Chounos, T. Korakis, I. Koutsopoulos, L. Tassiulas","doi":"10.1145/2639108.2641752","DOIUrl":"https://doi.org/10.1145/2639108.2641752","url":null,"abstract":"In this work, we present the AGILE Spectrum Adaptation system that is able to dynamically tune the channel central frequency and bandwidth of wireless links in an adaptive to the interference and traffic conditions way. The developed system is able to detect under-utilised spectrum fragments and optimally adjust the occupied spectrum. Through the online execution of 3 specifically designed experimental scenarios, we demonstrate the ability to implement distributed spectrum adaptation in commercial WLAN deployments, along with the obtained performance benefits.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124023414","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}
K. Sundaresan, M. Khojastepour, Eugene Chai, S. Rangarajan
Enabling wireless full-duplex (from an AP) with multiple half-duplex (HD) clients is key to widespread adoption of full-duplex (FD) in commercial networks. However, enabling FD in such networks is fundamentally challenged by a new form of uplink-downlink interference (UDI), arising between HD clients operating simultaneously in the uplink and downlink directions. In this context, we first show that spatial interference alignment (IA) between clients is an effective and scalable technique to address UDI and hence enable FD in these networks, especially in the presence of MIMO. We then present our solution and system FDoS: Full-Duplex without Stringsthat incorporates this notion. We build the theory of applying spatial IA to full-duplex networks in general and present elegant, implementation-friendly constructions for generating IA solutions, by leveraging the structure of interference specific to these networks. In the process, FDoS shows that only four HD clients are sufficient to eliminate UDI through IA and enable 2N streams at an N transceiver AP. FDoS also includes an efficient MAC design at the AP to handle clients with heterogeneous antenna capabilities, maximize the throughput of the enabled streams in the FD session as well as reduce the overhead incurred in FDoS by half by facilitating a distributed implementation. A prototype of FDoS on WARP radios showcases its ability to address UDI effectively, and hence enable 2N streams (for N=2,4) in varied settings with just four HD clients, and sustain rate gains of 1.75-2x over HD MU-MIMO systems.
{"title":"Full-duplex without strings: enabling full-duplex with half-duplex clients","authors":"K. Sundaresan, M. Khojastepour, Eugene Chai, S. Rangarajan","doi":"10.1145/2639108.2639127","DOIUrl":"https://doi.org/10.1145/2639108.2639127","url":null,"abstract":"Enabling wireless full-duplex (from an AP) with multiple half-duplex (HD) clients is key to widespread adoption of full-duplex (FD) in commercial networks. However, enabling FD in such networks is fundamentally challenged by a new form of uplink-downlink interference (UDI), arising between HD clients operating simultaneously in the uplink and downlink directions. In this context, we first show that spatial interference alignment (IA) between clients is an effective and scalable technique to address UDI and hence enable FD in these networks, especially in the presence of MIMO. We then present our solution and system FDoS: Full-Duplex without Stringsthat incorporates this notion. We build the theory of applying spatial IA to full-duplex networks in general and present elegant, implementation-friendly constructions for generating IA solutions, by leveraging the structure of interference specific to these networks. In the process, FDoS shows that only four HD clients are sufficient to eliminate UDI through IA and enable 2N streams at an N transceiver AP. FDoS also includes an efficient MAC design at the AP to handle clients with heterogeneous antenna capabilities, maximize the throughput of the enabled streams in the FD session as well as reduce the overhead incurred in FDoS by half by facilitating a distributed implementation. A prototype of FDoS on WARP radios showcases its ability to address UDI effectively, and hence enable 2N streams (for N=2,4) in varied settings with just four HD clients, and sustain rate gains of 1.75-2x over HD MU-MIMO systems.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124063579","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}
Maryam Ahmadi, Jianping Pan, Lei Zheng, Lin X. Cai, Fei Tong
Geometrical distance distribution (GDD) between nodes in wireless communication networks plays a significant role in modeling network performance metrics. Existing work on obtaining GDD assumes the network geometry to be a regular one, such as circle and square. Due to the various complex effects of wireless signals, however, the network geometry usually is quite irregular. Therefore, this paper proposes a novel systematic and unified approach to obtain the GDD between two random nodes associated with arbitrary network geometries. To the best of our knowledge, this is the first work that will fill the gap in the literature of this field.
