Analytical and experimental performance evaluation of BLE neighbor discovery process including non-idealities of real chipsets

The purpose of this paper is to evaluate from a real perspective the performance of Bluetooth Low Energy (BLE) as a technology that enables fast and reliable discovery of a large number of users/devices in a short period of time. The BLE standard specifies a wide range of configurable parameter values that determine the discovery process and need to be set according to the particular application requirements. Many previous works have been addressed to investigate the discovery process through analytical and simulation models, according to the ideal specification of the standard. However, measurements show that additional scanning gaps appear in the scanning process, which reduce the discovery capabilities. These gaps have been identified in all of the analyzed devices and respond to both regular patterns and variable events associated with the decoding process. We have demonstrated that these non-idealities, which are not taken into account in other studies, have a severe impact on the discovery process performance. Extensive performance evaluation for a varying number of devices and feasible parameter combinations has been done by comparing simulations and experimental measurements. This work also includes a simple mathematical model that closely matches both the standard implementation and the different chipset peculiarities for any possible parameter value specified in the standard and for any number of simultaneous advertising devices under scanner coverage

Proposal and evaluation of BLE discovery process based on new features of bluetooth 5.0

The device discovery process is one of the most crucial aspects in real deployments of sensor networks. Recently, several works have analyzed the topic of Bluetooth Low Energy (BLE) device discovery through analytical or simulation models limited to version 4.x. Non-connectable and non-scannable undirected advertising has been shown to be a reliable alternative for discovering a high number of devices in a relatively short time period. However, new features of Bluetooth 5.0 allow us to define a variant on the device discovery process, based on BLE scannable undirected advertising events, which results in higher discovering capacities and also lower power consumption. In order to characterize this new device discovery process, we experimentally model the real device behavior of BLE scannable undirected advertising events. Non-detection packet probability, discovery probability, and discovery latency for a varying number of devices and parameters are compared by simulations and experimental measurements. We demonstrate that our proposal outperforms previous works, diminishing the discovery time and increasing the potential user device density. A mathematical model is also developed in order to easily obtain a measure of the potential capacity in high density scenarios.Peer ReviewedPostprint (published version

Proposal and evaluation of BLE discovery process based on new features of bluetooth 5.0

The device discovery process is one of the most crucial aspects in real deployments of sensor networks. Recently, several works have analyzed the topic of Bluetooth Low Energy (BLE) device discovery through analytical or simulation models limited to version 4.x. Non-connectable and non-scannable undirected advertising has been shown to be a reliable alternative for discovering a high number of devices in a relatively short time period. However, new features of Bluetooth 5.0 allow us to define a variant on the device discovery process, based on BLE scannable undirected advertising events, which results in higher discovering capacities and also lower power consumption. In order to characterize this new device discovery process, we experimentally model the real device behavior of BLE scannable undirected advertising events. Non-detection packet probability, discovery probability, and discovery latency for a varying number of devices and parameters are compared by simulations and experimental measurements. We demonstrate that our proposal outperforms previous works, diminishing the discovery time and increasing the potential user device density. A mathematical model is also developed in order to easily obtain a measure of the potential capacity in high density scenarios

Anti-Collision Adaptations of BLE Active Scanning for Dense IoT Tracking Applications

Bluetooth low energy (BLE) is one of most promising technologies to enable the Internet-of-Things (IoT) paradigm. The BLE neighbor discovery process (NDP) based on active scanning may be the core of multiple IoT applications in which a large and varying number of users/devices/tags must be detected in a short period of time. Minimizing the discovery latency and maximizing the number of devices that can be discovered in a limited time are challenging issues due to collisions between frames sent by advertisers and scanners. The mechanism for resolution of collisions between scanners has a great impact on the achieved performance, but backoff in NDP has been poorly studied so far. This paper includes a detailed analysis of backoff in NDP, identifies and studies the factors involved in the process, reveals the limitations and problems presented by the algorithm suggested by the specifications and proposes simple and practical adaptations on scanner functionality. They are easily compatible with the current definitions of the standard, which together with a new proposal for the backoff scheme, may significantly improve the discovery latencies and, thus, the probability of discovering a large number of devices in high density scenarios

