Under the guidance of: Mr. G. Praveen Babu Associate Professor

1. Autonomous Reconfiguration System for Radio Links in Wireless Mesh Networks PresentedBy : G. Nata Raju (11031D6427) M.Tech (CNIS) Under the guidance of: Mr. G. Praveen Babu Associate Professor

2. Outline • Abstract • Introduction • The Genesis – Existing System • Disadvantages of existing system • Solution - Proposed System • Advantages • Motivation • Algorithm • ARS Architecture • Implementation steps • Modules • Requirement Analysis • References

3. Abstract • Multi-hop wireless mesh networks (WMNs) experience frequent link failures caused by channel interference, dynamic obstacles and/or applications’ bandwidth demands. These failures cause severe performance degradation in WMNs or require expensive, manual network management for their real-time recovery • This project presents an autonomous network reconfiguration system (ARS) that enables a multiradio WMN to autonomously recover from local link failures to preserve network performance. By using channel and radio diversities in WMNs, ARS generates necessary changes in local radio and channel assignments in order to recover from failures.

4. Introduction • Wireless Mesh Networks(WMN) are used in variety of applications, such as public safety, environment monitoring, and citywide wireless Internet services • Continuously evolving to meet the increasing capacity demands and other emerging applications. • Preserving the required performance of these WMNs is still a challenging problem. • Main problems are: • Increasing bandwidth demands new mobile users and applications. • Significant channel interference from other coexisting wireless networks • Not able to use some frequency channels because of spectrum etiquette or regulation

5. The Genesis – Existing System • Normal WMN • Ad-hoc routing protocols (AODV, DSR) • Manual network management for their real-time recovery • First, resource-allocation algorithms can provide (theoretical) guidelines for initial network resource planning. • Next, a greedy channel-assignment algorithm can reduce the requirement of network changes by changing settings of only the faulty link(s). • Third, fault-tolerant routing protocols, such as local re-routing or multi-path routing, can be adopted to use network-level path diversity for avoiding the faulty links.

6. Previous Network Model with link failures • Wireless Mesh Networks shows initial frequency assignment. This network shows some link failures. • After gaining the experience with number of network failures then requires reconfiguration settings.

7. Disadvantages of existing system • Degree of reconfiguration is not considered • Service disturbances occurs • Provides undesirable “global” re-configuration changes • Interference problems are created here • Some plans may consider the faulty links • They rely on detour paths or redundant transmissions hence link quality degradation problem occurs • Unsuitable for dynamic network reconfiguration

8. Solution - Proposed System • Autonomous Network Reconfiguration System (ARS) • It allows a multi-radio WMN to autonomously reconfigure its local network settings—channel, radio, and route assignment—for real-time recovery from link failures. • Equipped with a reconfiguration planning algorithm • Identifies local configuration changes for the recovery while minimizing changes of healthy network settings. • Core part: • Searches for feasible local configuration changes. • Identifies reconfiguration plans. • A monitoring protocol.

9. Advantages • Link quality increases • Satisfy the applications’ QoS demands, accommodating twice more flows than static assignment • Maximized packets distribution • Increases the network throughput and channel efficiency • Avoids the ripple effect via QoS-aware reconfiguration planning, unlike the greedy approach. • Increases the PDR (packet delivery ratio) • Requires only local re-configuration • It requires the minimum number of changes for the healthy network settings. • It avoids propagation of QoS failures to neighboring links.

10. Stability Addressing two phenomena that undermine the network stability due to CA Ripple Effect

11. Motivation • Multi Radio Wireless Mesh networks enables reconfigure channels and radio assignments. • Interference problems overcome with local link repair mechanism. • Local link repair provides the tuned channels. • