Networking solutions for connecting bluetooth low energy devices - a comparison

Bluetooth Low Energy (BLE) mesh networks provide flexible and reliable communication among low-power sensor-enabled Internet of Things (IoT) devices, enabling them to communicate in a flexible and robust manner. Nonetheless, the majority of existing BLE-based mesh protocols operate as flooding-based piconet or scatternet overlays on top of existing Bluetooth star topologies. In contrast, the Ad hoc On-Demand Distance Vector (AODV) protocol used primarily in wireless ad hoc networks (WAHNs) is forwarding-based and therefore more efficient, with lower overheads. However, the packet delivery ratio (PDR) and link recovery time for AODV performs worse compared to flooding-based BLE protocols when encountering link disruptions. We propose the Multipath Optimized AODV (M-O-AODV) protocol to address these issues, with improved PDR and link robustness compared with other forwarding-based protocols. In addition, M-O-AODV achieved a PDR of 88%, comparable to the PDR of 92% for flooding-based BLE, unlike protocols such as Reverse-AODV (R-AODV). Also, M-O-AODV was able to perform link recovery within 3700 ms in the case of node failures, compared with other forwarding-based protocols that require 4800 ms to 6000 ms. Consequently, M-O-AODV-based BLE mesh networks are more efficient for wireless sensor-enabled IoT environments.

Many well-known wireless networks are currently being used to develop educational robots. Bluetooth Low Energy (BLE) is one of the well-suited for educational robotic systems because of its simplicity, low power consumption, low cost, and robustness. To operate several robots simultaneously in a limited space like a classroom, a mesh network topology is necessary to communicate amongst robots. However, the BLE mesh network has a managed flooding protocol, which is inefficient for educational robotic systems since it is appropriate for small networks. Thus, a task synchronization is required to ensures the accuracy and stability of the system. This paper proposes task synchronization method in BLE mesh network to operate educational robots simultaneously and quickly as possible, but not in real-time without a central control system. The results demonstrate that the proposed method operate the task simultaneously and faster than a typical broadcasting in BLE.

Wireless Mesh Networks (WMN) are becoming inevitable in this world of high technology as it provides low cost access to broadband services. Moreover, the technologists are doing research to make WMN more reliable and secure. Subsequently, among wireless ad-hoc networking technologies, Bluetooth Low Energy (BLE) is gaining high degree of importance among researchers due to its easy availability in the gadgets and low power consumption. BLE started its journey from version 4.0 and announced the latest version 5 with mesh support capability. BLE being a low power and mesh supported technology is nowadays among the hot research topics for the researchers. Many of the researchers are working on BLE mesh technology to make it more efficient and smart. Apart from other variables of efficiency, like all communication networks, mesh network security is also of a great concern. In view of the aforesaid, this paper provides a comprehensive review on several works associated to the security in WMN and BLE mesh networks and the research related to the BLE security protocols. Moreover, after the detailed research on related works, this paper has discussed the pros and cons of the present developed mesh security mechanisms. Also, at the end after extracting the curx from the present research on WMN and BLE mesh security, this research study has devised some solutions as how to mitigate the BLE mesh network security lapses.

Bluetooth low energy (BLE) is a promising candidate technology for use in the Internet of Things (IoT) because of its ultra-low-power communication. Although BLE devices are designed to run on a small battery for a few years, several attempts have been made to extend BLE lifetime through various techniques. In particular, emerging approaches such as artificial intelligence (AI) can be utilized to further improve the BLE energy efficiency. For this purpose, this article proposes a Q-learning-based scheduling algorithm for BLE. The proposed scheduling algorithm dynamically adjusts the key parameters that govern the operation of the BLE transmission scheme. These key parameters, namely, the length of connection interval and the number of packets to transmit during the interval, have a profound effect on energy efficiency and the quality of service (QoS) specified in terms of maximum latency. According to the framework of reinforcement learning, our Q-learning-based scheduling algorithm is appropriately constructed to simultaneously provide a longer network lifetime and satisfy the QoS requirement. The numerical results show that the proposed Q-learning-based approach significantly increases the network lifetime compared to alternative methods while meeting QoS requirements.

Due to extremely low power consumption, backscatter is promising to become general-purpose communication for Internet of Things (IoT) networks. The state-of-the-art BLE backscatter system RBLE can work fully with commodity Bluetooth Low Energy (BLE) devices, however, the communication reliability of RBLE is still limited by its modulation scheme based on Binary Frequency Shift Keying (BFSK). To address this issue, we refer to the modulation of active BLE radios to improve the modulation scheme of the backscatter tag. We present PBLE, a practical BLE backscatter communication system that modulates using phase shift. We conduct experiments to verify the feasibility and efficacy. Evaluation results demonstrate the feasibility and performance gains over RBLE in terms of bit error rate (BER). With PBLE, it is possible for us to reliably read the sensor data of tags using daily BLE devices.

