The Experts below are selected from a list of 16062 Experts worldwide ranked by ideXlab platform

Canfeng Chen - One of the best experts on this subject based on the ideXlab platform.

  • adaptive Device Discovery in bluetooth low energy networks
    Vehicular Technology Conference, 2013
    Co-Authors: Jia Liu, Canfeng Chen
    Abstract:

    Bluetooth Low Energy (BLE) is a newly emerged technology targeting at low-power, low-cost wireless communications within medium or short range. Since BLE is well designed in favor of Wireless Body Area Networks (WBANs) or Wireless Personal Area Networks (WPANs), fast network access has been considered an important issue for users. This paper studies the performance about BLE Device Discovery particularly with multiple Devices. An analytical model is developed, based on classical ALOHA analysis, in consideration of three advertising channels of BLE. In addition, an enhanced mechanism is proposed enabling BLE scanner/initiator to learn the network contention and adjust parameters accordingly, so as to achieve lower latency. Through extensive simulations, the model has been validated highly accurate, and the proposed mechanism has shown its effectiveness in reducing unexpected long latency in crowd BLE networks.

  • Energy analysis of Device Discovery for bluetooth low energy
    IEEE Vehicular Technology Conference, 2013
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma, Ying Xu
    Abstract:

    Bluetooth Low Energy (BLE) is drawing more and more attention due to its recent appearance in consumer electronic products. As a low-power wireless solution, BLE provides attractive energy performance that makes it particularly suitable for portable, battery-driven electronic Devices. Although there are some prior arts focusing on BLE energy performance, it still lacks a thorough study on the important aspect of Device Discovery. Such energy cost, introduced by intermittent scanning or connection setup, could seriously affect the battery endurance ability of the Devices. In this paper, we present quantitative analysis on the neighbor Discovery energy for BLE. The modeling results that built upon measurement of CC2541 Mini-Development Kit have been validated quite accurate via extensive experiments. In addition, several interesting conclusions are found while investigating the achieved energy model, which may provide precious guidelines to the design of energy-efficient applications for BLE.

  • Modeling and performance analysis of Device Discovery in Bluetooth Low Energy networks
    GLOBECOM - IEEE Global Telecommunications Conference, 2012
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma
    Abstract:

    Bluetooth Low Energy (BT LE) is a low power air interface technology recently released by the Bluetooth Special Interest Group (BT SIG). As a promising radio, BT LE realizes many designing features to fulfill foreseeable requirements of short range communication, such as fast Device Discovery, power-saving transmitting, encryption and authentication, etc. In this paper, we focus on the modeling and performance analyzing of the Device Discovery process in BT LE networks. A general model for Device Discovery on multi-channel is proposed primarily, which is then tailored and simplified for the BT LE case, where three broadcasting channels are used. Via theoretical analysis, our study reveals that some potential pitfalls are residing in the current version of BT LE specification, i.e. improper parameter settings can significantly deteriorate the Device Discovery latency and increase meaningless energy consumption. We accordingly propose several strategies seeking ways to tackle the problem. The results of extensive simulation show that our strategies can largely reduce undesirable latency and effectively improve the efficiency of Device Discovery in BT LE networks.

Ying Xu - One of the best experts on this subject based on the ideXlab platform.

  • Energy analysis of Device Discovery for bluetooth low energy
    IEEE Vehicular Technology Conference, 2013
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma, Ying Xu
    Abstract:

    Bluetooth Low Energy (BLE) is drawing more and more attention due to its recent appearance in consumer electronic products. As a low-power wireless solution, BLE provides attractive energy performance that makes it particularly suitable for portable, battery-driven electronic Devices. Although there are some prior arts focusing on BLE energy performance, it still lacks a thorough study on the important aspect of Device Discovery. Such energy cost, introduced by intermittent scanning or connection setup, could seriously affect the battery endurance ability of the Devices. In this paper, we present quantitative analysis on the neighbor Discovery energy for BLE. The modeling results that built upon measurement of CC2541 Mini-Development Kit have been validated quite accurate via extensive experiments. In addition, several interesting conclusions are found while investigating the achieved energy model, which may provide precious guidelines to the design of energy-efficient applications for BLE.

Jun Liu - One of the best experts on this subject based on the ideXlab platform.

  • Energy analysis of Device Discovery for bluetooth low energy
    IEEE Vehicular Technology Conference, 2013
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma, Ying Xu
    Abstract:

    Bluetooth Low Energy (BLE) is drawing more and more attention due to its recent appearance in consumer electronic products. As a low-power wireless solution, BLE provides attractive energy performance that makes it particularly suitable for portable, battery-driven electronic Devices. Although there are some prior arts focusing on BLE energy performance, it still lacks a thorough study on the important aspect of Device Discovery. Such energy cost, introduced by intermittent scanning or connection setup, could seriously affect the battery endurance ability of the Devices. In this paper, we present quantitative analysis on the neighbor Discovery energy for BLE. The modeling results that built upon measurement of CC2541 Mini-Development Kit have been validated quite accurate via extensive experiments. In addition, several interesting conclusions are found while investigating the achieved energy model, which may provide precious guidelines to the design of energy-efficient applications for BLE.

