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1. A FAST REROUTE METHOD Team Members J.HENRY JEBHA – 20UCS007 B.VARUN – 20UCS017 S.TAMILARASAN – 20UCS0 2020 – 2024 Batch Guided By, Mrs. K.LEELA RANI M.E(CSE) Assistant Professor

2. Motivation 2 Fast rerouting helps minimize network downtime in the event of a failure or disruption. For applications that require high availability, reducing the time it takes to reroute and recover from failures is crucial. Users generally expect seamless and uninterrupted experiences with applications. Fast reroute ensures that even in the face of network failures, users experience minimal disruption, leading to higher satisfaction. In systems where reliability is critical, such as financial transactions or healthcare applications, minimizing the impact of network failures is essential.

3. Introduction 3 This Project presents a method to find an alternate path, after a link failure, from a source node to a destination node. Since re-convergence of an Interior Gateway Protocol can take hundreds of milliseconds, there is a need for a method that will find an alternate path in less time than this. The target application is a small (up to tens of nodes) access subnetwork of a service provider’s network, which is a typical scale encountered in practice; a service provider typically has many such small regional access networks. Consider a source node sending data to destination node. Suppose some link( i , j) on the shortest path from source to destination fails.

4. Objective 4 The primary goal of our Java project is to implement a Fast Reroute method that leverages advanced algorithms and intelligent decision-making to minimize the impact of network failures. By rapidly identifying alternative paths and rerouting traffic, our system aims to maintain continuous service availability, meeting the stringent demands of real-time applications and ensuring that critical systems remain operational.

5. Base Paper 5 Title :” A Survey of Fast-Recovery Mechanisms in Packet-Switched Networks ” Author & Year: Marco Chiesa,2022. Abstract – —In order to meet their stringent dependability requirements, most modern packet-switched communication networks support fast-recovery mechanisms in the data plane. While reactions to failures in the data plane can be significantly faster compared to control plane mechanisms, implementing fast recovery in the data plane is challenging, and has recently received much attention in the literature.

6. Literature Survey 6 Title Author Methodology Efficient Fast Reroute Algorithms for IP Networks Chen, L. and Wang, Q. Dynamic Programming and Path Computation A Survey on Fast Reroute Techniques in Computer Networks Gupta, R. and Sharma, S. Comparative Analysis and Classification Intelligent Rerouting: A Machine Learning Approach Kim, H. and Lee, J. Machine Learning (Reinforcement Learning)

7. Literature Survey 7 Java-based Network Resilience: A Case Stud Patel, A. and Desai, M. Java Programming and Event-Driven Architecture Optimizing Fast Reroute in SDN Environments Liu, Y. and Zhang, W. Software-Defined Networking (SDN) and Heuristics Enhancing Fast Reroute with Proactive Path Monitoring Wong, E. and Tan, C. Proactive Path Monitoring and Triggers

8. Literature Survey 8 Dynamic Rerouting Strategies in Cloud-based Networks Chen, X. and Zhao, L. Cloud Computing and Genetic Algorithms Dynamic Rerouting for Network Resilience in Java Wang, Q. and Liu, Y. Dynamic Programming and Genetic Algorithms Java-based Adaptive Fast Reroute in SDN Environments Chen, L. and Zhang, W. Software-Defined Networking (SDN) and Heuristics

9. Literature Survey 9 Efficient Fault Tolerance in Java Networks Kim, H. and Lee, J Java Programming and Ant Colony Optimization

10. Requirement Specification 10 Software Requirements: Operating System : Windows 7 Technology Used : Java, JDK 1.6   Hardware Requirements: Processor : Intel(R) Core(TM) i3 Processor Speed : 3.06 GHz Ram : 2 GB Hard Disk Drive : 250 GB CD-ROM Drive : Sony Monitor : “17” inches Keyboard : TVS Gold Mouse : Logitech

11. System Design 11 Fig 1.0 System Design Source node Node F Node E Node D Node C Node B Node G Node H Destination Network (base Station) Set Cost Value for Every Nodes & Deplete Non Functioning Nodes

12. Gantt Chart 12 Fig 1.1 Gantt Chart

13. Extension Work 13 The proposed algorithm increases the WSN lifetime by replacing some of the sensor nodes that are not functioning. In addition to enhancing the active nodes and reducing the data losses, the FNR algorithm reduces the relayed energy consumption by reducing the number of data relayed, as the replaced sensor nodes are usually used the most

