Collaborative neighbor discovery in directional wireless sensor networks: algorithm and analysis

Abstract

In directional wireless sensor networks (DSNs), sensor nodes with directional antennas provide extended network lifetime and better coverage performance. However, one of the key challenges of directional nodes is to discover their neighbors due to difficulty in achieving synchronization among their directed transmissions and receptions. Existing solutions suffer from high discovery latency and poor percentage of neighbor discovery either due to lack of proper coordination or centralized management of the discovery operation. In this work, we develop a collaborative neighbor discovery (COND) mechanism for DSNs. Each COND node polls to directly discover its neighbors in a distributed way and collaborates with the already discovered nodes so as to allow indirect discovery. It helps to increase the neighbor discovery performance significantly. A Markov chain-based analytical model is developed to quantify theoretical performances of the proposed COND system. The performance of the COND system is evaluated in Network Simulator Version 3, and simulation results reveal that it greatly reduces the discovery latency and increases neighbor discovery ratio compared to state-of-the-art approaches.

Multiple token‐based neighbor discovery for directional sensor networks

“…The performance of the proposed MuND protocol is evaluated using the Cooja simulator with directional antenna support . For performance analysis, the proposed MuND protocol is compared with existing protocols like direct and indirect COND and SAND in terms of metrics like neighbor discovery latency, neighbor discovery ratio, control packet overhead and energy consumption. The simulation results are obtained by averaging results over multiple simulations.…”

“…As a result, the reception of HELLO or REPLY packets is not guaranteed. Beam synchronization is achieved in the collaborative neighbor discovery (COND) protocol . Direct and indirect COND protocols propose a distributed and collaborative method of neighbor discovery which is meant to drastically reduce neighbor discovery latency.…”

Beamforming Optimization in Internet of Things Applications Using Robust Swarm Algorithm in Conjunction with Connectable and Collaborative Sensors

“…It should be noted that when using the directional antenna model within WSN, it becomes difficult for each sensor to share the global information with other neighbors. Therefore, in [20] the authors developed a fully distributed directional antenna array discovery mechanism to find collaborative sensors. A discrete-time Markov chain is used for analyzing the performance of the antenna array to direct and indirect neighbor discovery as well as selection of feedback policies jointly which helps to decrease collisions and reduce the latency in the network.…”

“…Thus, the minimum number of these samples can be determined when the mainlobe and sidelobes reach their stable values. To avoid occurrence of grating lobes, the interspace among sensors should satisfy r o ≤ λ 2 ≤ ρπd max [20]. The selection process can be summarized as follows:…”

“…Step 3 Sensors are selected to form an antenna array that adjusts its own radiation pattern to radiate the beampattern in certain direction and reject the signals from other directions. This is controlled by the weighted signal of the collaborative sensors which are computed and the signal is transmitted to the cluster head based on robust particle swarm as discussed in Section 6.2 to satisfy the objective function defined in Equation (20). The memetic objective function shows that these weights could be adapted to change based on the signal environment in terms of fluctuations/shadowing in the channel.…”