{"title":"Poster: geometrical distance distribution for modeling performance metrics in wireless communication networks","authors":"Maryam Ahmadi, Jianping Pan, Lei Zheng, Lin X. Cai, Fei Tong","doi":"10.1145/2639108.2642905","DOIUrl":"https://doi.org/10.1145/2639108.2642905","url":null,"abstract":"Geometrical distance distribution (GDD) between nodes in wireless communication networks plays a significant role in modeling network performance metrics. Existing work on obtaining GDD assumes the network geometry to be a regular one, such as circle and square. Due to the various complex effects of wireless signals, however, the network geometry usually is quite irregular. Therefore, this paper proposes a novel systematic and unified approach to obtain the GDD between two random nodes associated with arbitrary network geometries. To the best of our knowledge, this is the first work that will fill the gap in the literature of this field.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116623330","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}
In this paper, we describe the in-lane communication framework that enables the communication between vehicles on the same lane. The system creates a unique signature for each lane using smartphone inertial sensors. The calculated lane signature will be attached with each broadcasted message, where other vehicles on the street compare it with their own lane signature to decide if the received message came from a vehicle on the same lane or not. The paper concentrates on finding the right features that can be used to identify a lane in a road. To identify a lane with a unique signature, the paper proposes a combination of driving features and road features. The paper uses the inertial sensors because the current GPS systems are not accurate enough to locate vehicles with a lane level accuracy. The ability to establish a communication channel between vehicles on the same lane can enhance the road safety and enable several interesting navigation applications.
{"title":"Poster: in-lane communication framework using smartphone's inertial sensors","authors":"Abdulla Alasaadi, T. Nadeem","doi":"10.1145/2639108.2642912","DOIUrl":"https://doi.org/10.1145/2639108.2642912","url":null,"abstract":"In this paper, we describe the in-lane communication framework that enables the communication between vehicles on the same lane. The system creates a unique signature for each lane using smartphone inertial sensors. The calculated lane signature will be attached with each broadcasted message, where other vehicles on the street compare it with their own lane signature to decide if the received message came from a vehicle on the same lane or not. The paper concentrates on finding the right features that can be used to identify a lane in a road. To identify a lane with a unique signature, the paper proposes a combination of driving features and road features. The paper uses the inertial sensors because the current GPS systems are not accurate enough to locate vehicles with a lane level accuracy. The ability to establish a communication channel between vehicles on the same lane can enhance the road safety and enable several interesting navigation applications.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123438092","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}
Liqun Li, G. Shen, Chunshui Zhao, T. Moscibroda, Jyh-Han Lin, Feng Zhao
Diversity in training data density and environment locality is intrinsic in the real-world deployment of indoor localization systems and has a major impact on the performance of existing localization approaches. In this paper, through micro-benchmarks, we find that fingerprint-based approaches are preferable in scenarios where a dense database is available; while model-based approaches are the method of choice in the case of sparse data. It should be noted, however, that practical situations are complex. A single deployment often features both sparse and dense sampled areas. Furthermore, the internal layout affects the propagation of radio signals and exhibits environmental impacts. A certain number of measurement samples may be sufficient for one part of the building, but entirely insufficient for another. Thus, finding the right indoor localization algorithm for a given large-scale deployment is challenging, if not impossible; there is no one-size-fits-all indoor localization approach. Realizing the fundamental fact that the quality of the location database capturing the actual radio map dictates localization accuracy, in this paper, we propose Modellet, an algorithmic approach that optimally approximates the actual radio map by unifying model-based and fingerprint-based approaches. Modellet represents the radio map using a fingerprint-cloud that incorporates both measured real fingerprints and virtual fingerprints, which are computed from models with a local support, based on the key concept of the supporting set. We evaluate Modellet with data collected from an office building as well as 13 large-scale deployment venues (shopping malls and airports), located across China, U.S., and Germany. Comparing Modellet with two representative baseline approaches, RADAR and EZPerfect, demonstrates that Modellet effectively adapts to different data densities and environmental conditions, substantially outperforming existing approaches.