14. Modules 14 Blacklist Multipath Routing Directed Diffusion Algorithm Grade Diffusion Algorithm Fault Node Recovery Fast Reroute

15. Blacklist Module 15 Each packet carries a blacklist (a minimal set of degraded links encountered along its path), and the next hop is determined by excluding the blacklisted links. A packet’s blacklist is initially empty and remains empty when there is no discrepancy between the current and the advertised states of links along its path. But when a packet arrives at a node with a degraded link adjacent to its next hop, that link is added to the packet’s blacklist. The packet is then forwarded to an alternate next hop. The packet’s blacklist is reset to empty when the next hop makes forward progress, i.e., the next hop has a shorter path to the destination than any of the nodes traversed by the packet.

16. Multipath Routing Module 16 Multipath routing is a promising routing scheme to accommodate these requirements by using multiple pairs of routes between a source and a destination. Multipath routing is the routing technique of using multiple alternative paths through a network, which can yield a variety of benefits such as increased bandwidth, or improved security. The multiple paths computed might be overlapped, edge-disjointed or node-disjointed with each other. Extensive research has been done on multipath routing techniques.

17. Directed Diffusion Algorithm Module 17 The goal of the DD algorithm is to reduce the data relay transmission counts for power management. The DD algorithm is a query-driven transmission protocol. The collected data is transmitted only if it matches the query from the sink node. In the DD algorithm, the sink node provides the queries in the form of attribute-value pairs to the other sensor nodes by broadcasting the query packets to the whole network. Subsequently, the sensor nodes send the data back to the sink node only when it fits the queries.

18. Grade Diffusion Algorithm Module 18 The GD algorithm not only creates the routing for each sensor node but also identifies a set of neighbor nodes to reduce the transmission loading. Each sensor node can select a sensor node from the set of neighbor nodes when its grade table lacks a node able to perform the relay. The GD algorithm can also record some information regarding the data relay. Then, a sensor node can select a node with a lighter loading or more available energy than the other nodes to perform the extra relay operation. That is, the GD algorithm updates the routing path in real time, and the event data is thus sent to the sink node quickly and correctly.

19. Fault Node Recovery Module 19 Fault node recovery (FNR) algorithm for WSNs based on the grade diffusion algorithm combined with the genetic algorithm. The FNR algorithm creates the grade value, routing table, neighbor nodes, and payload value for each sensor node using the grade diffusion algorithm. In the FNR algorithm, the number of nonfunctioning sensor nodes is calculated during the wireless sensor network operation, The sensor nodes transfer the event data to the sink node according to the GD algorithm when events appear.

20. Fast Reroute Module 20 Techniques developed for fast recovery from multiple-link failures provide more than one forwarding edge to route a packet to a destination. Whenever the default forwarding edge fails or a packet is received from the node attached to the default forwarding edge for the destination, the packets are rerouted on the backup ports. It present a framework for IP fast reroute detailing three candidate solutions for IP fast reroute that have all gained considerable attention. When a forwarding link on a tree fails, the packet may be switched to the other tree.

21. Network 21

22. Appendix A-Sample screen Shots   22

23. Node A after Sending Packets 23

24. Node B with received packets 24

25. Node I (Destination) after receiving the packets from Node A (Source) 25

26. Network after sending the packets to destination node 26

27. Social Impact 27 a fault node recovery algorithm for WSN based on the grade diffusion algorithm combined with a genetic algorithm. The FNR algorithm requires replacing fewer sensor nodes and reuses the most routing paths, increasing the WSN lifetime and reducing the replacement cost.

28. Journal 28

29. References 29 R. Agrawal , T. Imielinski , and A. Swami, “Mining Association Rule between Sets of Items in Large Databases,” Proc. ACM SIGMOD Conf. on Management of Data, pp. 207-216, May 2021. R. Agrawal and R. Srikant , “Fast Algorithm for Mining Association Rules,” Proc. Int’l. Conf. on Very Large Databases, pp. 478- 499, Sept. 2022. R. Agrawal and R. Srikant , “Mining Sequential Patterns,” Proc. Int’l. Conf. on Data Engineering, pp. 3-14, Mar. 2000.

30. Sites Referred 30 http://www.ieee.org http://www.almaden.ibm.com/software/quest/Resources/

31. Thank You