Infrastructure-Less Communication Platform for Off-The-Shelf Android Smartphones

Oide, Takuma; Abe, Toru; Suganuma, Takuo

doi:10.3390/s18030776

Cited by 8 publications

(11 citation statements)

References 21 publications

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“…Cordova plugins for accessing the user's location, also while the app is running in the background, are readily available. 39 When tracking the user's location, frequent visits at points of interest or restaurants can indicate preference, and ratings can be inferred. When implementing location tracking, the tradeoff is typically between accuracy, frequency, and battery drain.…”

Section: ) Automatic Data Trackingmentioning

confidence: 99%

MobRec: Mobile Platform for Decentralized Recommender Systems

Beierle¹

2021

T-Labs Series in Telecommunication Services

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Section: ) Automatic Data Trackingmentioning

confidence: 99%

MobRec: Mobile Platform for Decentralized Recommender Systems

Beierle¹

2021

T-Labs Series in Telecommunication Services

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“…The WiFi Alliance developed another WiFi mode for device-to-device communication, WiFi Direct, which is supported on Android devices with version 4.0 and higher [39]. 8 There are several related papers dealing with WiFi Direct for device-to-device communication [18], [37], [40]- [43].…”

Section: B Wifimentioning

confidence: 99%

“…Cordova plugins for accessing the user's location, also while the app is running in the background, are readily available 39 . When tracking the user's location, frequent visits at points of This work is licensed under a Creative Commons Attribution 4.0 License.…”

Section: ) Automatic Data Trackingmentioning

confidence: 99%

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MobRec — Mobile Platform for Decentralized Recommender Systems

Beierle

Egger

2020

IEEE Access

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Recommender systems recommend new movies, music, restaurants, etc. Typically, service providers organize such systems in a centralized way, holding all the data. Biases in the recommender systems are not transparent to the user and lock-in effects might make it inconvenient for the user to switch providers. In this paper, we present the concept, design, and implementation of MobRec, a mobile platform that decentralizes the data collection, data storage, and recommendation process. MobRec's architecture does not need any backend and solely consists of the users' smartphones, which already contain the users' preferences and ratings. Being in proximity in public places or public transportation, data is exchanged in a device-to-device manner, building local databases that can recommend new items. One of biggest challenges of such a system is the implementation of unobtrusive device-to-device data exchange on off-the-shelf Android devices and iPhones. MobRec facilitates such data exchange, building on Google Nearby Messages with Bluetooth Low Energy. We achieve the successful exchange of data within 3 to 4 minutes, making it suitable for the described scenario. We demonstrate the feasibility of decentralized recommender systems and provide blueprints for the development of seamless multi-platform device-to-device communication.

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“…In [27], the authors used SDN (Software Defined Network) based method to organize the Wi-Fi Direct groups to reduce the overall interference in a Wi-Fi network. The authors in [29] propose to build multi-hop ad-hoc networks using Wi-Fi Direct. A similar approach is adopted in [30] for inter-group communication to build multi-hop networks in Wi-Fi Direct networks.…”

Section: The Wi-fi Direct Technologymentioning

confidence: 99%

Optimal Group Formation in Dense Wi-Fi Direct Networks for Content Distribution

2019

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Wi-Fi Direct enables direct communication between Wi-Fi devices by forming Peer to Peer (P2P) groups. In each P2P group, one device becomes the Group Owner (GO) and serves as an access point (AP) to connect the remaining devices. The group formation in Wi-Fi Direct has two major limitations. Firstly, it is initiated between two P2P devices only. It does not define any mechanism to allow more than two devices to contend for becoming GO. Secondly, it does not include a selection criteria for the GO (to allow vendor-specific implementation). These limitations can significantly reduce the performance of the Wi-Fi Direct networks. Earlier works addressed these issues using heuristic approaches which do not guarantee optimum performance. Furthermore, the selection of multiple GOs (in dense networks) has not been rigorously investigated in the literature. This paper proposes a modified group formation scheme among multiple devices. The proposed scheme formulates the GO selection problem as an optimization problem which is solved using integer programming (IP). The GOs are selected based on link capacities with the objective to maximize the overall network throughput. In multicast applications, the proposed scheme is implemented such that the minimum achievable rate by any device is maximized. The performance of the proposed GO selection scheme is extensively evaluated through realistic simulation performed in ns-3. The results reveal significant performance gains in terms of group formation time and network throughput. For instance, a throughput gain of 19.8% is achieved using a single GO. The gain is further improved by using a higher number of GOs. In multicast applications, a Packet Loss Ratio (PLR) of 2.8% is maintained. Detailed performance evaluation is presented for several scenarios considering different network sizes, number of GOs, and distribution of user's locations. Moreover, a comparison with state-of-the-art schemes is presented to validate the advantages of the proposed scheme.

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Infrastructure-Less Communication Platform for Off-The-Shelf Android Smartphones

Cited by 8 publications

References 21 publications

MobRec: Mobile Platform for Decentralized Recommender Systems

MobRec: Mobile Platform for Decentralized Recommender Systems

MobRec — Mobile Platform for Decentralized Recommender Systems

Optimal Group Formation in Dense Wi-Fi Direct Networks for Content Distribution

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