Gratuitous Neighbor Discovery: Creating Neighbor Cache Entries on First-Hop Routers

Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

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Block Design-Based Asynchronous Neighbor Discovery Protocol for Wireless Sensor Networks

Journal of Sensors ◽

10.1155/2015/951652 ◽

2015 ◽

Vol 2015 ◽

pp. 1-12 ◽

Cited By ~ 5

Author(s):

Sangil Choi ◽

Wooksik Lee ◽

Teukseob Song ◽

Jong-Hoon Youn

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Simulation Study ◽

Mathematical Proof ◽

Block Design ◽

Wireless Sensor ◽

Neighbor Discovery ◽

Block Designs ◽

Worst Case ◽

Neighbor Discovery Protocol

Neighbor discovery is a significant research topic in wireless sensor networks. After wireless sensor devices are deployed in specific areas, they attempt to determine neighbors within their communication range. This paper proposes a new Block design-based Asynchronous Neighbor Discovery protocol for sensor networks calledBAND. We borrow the concept of combinatorial block designs for neighbor discovery. First, we summarize a practical challenge and difficulty of using the original block designs. To address this challenge, we create a new block generation technique for neighbor discovery schedules and provide a mathematical proof of the proposed concept. A key aspect of the proposed protocol is that it combines two block designs in order to construct a new block for neighbor discovery. We analyze the worst-case neighbor discovery latency numerically between our protocol and some well-known protocols in the literature. Our protocol reveals that the worst-case latency is much lower than others. Finally, we evaluate the performance ofBANDand existing representative protocols through the simulation study. The results of our simulation study show that the average and maximum latency ofBANDis about 40% lower than that of existing protocols. Furthermore,BANDspends approximately 30% less energy than others during the neighbor discovery process.

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