Cognitive Location based Mobile Adhoc Networks Implementation with an Android Operating Systems

α
Rajaram
Rajaram
σ
Dr. V. Sumathy
Dr. V. Sumathy
α Savitribai Phule Pune University Savitribai Phule Pune University

Send Message

To: Author

Cognitive Location based Mobile Adhoc Networks Implementation with an Android Operating Systems

Article Fingerprint

ReserarchID

CSTNWS72475

Cognitive Location based Mobile Adhoc Networks Implementation with an Android Operating Systems Banner

AI TAKEAWAY

Connecting with the Eternal Ground
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

Abstract

Cognitive radio (CR) technology is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. CR networks, equipped with the intrinsic capacities of the cognitive radio, will provide an ultimate spectrumaware communication paradigm in wireless communications. Specifically, in cognitive radio ad hoc networks (CRAHNs), the distributed multihop architecture, the dynamic network topology, and the time and location varying spectrum availability are some of the key distinguishing factors. In this paper, intrinsic properties and current research challenges of the CRAHNs are presented. A particular emphasis is given to distributed coordination between CR users through the establishment of a common control channel. Lastly, a new commission called the park model is explained, where CRAHN users may independently determine their own performance based on pre-decided spectrum. The performance is comparable to MANET routing protocols In this system implementation through real time systems with Specialized ANDROID BASED OPERATING SYSTEMS.

References

10 Cites in Article
  1. S Adibi,S Erfani (2006). A multipath routing survey for mobile ad hoc networks.
  2. Kemal Akkaya,Mohamed Younis (2005). A survey on routing protocols for wireless sensor networks.
  3. Ian Akyildiz,Won-Yeol Lee,Mehmet Vuran,Shantidev Mohanty (2006). NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey.
  4. A Daoud,M Alanyali,D Starobinski (2007). Secondary pricing of spectrum in cellular CDMA networks.
  5. R Brodersen,A Wolisz,D Cabric,S Mishra,D Willkomm (2004). Corvus: a cognitive radio approach for usage of virtual unlicensed spectrum.
  6. D Cabric,S Mishra,R Brodersen (2004). Implementation issues in spectrum sensing for cognitive radios.
  7. D Cabric,A Tkachenko,R Brodersen (2006). Spectrum sensing measurements of pilot, energy, and collaborative detection.
  8. Berk Canberk,Ian Akyildiz,Sema Oktug (2008). Primary User Activity Modeling Using First-Difference Filter Clustering and Correlation in Cognitive Radio Networks.
  9. L Cao,H Zheng (2005). Distributed spectrum allocation via local bargaining.
  10. L Cao,H Zheng (2008). Distributed rule-regulated spectrum sharing.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Rajaram. 2014. \u201cCognitive Location based Mobile Adhoc Networks Implementation with an Android Operating Systems\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E4): .

Download Citation

Issue Cover
GJCST Volume 14 Issue E4
Pg. 11- 15
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Version of record

v1.2

Issue date

July 26, 2014

Language
en
Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

Article Matrices
Total Views: 9043
Total Downloads: 2432
2026 Trends
Related Research

Published Article

Cognitive radio (CR) technology is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. CR networks, equipped with the intrinsic capacities of the cognitive radio, will provide an ultimate spectrumaware communication paradigm in wireless communications. Specifically, in cognitive radio ad hoc networks (CRAHNs), the distributed multihop architecture, the dynamic network topology, and the time and location varying spectrum availability are some of the key distinguishing factors. In this paper, intrinsic properties and current research challenges of the CRAHNs are presented. A particular emphasis is given to distributed coordination between CR users through the establishment of a common control channel. Lastly, a new commission called the park model is explained, where CRAHN users may independently determine their own performance based on pre-decided spectrum. The performance is comparable to MANET routing protocols In this system implementation through real time systems with Specialized ANDROID BASED OPERATING SYSTEMS.

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

Cognitive Location based Mobile Adhoc Networks Implementation with an Android Operating Systems

Rajaram
Rajaram Savitribai Phule Pune University
Dr. V. Sumathy
Dr. V. Sumathy

Research Journals