Low-cost test measurement setup for real IoT BLE sensor device characterization

The methodology presented in this paper aims to characterize impairments shown by real devices which are usually neglected on standardized tests but that become very important in massive IoT scenarios. For instance, we have measured that real BLE scanners are not able to scan continuously even though they are configured to do so. Besides, we have also found and demonstrated that some manufacturers seem not to apply any backoff mechanism although it is mandatory. These two unexpected behaviors have a significant impact on the performance of massive wireless sensor networks based on BLE. So, it becomes necessary to characterize these and other impairments. The proposed tests are based on device current consumption measurements and their association with the information obtained from upper layers. We describe a new low-cost generic measurement setup and provide all the necessary data (configuration parameters, scripts, etc.) for applying the proposed methodology. As an example, we use it to profile the behavior of Bluetooth Low Energy devices. Furthermore, the proposed setup can also inspire researchers to characterize other wireless technology devices, like Wi-Fi, Zigbee, LoRa, etc

Fog-Driven Context-Aware Architecture for Node Discovery and Energy Saving Strategy for Internet of Things Environments

The consolidation of the Fog Computing paradigm and the ever-increasing diffusion of Internet of Things (IoT) and smart objects are paving the way toward new integrated solutions to efficiently provide services via short-mid range wireless connectivity. Being the most of the nodes mobile, the node discovery process assumes a crucial role for service seekers and providers, especially in IoT-fog environments where most of the devices run on battery. This paper proposes an original model and a fog-driven architecture for efficient node discovery in IoT environments. Our novel architecture exploits the location awareness provided by the fog paradigm to significantly reduce the power drain of the default baseline IoT discovery process. To this purpose, we propose a deterministic and competitive adaptive strategy to dynamically adjust our energy-saving techniques by deciding when to switch BLE interfaces ON/OFF based on the expected frequency of node approaching. Finally, the paper presents a thorough performance assessment that confirms the applicability of the proposed solution in several different applications scenarios. This evaluation aims also to highlight the impact of the nodes' dynamic arrival on discovery process performance

PSM-DMO: power save mode and discontinuous BLE mesh operation

The Bluetooth Low Energy (BLE) mesh profile, standardized by the Bluetooth Special Interest Group (SIG), has an increasing interest in IoT solutions. However, the standard assumes that relay and friend nodes should be continuously scanning the channel awaiting any incoming transmissions. This could be very inefficient in terms of energy consumption, particularly in application scenarios where the backbone of the mesh network cannot be powered and traffic is infrequent. Hence, we present a novel strategy, named PSM-DMO, that minimizes the scan periods and thus, significantly reduces the overall energy consumption of the mesh network. PSM-DMO is defined as a new and optional feature for the currently published BLE mesh specifications, coexists with the standard operation, and is implemented without modifying the core of the specification. The proposal, that ensures the reliability of the mesh operation, can be used in BLE sensor networks that can tolerate a certain transmission delay. PSM-DMO replaces the continuous scan by a periodic but asynchronous polling process whereby the relay and sink nodes interrogate their neighbors about the existence of data to receive or to retransmit through the network. Nodes only go into scan mode during the period of time the mesh network will be involved in the transmission and dissemination. This period is estimated by the node which is the source of data, it is announced to its neighbors and it is propagated consecutively by all the relay nodes until the destination. PSM-DMO allows a theoretical reduction in the energy consumption of relay nodes up to 99.24 %

