Neighbor discovery in traditional wireless networks and cognitive radio networks: Basics, taxonomy, challenges and future research directions

Khan, Athar Ali; Rehmani, Mubashir Husain; Saleem, Yasir

doi:10.1016/j.jnca.2015.03.003

Cited by 30 publications

(12 citation statements)

References 81 publications

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“…Combining four routing mechanisms in mobile ad hoc networks. In addition, some researchers have introduced neighbor discovery into multi-directional antenna environment [26,27], multi-user environment [28], and cognitive network environment [29].…”

Section: Related Workmentioning

confidence: 99%

Technology of Neighbor Discovery for Networks

Jiang

2020

Mobile Information Service for Networks

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Neighbor discovery is one of the basic technologies of mobile information service for networks. It is the key to discover the surrounding nodes at the data link layer and organize the network effectively. Firstly, this chapter introduces the basic concept and the development of neighbor discovery in detail. According to popular social application scenarios, efficient neighbor discovery algorithms (Erupt and Centron) are introduced. In these algorithms, the Erupt algorithm divides the nodes into two categories according to their roles: the sponsor node and the participant node. Using a recession strategy, the sponsor consumes more energy in exchange for higher discovery efficiency. By creating a core group, the Centron algorithm solves the problem that communications between nodes will be affected by frequent collisions in the crowded region, which reduces the efficiency of discovery. The above algorithms are proved to be efficient in terms of energy, efficiency, and delay. Besides, these algorithms can provide inspirations for how to design better neighbor discovery algorithms in the future.

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Section: Related Workmentioning

confidence: 99%

Technology of Neighbor Discovery for Networks

Jiang

2020

Mobile Information Service for Networks

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“…In traditional single-channel or multi-channel wireless networks, neighbor discovery is a problem that has been extensively studied under a variety of different models (w.r.t., e.g., synchrony and availability of collision detection). Interested readers can, e.g., refer to the survey paper from Khan et al [9], and from Chen et al [2], for more details. On the contrary, for cognitive radio networks, limited focus has been put on this problem.…”

Section: Related Workmentioning

confidence: 99%

“…On the contrary, for cognitive radio networks, limited focus has been put on this problem. (See related parts in [9] for a survey.) We are only able to identify one work from Zeng et al [25] 2 that explicitly targets this issue and provides theoretical results.…”

Section: Related Workmentioning

confidence: 99%

Communication Primitives in Cognitive Radio Networks

Gilbert

Kühn

Zheng

2017

Proceedings of the ACM Symposium on Principles of Distributed Computing

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Cognitive radio networks are a new type of multi-channel wireless network in which different nodes can have access to different sets of channels. By providing multiple channels, they improve the efficiency and reliability of wireless communication. However, the heterogeneous nature of cognitive radio networks also brings new challenges to the design and analysis of distributed algorithms.In this paper, we focus on two fundamental problems in cognitive radio networks: neighbor discovery, and global broadcast. We consider a network containing n nodes, each of which has access to c channels. We assume the network has diameter D, and each pair of neighbors have at least k ≥ 1, and at most k max ≤ c, shared channels. We also assume each node has at most ∆ neighbors. For the neighbor discovery problem, we design a randomized algorithm CSEEK which has time complexityÕ((c 2 /k) + (k max /k) · ∆). CSEEK is flexible and robust, which allows us to use it as a generic "filter" to find "well-connected" neighbors with an even shorter running time. We then move on to the global broadcast problem, and propose CGCAST, a randomized algorithm which takesCGCAST uses CSEEK to achieve communication among neighbors, and uses edge coloring to establish an efficient schedule for fast message dissemination.Towards the end of the paper, we give lower bounds for solving the two problems. These lower bounds demonstrate that in many situations, CSEEK and CGCAST are near optimal.

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“…Therefore, it seems very realistic to assume that those nodes which are in the direct radio communication range (one hop nodes) of each other already share a secret symmetric key. This can easily be accomplished during the secure neighbor discovery phase (Khan et al, 2015;Poturalski et al, 2013;Taheri et al, 2016). After the initial deployment phase, various available routes are established between communicating nodes and routing tables as usual are kept on being updated according to the underlying routing protocol.…”

Section: The Attack Modelmentioning

confidence: 99%

An Identity based Routing Path Verification Scheme for Wireless Sensor Networks

Khan

2017

IJSNET

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While the ability to express routing policies in Wireless Sensor Networks (WSNs) has been well-studied, unfortunately, the ability to enforce these policies has not been. The core challenge is that if we assume an adversarial, decentralized, and high-speed environment, then how can the receiving node be sure that the path being announced by the incoming packet is the actual path followed by it? In this paper we describe the networking primitive, called Routing Path Verification (RPV), which serves as a tool to enforce routing policies and presents a solution to the defined core challenge. We assess the security of the proposed RPV construction in a formal way. More significantly we augment a suitable key exchange protocol with our proposed RPV construction, to achieve an overall RPV scheme. We also evaluate the computational, communication and storage overhead of our proposed scheme and the experimental results show that the approach is quite scalable.

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Neighbor discovery in traditional wireless networks and cognitive radio networks: Basics, taxonomy, challenges and future research directions

Cited by 30 publications

References 81 publications

Technology of Neighbor Discovery for Networks

Technology of Neighbor Discovery for Networks

Communication Primitives in Cognitive Radio Networks

An Identity based Routing Path Verification Scheme for Wireless Sensor Networks

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