{"title":"Experiencing and handling the diversity in data density and environmental locality in an indoor positioning service","authors":"Liqun Li, G. Shen, Chunshui Zhao, T. Moscibroda, Jyh-Han Lin, Feng Zhao","doi":"10.1145/2639108.2639118","DOIUrl":"https://doi.org/10.1145/2639108.2639118","url":null,"abstract":"Diversity in training data density and environment locality is intrinsic in the real-world deployment of indoor localization systems and has a major impact on the performance of existing localization approaches. In this paper, through micro-benchmarks, we find that fingerprint-based approaches are preferable in scenarios where a dense database is available; while model-based approaches are the method of choice in the case of sparse data. It should be noted, however, that practical situations are complex. A single deployment often features both sparse and dense sampled areas. Furthermore, the internal layout affects the propagation of radio signals and exhibits environmental impacts. A certain number of measurement samples may be sufficient for one part of the building, but entirely insufficient for another. Thus, finding the right indoor localization algorithm for a given large-scale deployment is challenging, if not impossible; there is no one-size-fits-all indoor localization approach. Realizing the fundamental fact that the quality of the location database capturing the actual radio map dictates localization accuracy, in this paper, we propose Modellet, an algorithmic approach that optimally approximates the actual radio map by unifying model-based and fingerprint-based approaches. Modellet represents the radio map using a fingerprint-cloud that incorporates both measured real fingerprints and virtual fingerprints, which are computed from models with a local support, based on the key concept of the supporting set. We evaluate Modellet with data collected from an office building as well as 13 large-scale deployment venues (shopping malls and airports), located across China, U.S., and Germany. Comparing Modellet with two representative baseline approaches, RADAR and EZPerfect, demonstrates that Modellet effectively adapts to different data densities and environmental conditions, substantially outperforming existing approaches.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132316729","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 next frontier of mobility -- from behavioral analysis for the app ecosystem to geolocation on steroids -- presents challenges as tough as the opportunities are expansive. What is the TCP/IP of the Internet of Things era? And who will build it? Hyper-aware smartphones that know you're in the snack aisle are great for retailers, but who's addressing the security implications? The industry is charting its strategic course, but there is an exciting opportunity for researchers and academia to provide the coordinates towards the solutions to mobility's hardest problems. In this keynote, Kit Colbert, Chief Technology Officer for End-User Computing at VMware, will discuss the unsolved challenges in mobility, and the possibilities that will be unlocked when the industry and academia partner on finding the answers.
{"title":"BYOzzzz: focusing on the unsolved challenges in mobility, an industry perspective","authors":"Kit Colbert","doi":"10.1145/2639108.2639418","DOIUrl":"https://doi.org/10.1145/2639108.2639418","url":null,"abstract":"The next frontier of mobility -- from behavioral analysis for the app ecosystem to geolocation on steroids -- presents challenges as tough as the opportunities are expansive. What is the TCP/IP of the Internet of Things era? And who will build it? Hyper-aware smartphones that know you're in the snack aisle are great for retailers, but who's addressing the security implications? The industry is charting its strategic course, but there is an exciting opportunity for researchers and academia to provide the coordinates towards the solutions to mobility's hardest problems. In this keynote, Kit Colbert, Chief Technology Officer for End-User Computing at VMware, will discuss the unsolved challenges in mobility, and the possibilities that will be unlocked when the industry and academia partner on finding the answers.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121047128","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 rapid rise in variety of available smartphones today and their rich sensing capabilities, there is an increasing interest in using mobile sensing in large-scale experiments and commercial applications. Motivated by the lack of a universal, multi-platform library, in this paper we present SensingKit, an efficient, open-source, client-server system that supports both iOS and Android mobile devices. SensingKit is capable of continuous sensing the device's motion (Accelerometer, Gyroscope, Magnetometer), location (GPS) and proximity to other smartphones (Bluetooth Smart). The data are temporarily saved to the device's memory and transmitted to a server for further analysis over any Internet connection. We believe that this platform will be beneficial to all researchers and developers who need to perform mobile sensing in their applications and experiments.
{"title":"Poster: SensingKit: a multi-platform mobile sensing framework for large-scale experiments","authors":"Kleomenis Katevas, H. Haddadi, L. Tokarchuk","doi":"10.1145/2639108.2642910","DOIUrl":"https://doi.org/10.1145/2639108.2642910","url":null,"abstract":"With the rapid rise in variety of available smartphones today and their rich sensing capabilities, there is an increasing interest in using mobile sensing in large-scale experiments and commercial applications. Motivated by the lack of a universal, multi-platform library, in this paper we present SensingKit, an efficient, open-source, client-server system that supports both iOS and Android mobile devices. SensingKit is capable of continuous sensing the device's motion (Accelerometer, Gyroscope, Magnetometer), location (GPS) and proximity to other smartphones (Bluetooth Smart). The data are temporarily saved to the device's memory and transmitted to a server for further analysis over any Internet connection. We believe that this platform will be beneficial to all researchers and developers who need to perform mobile sensing in their applications and experiments.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121789063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 20th annual international conference on Mobile computing and networking","authors":"","doi":"10.1145/2639108","DOIUrl":"https://doi.org/10.1145/2639108","url":null,"abstract":"","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115061462","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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