PSM-DMO: power save mode and discontinuous BLE mesh operation

The Bluetooth Low Energy (BLE) mesh profile, standardized by the Bluetooth Special Interest Group (SIG), has an increasing interest in IoT solutions. However, the standard assumes that relay and friend nodes should be continuously scanning the channel awaiting any incoming transmissions. This could be very inefficient in terms of energy consumption, particularly in application scenarios where the backbone of the mesh network cannot be powered and traffic is infrequent. Hence, we present a novel strategy, named PSM-DMO, that minimizes the scan periods and thus, significantly reduces the overall energy consumption of the mesh network. PSM-DMO is defined as a new and optional feature for the currently published BLE mesh specifications, coexists with the standard operation, and is implemented without modifying the core of the specification. The proposal, that ensures the reliability of the mesh operation, can be used in BLE sensor networks that can tolerate a certain transmission delay. PSM-DMO replaces the continuous scan by a periodic but asynchronous polling process whereby the relay and sink nodes interrogate their neighbors about the existence of data to receive or to retransmit through the network. Nodes only go into scan mode during the period of time the mesh network will be involved in the transmission and dissemination. This period is estimated by the node which is the source of data, it is announced to its neighbors and it is propagated consecutively by all the relay nodes until the destination. PSM-DMO allows a theoretical reduction in the energy consumption of relay nodes up to 99.24 %.This work has been supported in part by the Spanish Ministry of Science through the projects RTI2018-099880-B-C32. RTI2018-095684-B-I00 and RTI2018-099063-B-I00 with ERFD funds, and by the Government of Aragon (Reference Group T31_20R).Peer ReviewedPostprint (published version

On the use of sniffers for spectrum occupancy measurements of Bluetooth low energy primary channels

The methods usually employed to measure channel occupancy show limitations in the context of Bluetooth Low Energy (BLE) advertisements. We propose and analyze the use of BLE sniffers as light and portable low-cost spectrum occupancy meters to be used in scenarios where real time signal analyzers are not adequate. For the measurement technique to be successful, several low-level effects must be considered. The paper argues about on-air time, receiving blind times due to processing and intra system interference, buffer saturation and frequency anchoring. Hence, a compensation procedure based on collision rate estimation is proposed. Results with the refined method show that occupancies of 40% can be measured with an overestimation error whose percentile 95% is 5 percentage points. This is reduced to 1.9 points when the occupancy is 15%. The sniffers perform in real time and are shown to correctly track short term load variations. The strategy has been successfully used to characterize occupancy in highly variable and loaded scenarios such as subway platforms and a shopping mall. Values up to 25% have been observed, which implies a relevant packet error rate. Hence, the tool can be used to make agile audits and configure the parameters that control communication redundancy in new or existing networks.The work by UPC has been funded by MCIN/ AEI /10.13039/501100011033 and by ERDF A way of making Europe, with the grant RTI2018-099880-B-C32 and PID2021-125799OA-I00. The work by I3A-UZ has been funded by MCIN/ AEI /10.13039/501100011033 and by ERDF A way of making Europe, with the grants RTI2018-095684-B-I00 and RTI2018-099063-B-I00, and by the Government of Aragon (Reference Group T31 20R).Peer ReviewedPostprint (published version

On the use of sniffers for spectrum occupancy measurements of Bluetooth low energy primary channels

The methods usually employed to measure channel occupancy show limitations in the context of Bluetooth Low Energy (BLE) advertisements. We propose and analyze the use of BLE sniffers as light and portable low-cost spectrum occupancy meters to be used in scenarios where real time signal analyzers are not adequate. For the measurement technique to be successful, several low-level effects must be considered. The paper argues about on-air time, receiving blind times due to processing and intra system interference, buffer saturation and frequency anchoring. Hence, a compensation procedure based on collision rate estimation is proposed. Results with the refined method show that occupancies of 40% can be measured with an overestimation error whose percentile 95% is 5 percentage points. This is reduced to 1.9 points when the occupancy is 15%. The sniffers perform in real time and are shown to correctly track short term load variations. The strategy has been successfully used to characterize occupancy in highly variable and loaded scenarios such as subway platforms and a shopping mall. Values up to 25% have been observed, which implies a relevant packet error rate. Hence, the tool can be used to make agile audits and configure the parameters that control communication redundancy in new or existing networks