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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Netwatch: Empowering Network Visibility and Blackhole Detection & Identification in Segment Routing |
| Authors Name: | Sanjay H S , Kumaraswamy S |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_214527
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| Published Paper Id: | IJNRD2404057 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Detecting network black holes (BHs) proves to be a formidable undertaking, given their propensity to disrupt services for particular traffic flows due to device misconfigurations. The intricacies escalate within the framework of Segment Routing (SR) due to the necessity of an encapsulation mechanism for enforcing segment lists on packets. While existing active probing tools targeting IPv6 BH detection fall short in the context of SR, this project aims to confront the challenge of identifying SR Black Holes within SR domains. In this endeavor, we draw upon an experimental showcase illustrating the creation of an SR Black Hole to underscore the limitations inherent in active probing-based tools. To surmount these constraints, we introduce a passive framework named Segment Routing Black Holes Detection (SR-BHD). SR-BHD capitalizes on specific traffic counters present in SR-capable nodes to validate the conservation of flow principle across network elements. Functioning by continuously monitoring traffic flow within SR domains, SR-BHD offers an alternative to active probing. During the experimental evaluation, various scenarios are simulated, and SR environments are emulated to assess the efficacy of SR-BHD. The outcomes reveal that SR-BHD adeptly discerns SR BHs by identifying any deviation from the flow conservation principle. This capability enables network administrators to promptly recognize and rectify BHs, mitigating the impact on traffic flows and ensuring a dependable network performance. In accordance with proper citations, the SR-BHD framework stands as an innovative approach for passive SR Black Hole detection, providing an efficient alternative to active probing. Its adaptability within SR domains and adept handling of challenges posed by the encapsulation mechanism solidify its status as a valuable tool for network monitoring and failure detection within SR architectures. Overall, this project makes a substantial contribution to enhancing the reliability and performance of SR networks by addressing the specific issue of detecting SR Black Holes. The SR-BHD framework emerges as a pragmatic and effective solution, empowering network administrators to proactively identify and address BHs, thereby guaranteeing uninterrupted and efficient traffic flow within SR domains. |
| Keywords: | Index Terms: Segment routing, network black hole, failure detection, network monitoring, flow conservation principles |
| Cite Article: | "Netwatch: Empowering Network Visibility and Blackhole Detection & Identification in Segment Routing", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.a439-a450, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404057.pdf |
| Downloads: | 00050 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404057 Registration ID: 214527 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: a439-a450 Country: BANGALORE, KARNATAKA, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404057 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404057 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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