Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

Radi, Marjan; Dezfouli, Behnam; Bakar, Kamalrulnizam Abu; Razak, Shukor Abd

doi:10.1155/2014/789642

Cited by 8 publications

(3 citation statements)

References 41 publications

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“…Code based approach [1], survey of neighbor discovery protocols [2], [11], [12], [14], [20], [30], [32], block design based protocols [3], energy efficient neighbor discovery [4], asynchronous neighbor discovery in duty cycled networks [5] and neighbor discovery in cognitive radio networks [6] are found in the literature. Other approaches found include a generic flexible protocol [10], smart phone neighbor discovery [13], secure neighbor discovery [15], adaptive neighbor discovery [16], quorum based approach [17], fast neighbor discovery [18], neighbor discovery and link quality estimation [19], low power neighbor discovery [21], broadcast foreigner discovery [22], x-raying neighbor discovery [23], neighbor discovery in 3D scenarios [24], neighbor discovery for security [25], multi-packet reception based neighbor discovery [26], multi-channel neighbor discovery [27] and heterogeneous neighbor discovery [28]. Neighbor discovery for opportunistic networking [31], group-based neighbor discovery [34] and continuous neighbor discovery in asynchronous sensor networks [35] are other approaches found in the literature.…”

Section: Other Neighbor Discovery Approachesmentioning

confidence: 99%

Present State-of-the-Art of Continuous Neighbor Discovery in Asynchronous Wireless Sensor Networks

Mekala¹,

Chatrapati²

2018

EAI Endorsed Transactions on Energy Web

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In this paper, we reviewed the literature on various techniques found in WSN for neighbor discovery. Neighbor discovery is a fundamental phenomenon in the network in the deployment phase. However, due to the dynamic nature of WSN, and there are possibilities of adding new nodes and removing nodes from the network, continuous neighbour discovery is needed. It does mean that neighbour discovery is not a one-time task. With neighbour discovery, there are many advantages to WSN. The efficiency of the network is improved besides saving the energy of nodes and increasing the lifetime of nodes. The review of the literature made in this paper provides useful insights on the present state of the art of continuous neighbour discovery in WSN. It also provides research gaps found in the literature.

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Section: Other Neighbor Discovery Approachesmentioning

confidence: 99%

Present State-of-the-Art of Continuous Neighbor Discovery in Asynchronous Wireless Sensor Networks

Mekala¹,

Chatrapati²

2018

EAI Endorsed Transactions on Energy Web

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“…From this perspective, the number of exchanged beacon messages for collecting residual energy information would still be manageable in our approach. Interested readers are referred to a study presented in [32] on the number of beacon messages required for neighborhood discovery based on different neighborhood size of a network.…”

Section: Memory Requirement Scalability and Neighbor Information Rementioning

confidence: 99%

Prolonging the lifetime of wireless sensor networks using secondary sink nodes

Murugan¹,

Pathan

2015

Telecommun Syst

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This work proposes an approach for improving energy-efficiency and thus increasing network lifetime in wireless sensor network (WSN) using a logical energy tree (LET). In our scheme, LET is constructed using the remaining available energy in each node. Two routing algorithms are framed based on LET: one with centralized sink node called LETCSN and the other with centralized sink node and secondary sink nodes called LETSSN. sensor nodes are deployed in some fixed patterns. A mathematical model is devised to understand the effect of node deployment pattern on improving network lifetime. Both proposed routing algorithms are evaluated with seven different deployment patterns, simulated in ns-2 and are compared with the existing classic algorithms based on the number of data packets, throughput, network lifetime, and data packet's average network lifetime product. Our evaluation and simulation results show that LETSSN maximizes the network lifetime for all node-deployment patterns taken into consideration.

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“…After network initialization, every node should identify at least one path towards the network data gathering point (i.e., sink node) [34]. Therefore, LINKORD aims to construct the minimum cost network data gathering tree which is rooted at the sink node and provides efficient data gathering during network operation through two different phases.…”

Section: Link Ordering-based Data Gathering Protocolmentioning

confidence: 99%

LINKORD: link ordering-based data gathering protocol for wireless sensor networks

et al. 2014

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With respect to the multi-hop communication pattern of wireless sensor networks, all the nodes should establish multi-hop paths towards a common data gathering point to provide a data gathering service for the underlying applications. Although data gathering protocols provide a simple service, these protocols suffer from poor performance in practice due to the power constraints of low-power sensor nodes and unreliability of wireless links. Existing data gathering protocols rely on the ETX metric to find high-throughput paths through assuming there is an infinite number of transmission attempts at the link layer for delivering a single packet over every link. However, in practice the link layer provides a bounded number of transmissions per packet over individual links. Therefore, employing existing data gathering protocols in these situations may result in the construction of the paths that require more than maximum number of provided link layer transmissions for delivering a single packet over each link. In this regard, we propose a path cost function which considers the limitation on the number of provided link layer transmissions and relative position of the links along the paths according to their data transmission probability. Furthermore, we introduce a data gathering protocol which uses the proposed path cost function to construct high-throughput paths. Moreover, this protocol employs a newly designed congestion control mechanism during the data transmission process to provide energy-efficient and high-throughput data delivery. The simulation results 123 206 M. Radi et al. show that, the proposed protocol improves data delivery ratio by 70 % and network goodput by 80 %, while it reduces the consumed energy for data delivery by 50 % compared to the default data gathering protocol of TinyOS.

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Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

Cited by 8 publications

References 41 publications

Present State-of-the-Art of Continuous Neighbor Discovery in Asynchronous Wireless Sensor Networks

Present State-of-the-Art of Continuous Neighbor Discovery in Asynchronous Wireless Sensor Networks

Prolonging the lifetime of wireless sensor networks using secondary sink nodes

LINKORD: link ordering-based data gathering protocol for wireless sensor networks

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