Computing the Probability of Specific Random Sector Graphs with Applications in Wireless Networks with Directional Antennas

Wu, Chun Yi; Yu, Chang Wu

doi:10.1109/iih-msp.2014.175

Cited by 3 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Random sector directed graphs and random geometric graphs are identical in case of φ = 2π [13], [14], [48], [49].…”

Section: Definition 1 (Uowsns As Random Sector Directed Graphs)mentioning

confidence: 99%

“…Random sector directed graphs and random geometric graphs are identical in case of φ = 2π [13], [14], [48], [49]. 1 We assumed that floating relay nodes are fastened to the seabed in order to prevent their loss by drifting in case of strong deep currents.…”

Section: Network Modelmentioning

confidence: 99%

“…On the contrary, such a model is not suitable for UOWSNs because a node can only reach to the nodes within a certain beam scanning angle around their transmission trajectory, that is, optical wireless nodes are connected via unidirectional links. Directed communication networks are generally modeled by random scaled sector graphs [13] where a unidirectional communication link from node n i to n j (i.e., n i → n j ) is established if and only if n j is positioned within the beam scanning angle of n i . Notice that a directed reverse path is possible (i.e., n j → n i ) if n i is in the beam-width of n j or through other multi-hop path.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Performance Analysis of Connectivity and Localization in Multi-Hop Underwater Optical Wireless Sensor Networks

Saeed

Çelik

Alouini

et al. 2019

IEEE Trans. on Mobile Comput.

View full text Add to dashboard Cite

Underwater optical wireless links have limited range and intermittent connectivity due to the hostile aquatic channel impairments and misalignment between the optical transceivers. Therefore, multi-hop communication can expand the communication range, enhance network connectivity, and provide a more precise network localization scheme. In this regard, this paper investigates the connectivity of underwater optical wireless sensor networks (UOWSNs) and its impacts on the network localization performance. Firstly, we model UOWSNs as randomly scaled sector graphs where the connection between sensors is established by point-to-point directed links. Thereafter, the probability of network connectivity is analytically derived as a function of network density, communication range, and optical transmitters' divergence angle. Secondly, the network localization problem is formulated as an unconstrained optimization problem and solved using the conjugate gradient technique. Numerical results show that different network parameters such as the number of nodes, divergence angle, and transmission range significantly influence the probability of a connected network. Furthermore, the performance of the proposed localization technique is compared to well-known network localization schemes and the results show that the localization accuracy of the proposed technique outperforms the literature in terms of network connectivity, ranging error, and number of anchors.

show abstract

“…Random sector directed graphs and random geometric graphs are identical in case of φ = 2π [13], [14], [48], [49].…”

Section: Definition 1 (Uowsns As Random Sector Directed Graphs)mentioning

confidence: 99%

Section: Network Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance Analysis of Connectivity and Localization in Multi-Hop Underwater Optical Wireless Sensor Networks

Saeed

Çelik

Alouini

et al. 2019

IEEE Trans. on Mobile Comput.

View full text Add to dashboard Cite

show abstract

“…On the contrary, such a model is not suitable for UOWNs because a node can only reach to the nodes within a certain beam scanning angle around their transmission trajectory, that is, optical wireless nodes are connected via unidirectional links. Directed communication networks are generally modeled by random scaled sector graphs [254] where a unidirectional communication link from node n i to n j (i.e., n i → n j ) is established if and only if n j is positioned within the beam scanning angle of n i . Notice that a directed reverse path is possible (i.e., n j → n i ) if n i is in the beam-width of n j or through other multi-hop path as illustrated in Fig.…”

Section: A Connectivity Analysis Of Uownsmentioning

confidence: 99%

“…Notice that E i,j = 1 only if n i → n j holds. Random sector directed graphs and random geometric graphs are identical in case of φ = 2π [248], [249], [254], [275]. Notice that two nodes i and j are connected when the distance between them is less than R in random geometric graphs, however, the connectivity of random directed sector graphs also depends on the beam scanning angle and its orientation.…”

Section: A Connectivity Analysis Of Uownsmentioning

confidence: 99%

Underwater optical wireless communications, networking, and localization: A survey

et al. 2019

View full text Add to dashboard Cite

Underwater wireless communications can be carried out through acoustic, radio frequency (RF), and optical waves. Compared to its bandwidth limited acoustic and RF counterparts, underwater optical wireless communications (UOWCs) can support higher data rates at low latency levels. However, severe aquatic channel conditions (e.g., absorption, scattering, turbulence, etc.) pose great challenges for UOWCs and significantly reduce the attainable communication ranges, which necessitates efficient networking and localization solutions. Therefore, we provide a comprehensive survey on the challenges, advances, and prospects of underwater optical wireless networks (UOWNs) from a layer by layer perspective which includes: 1) Potential network architectures; 2) Physical layer issues including propagation characteristics, channel modeling, and modulation techniques 3) Data link layer problems covering link configurations, link budgets, performance metrics, and multiple access schemes; 4) Network layer topics containing relaying techniques and potential routing algorithms; 5) Transport layer subjects such as connectivity, reliability, flow and congestion control; 6) Application layer goals and state-of-the-art UOWN applications, and 7) Localization and its impacts on UOWN layers. Finally, we outline the open research challenges and point out the future directions for underwater optical wireless communications, networking, and localization research.

show abstract

Connectivity Analysis of Underwater Optical Wireless Sensor Networks: A Graph Theoretic Approach

Saeed

Çelik

Al-Naffouri

et al. 2018

2018 IEEE International Conference on Communications Workshops (ICC Workshops)

View full text Add to dashboard Cite

Computing the Probability of Specific Random Sector Graphs with Applications in Wireless Networks with Directional Antennas

Cited by 3 publications

References 17 publications

Performance Analysis of Connectivity and Localization in Multi-Hop Underwater Optical Wireless Sensor Networks

Performance Analysis of Connectivity and Localization in Multi-Hop Underwater Optical Wireless Sensor Networks

Underwater optical wireless communications, networking, and localization: A survey

Connectivity Analysis of Underwater Optical Wireless Sensor Networks: A Graph Theoretic Approach

Contact Info

Product

Resources

About