In this demo we fabricate 4 development boards using the APlix CSR1010 modules and then establish a Bluetooth Low Energy (BLE) mesh network, which is suitable for power-limited and low-complexity IoT applications with low-priority and infrequent data traffic. In addition to the basic operations such as sensing and actuating devices, this demo also shows a BLE star-mesh integration topology to extend the connectivity range to cover 4 laboratories.

Recently, backscatter technology has attracted much interest in wireless communication due to its novel low-cost and battery-free design. Since Bluetooth Low Energy (BLE) was born to be low energy consumption, great efforts have been made in BLE-based backscatter systems, like FreeRider, RBLE. In this paper, we present BonusBlue, a BLE backscatter system that enables high-goodput communication with commercial BLE devices. BonusBlue tag generates BLE packets by modulating data on excitation signals and set up a data connection with BLE receiver using a state machine, thus achieving a high-goodput communication link. We present this state machine design and build a prototype of our tag using an FPGA, and evaluate its performance with BLE devices. Our evaluation shows that the backscatter tag can build a robust data connection link with commodity BLE device in the guidance of our state machine and transmit tag data on this link. Experimental results show that our backscatter system can achieve a goodput of up to 16.9 kbps.

Nowadays, the Internet of Things (IoT) is spreading rapidly towards creating smart environments.Home automation, intra-vehicular interaction, and wireless sensor networks (WSN) are among the most popular applications discussed in IoT literature.One of the most available and popular wireless technologies for short-range operations is Bluetooth.In late 2010, the Bluetooth Special Interest Group (SIG) launched the Bluetooth 4.0 Specification, which brings Bluetooth Low Energy (BLE) as part of the specification.BLE characterises as being a very low power wireless technology, capable of working on a coin-cell or even by energy scavenging.Nevertheless, the nature of Bluetooth (and BLE) has always been a connection-oriented communication in a Master/Slave configuration.Several studies exist showing how to create mesh networks for Classic Bluetooth, called Scatternets, by utilizing some nodes as slaves to relay data between Masters.However, BLE didn't support role changing until the 4.1 Specification released in 2013.The capability of a wireless technology to create a Mobile Ad-Hoc Network (MANET) is vital for supporting the plethora of sensors, peripherals, and devices that could coexist in any IoT environment.This work focuses on proposing a new autoconfiguring dynamic address allocation scheme for a BLE Ad-Hoc network, and a network map discovery and maintenance mechanism that doesn't require role changing, thus being possible to implement it in 4.0 compliant devices as well as 4.1 or later to develop a MANET.Any ad-hoc routing protocol can utilise the proposed method to discover, keep track, and maintain the mesh network node topology in each of their nodes.

The rapid and increasing application of wireless technology, especially Bluetooth Low Energy (BLE), provides many benefits to our daily lives. With BLE, the small packets of data can be exchanged over a wireless channel, whereas the data security is a concern. For example, the BLE standards define that if one BLE device with input-output capabilities tries to establish a connection while the other BLE device does not support input-output, an unauthenticated channel will be established. That is, in the worst case, the connection is established where no security is applied. To mitigate this issue, we propose a security protocol, named BALSAPro, at the application layer that complements the existing protocols such as Security Manager Protocol (SMP), which can help establish a secure channel with authentication and non-repudiation, when pairing has not been used. In the evaluation, we implement and evaluate our protocol performance compared with similar work at the application layer. The results demonstrate that our protocol can enhance the security level with less time consumption.

Digitalization of the shipyard environment is a challenging problem, and also it is necessary for competing the international ship manufacturers. Thus, this study introduced a real-time accurate positioning system that is an indispensable part of a digital manufacturing system. The system implementation and measurements took place in Sedef Shipyard, the largest shipbuilding facility in Turkey. Since the shipyard includes indoor and outdoor environments, Bluetooth Low Energy (BLE) systems provide the best solution for locating the staff. The most challenging problem is to determine the positions in the metallic surroundings. The constructed system solves this problem by placing gateways and sensors at essential locations and using a mesh network. With the designed user interface, the position of the staff can be monitored accurately in real time, and reports can be generated.