  • Modeling and performance analysis of Device Discovery in Bluetooth Low Energy networks
    GLOBECOM - IEEE Global Telecommunications Conference, 2012
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma
    Abstract:

    Bluetooth Low Energy (BT LE) is a low power air interface technology recently released by the Bluetooth Special Interest Group (BT SIG). As a promising radio, BT LE realizes many designing features to fulfill foreseeable requirements of short range communication, such as fast Device Discovery, power-saving transmitting, encryption and authentication, etc. In this paper, we focus on the modeling and performance analyzing of the Device Discovery process in BT LE networks. A general model for Device Discovery on multi-channel is proposed primarily, which is then tailored and simplified for the BT LE case, where three broadcasting channels are used. Via theoretical analysis, our study reveals that some potential pitfalls are residing in the current version of BT LE specification, i.e. improper parameter settings can significantly deteriorate the Device Discovery latency and increase meaningless energy consumption. We accordingly propose several strategies seeking ways to tackle the problem. The results of extensive simulation show that our strategies can largely reduce undesirable latency and effectively improve the efficiency of Device Discovery in BT LE networks.

Yan Ma - One of the best experts on this subject based on the ideXlab platform.

  • Energy analysis of Device Discovery for bluetooth low energy
    IEEE Vehicular Technology Conference, 2013
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma, Ying Xu
    Abstract:

    Bluetooth Low Energy (BLE) is drawing more and more attention due to its recent appearance in consumer electronic products. As a low-power wireless solution, BLE provides attractive energy performance that makes it particularly suitable for portable, battery-driven electronic Devices. Although there are some prior arts focusing on BLE energy performance, it still lacks a thorough study on the important aspect of Device Discovery. Such energy cost, introduced by intermittent scanning or connection setup, could seriously affect the battery endurance ability of the Devices. In this paper, we present quantitative analysis on the neighbor Discovery energy for BLE. The modeling results that built upon measurement of CC2541 Mini-Development Kit have been validated quite accurate via extensive experiments. In addition, several interesting conclusions are found while investigating the achieved energy model, which may provide precious guidelines to the design of energy-efficient applications for BLE.

  • Modeling and performance analysis of Device Discovery in Bluetooth Low Energy networks
    GLOBECOM - IEEE Global Telecommunications Conference, 2012
    Co-Authors: Jun Liu, Canfeng Chen, Yan Ma
    Abstract:

    Bluetooth Low Energy (BT LE) is a low power air interface technology recently released by the Bluetooth Special Interest Group (BT SIG). As a promising radio, BT LE realizes many designing features to fulfill foreseeable requirements of short range communication, such as fast Device Discovery, power-saving transmitting, encryption and authentication, etc. In this paper, we focus on the modeling and performance analyzing of the Device Discovery process in BT LE networks. A general model for Device Discovery on multi-channel is proposed primarily, which is then tailored and simplified for the BT LE case, where three broadcasting channels are used. Via theoretical analysis, our study reveals that some potential pitfalls are residing in the current version of BT LE specification, i.e. improper parameter settings can significantly deteriorate the Device Discovery latency and increase meaningless energy consumption. We accordingly propose several strategies seeking ways to tackle the problem. The results of extensive simulation show that our strategies can largely reduce undesirable latency and effectively improve the efficiency of Device Discovery in BT LE networks.

Mohammed Atiquzzaman - One of the best experts on this subject based on the ideXlab platform.

  • energy efficient Device Discovery for reliable communication in 5g based iot and bsns using unmanned aerial vehicles
    Journal of Network and Computer Applications, 2017
    Co-Authors: Vishal Sharma, Fei Song, Ilsun You, Mohammed Atiquzzaman
    Abstract:

    Abstract Connectivity among real-world entities is one of the primary requirements of the upcoming Fifth Generation Public Private Partnership (5G-PPP). Both Internet of Things (IoT) and Body Sensor Networks (BSNs) are major applications of 5G networks. However, over-consumption of energy for Device Discovery, which includes registration, removal, querying, routing etc, quickly depletes the resources of a node, which may further influence the whole network. There are a number of approaches which provide energy efficient mechanisms for the selection of Devices in a network operating with different types of nodes; however, these approaches are unable to maintain a high transmission capacity along with energy conservation and fault-tolerance. In this paper, an energy efficient approach for Device Discovery in 5G-based IoT and BSNs using multiple Unmanned Aerial Vehicles (UAVs) is presented. A functional architecture is proposed, which utilizes XML charts to perform Device Discovery on the basis of networks state cost and available energy. The significant gains achieved in energy consumption, end to end delays and packet loss show that our solution is capable of providing energy efficient Device Discovery with 78.4% reduction in the overall energy consumption compared to existing solutions. The advantage of UAVs in energy efficient networking is illustrated using numerical analysis which suggests 75% enhancement in the energy-asymptote of the existing networks.