A Talk-Listen-Ack Beaconing Strategy for Neighbor Discovery Protocols in Wireless Sensor Networks

Neighbor discovery is a fundamental function for sensor networking. Sensor nodes discover each other by sending and receiving beacons. Although many time-slotted neighbor discovery protocols (NDPs) have been proposed, the theoretical discovery latency is measured by the number of time slots rather than the unit of time. Generally, the actual discovery latency of a NDP is proportional to its theoretical discovery latency and slot length, and inversely proportional to the discovery probability. Therefore, it is desired to increase discovery probability while reducing slot length. This task, however, is challenging because the slot length and the discovery probability are two conflicting factors, and they mainly depend on the beaconing strategy used. In this paper, we propose a new beaconing strategy, called talk-listen-ack beaconing (TLA). We analyze the discovery probability of TLA by using a fine-grained slot model. Further, we also analyze the discovery probability of TLA that uses random backoff mechanism to avoid persistent collisions. Simulation and experimental results show that, compared with the 2-Beacon approach that has been widely used in time-slotted NDPs, TLA can achieve a high discovery probability even in a short time slot. TLA is a generic beaconing strategy that can be applied to different slotted NDPs to reduce their discovery latency.

How reliable is smartphone-based electronic contact tracing for COVID-19?

A look through the lens of neighbor discovery protocols reveals significant potential to improve electronic contact-tracing accuracy.

An adaptive multi-hop routing with IoT abstraction for minimizing delay-node capacity trade-offs in mobile ad-hoc network

<span>Delay and node capacity are incompatible mobile ad hoc constraints because of the network's versatility and self-disciplined design. </span><span>It is a challenging problem to maximize the trade-off between the above mobility correlation factors. </span><span>This manuscript proposes an adaptive multi-hop routing (A.M.R.) for mobile ad-hoc network (MANET) to minimize the trade-off by integrating the internet of things (IoT). IoT nodes' smart computing and offloading abilities are extended to ad-hoc nodes to improve routing and transmission. Dor MANET nodes in route exploration, neighbor selection, and data transmission, the beneficial features of IoT include enhanced decision making. The traditional routing protocols use IoT at the time of the neighbor discovery process in updating the routing table and localization. </span><span>The harmonizing technologies with their extended support improve the performance of MANETs has been estimated. The proposed method achieves better throughput (14.16 Mbps), delay (0.118), packet drop (126), and overhead (36 packets) when compared to existing methods.</span>

Improving Sensor Network Performance with Directional Antennas: A Cross-layer Optimization

The use of directional antennas for wireless communications brings several benefits, such as increased communication range and reduced interference. One example of directional antennas are electronically switched directional (ESD) antennas that can easily be integrated into Wireless Sensor Networks (WSNs) due to their small size and low cost. However, current literature questions the benefits of using ESD antennas in WSNs due to the increased likelihood of hidden terminals and increased power consumption. This is mainly because earlier studies have used directionality for transmissions but not for reception. In this article, we introduce novel cross-layer optimizations to fully utilize the benefits of using directional antennas. We modify the Medium Access Control (MAC) , routing, and neighbor discovery mechanisms to support directional communication. We focus on convergecast investigating a large number of different network topologies. Our experimental results, both in simulation and with real nodes, show when the traffic is dense, networks with directional antennas can significantly outperform networks with omnidirectional ones in terms of packet delivery rate, energy consumption, and energy per received packet.

Reconfigurable Intelligent Surface-Assisted Bluetooth Low Energy Link in Metal Enclosure

Reconfigurable intelligent surface (RIS) technology is at the forefront for its transformative role in future wireless communication systems such as wireless local area networks (WLAN), sixth-generation (6G) communication, and internet-of-things (IoT). This paper presents RIS-assisted Bluetooth low energy (BLE) communication links in neighbor discovery mode. We optimized the packet error rate (PER) performance of the BLE communication link in a highly reflecting metal enclosure environment. We used one RIS for the PER optimization of four BLE physical (PHY) modes. Then, we used two RISs simultaneously in a distributed and centralized manner to further optimize the PER of all BLE PHY modes. We found PER optimization using two RISs is better than the PER optimization using one RIS. Additionally, PER optimization using a centralized arrangement of RISs outperformed PER optimization using distributed arrangement. We found the coded BLE modes i.e., LE500K and LE125K show lower PER than the uncoded counterpart i.e., LE1M and LE2M. This is because uncoded BLE PHY modes have higher data rates than the coded BLE PHY modes. Because of additional channel power gains introduced by RIS-based passive beamforming, the PER of coded and uncoded BLE PHY modes is further reduced.

A Framework for Analyzing Neighbor Discovery Protocols under Non-Ideal Conditions

Neighbor Discovery (ND) protocols are crucial to achieving the paradigm of interconnecting thousands of small nodes (sensors or things) to the Internet, also known as the IoT. These protocols usually assume that nodes operate with few energy resources. Therefore, they cannot be fully active all the time. The vast majority of these protocols focus on increasing the probability that two nodes become active simultaneously, thus enabling mutual discovery. In addition, these protocols assume that successful discovery is guaranteed once two nodes are simultaneously active, with very few exceptions. However, many problems can disrupt the discovery, such as channel errors, collisions, synchronization mismatches, energy availability, and so forth. Most ND protocols did not consider these factors, making them vulnerable to severe performance degradation when transmission errors occur. This paper proposes a new framework to evaluate the performance of deterministic neighbor discovery protocols when transmission errors are present. The proposed framework facilitates obtaining an analytical CDF of the discovery time of such protocols with transmissions errors without having to implement the protocol in a simulator, since is time-consuming and prone to implementation errors. We applied the framework to analyze the effect of transmission errors on the discovery time in four of the most representative ND protocols in the literature. Finally, we validate the framework accuracy for the selected protocols using extensive simulations. The results show that the CDF of discovery times provided by the framework closely matches the performance results obtained through simulating these protocols. In general, neighbor discovery protocols are deeply affected as a result of transmission errors.