This paper investigates the possibility to develop a Bluetooth Low Energy (BLE) device as part of Internet of Things chain. For this purpose, both the hardware and the software aspects are considered. Thus, the BLE software stack from Texas Instruments and the CC2541 platform were chosen. Considering the CC2541 Keyfob device which contains an accelerometer, new facilities are firstly introduced by modifying the existing embedded software. Then, a new hardware component is connected, and the necessary software components are included in order to use this new element. The two main applications that are employed to monitor the activity of the BLE devices are analyzed and a new one based on MATLAB is introduced to improve the facilities of the existing applications. Thus, using the ideas presented in this paper, new BLE devices can be developed.

Bluetooth Low Energy (BLE) is a popular low power wireless technology, used for short-range communication. In BLE networks, discovery process enables fast and energy-efficient communication, since all communications must involve it at the first step. For this reason, some studies have proposed novel discovery schemes to improve the performance of device discovery process. Nevertheless, literature report that provides a consolidated view are limited and insufficient. In this paper, we survey different device discovery schemes in BLE networks and discuss their advantages and limitations. The enhanced schemes are categorized into two approaches: parameter adjustment and collision avoidance approach. The first approach improves the performance by adjusting the discovery parameters according to a network situation. In the second approach, the BLE devices try to avoid the interference to reduce collisions in crowded networks.

Future telecommunications aim to be ubiquitous and efficient, as widely deployed connectivity will allow for a variety of edge/fog based services. Challenges are numerous, e.g., spectrum overuse, energy efficiency, latency and bandwidth, battery life and computing power of edge devices. Addressing these challenges is key to compose the backbone for the future Internet-of-Things (IoT). Among IoT applications are Indoor Positioning System and indoor Real-Time-Location-Systems systems, which are needed where GPS is unviable. The Bluetooth Low Energy (BLE) 5.1 specification introduced Direction Finding to the protocol, allowing for BLE devices with antenna arrays to derive the Angle-of-Arrival (AoA) of transmissions. Well known algorithms for AoA calculation are computationally demanding, so recent works have addressed this, since the low-cost of BLE devices may provide efficient solutions for indoor localization. In this paper, we present a system topology and algorithms for self-localization where a receiver with an antenna array utilizes the AoAs from fixed battery powered beacons to self-localize, without a centralized system or wall-power infrastructure. We conduct two main experiments using a BLE receiver of our own design. Firstly, we validate the expected behaviour in an anechoic chamber, computing the AoA with an RMSE of <inline-formula> <tex-math notation="LaTeX">$\mathrm {10.7~ ^{circ}}$ </tex-math></inline-formula>. Secondly, we conduct a test in an outdoor area of 12 by 12 meters using four beacons, and present pre-processing steps prior to computing the AoAs, followed by position estimations achieving a mean absolute error of <inline-formula> <tex-math notation="LaTeX">$\mathrm {3.6~ \text {m}}$ </tex-math></inline-formula> for 21 map positions, with a minimum as low as <inline-formula> <tex-math notation="LaTeX">$\mathrm {1.1~ \text {m}}$ </tex-math></inline-formula>.

Beacons turn the physical world into a new digital channel. They bring digital content and engagement closer to the point of purchase. Beacon technology transmits small packets of data using Bluetooth Low Energy. When a customer’s phone “hears” the beacon it knows how close it is and we can then send a message, a notice, a piece of media or other information. Beacons are low-power transmitters equipped with Bluetooth Low Energy or BLE. Bluetooth Low Energy help mobile devices to detect Proximity and determine micro-location. Advantages of Bluetooth low energy devices are it works up to 100 meters, doesn’t drain the phone battery.In this paper problems with beacon are described and path navigation using Bluetooth Low Keywords: Beacon , Internet of Things – Beacons The New Revolution, Bluetooth Low Energy, Path Navigation, Background Monitoring, Ranging Beacons, Proximity, Tracking

Bluetooth Low Energy (BLE) is a widely adopted wireless communication technology in the Internet of Things (IoT). BLE offers secure communication through a set of pairing strategies. However, these pairing strategies are obsolete in the context of IoT. The security of BLE based devices relies on physical security, but a BLE enabled IoT device may be deployed in a public environment without physical security. Attackers who can physically access a BLE-based device will be able to pair with it and may control it thereafter. Therefore, manufacturers may implement extra authentication mechanisms at the application layer to address this issue. In this paper, we design and implement a BLE Security Scan (BLESS) framework to identify those BLE apps that do not implement encryption or authentication at the application layer. Taint analysis is used to track if BLE apps use nonces and cryptographic keys, which are critical to cryptographic protocols. We scan 1073 BLE apps and find that 93% of them are not secure. To mitigate this problem, we propose and implement an application-level defense with a low-cost $0.55 crypto co-processor using public key cryptography.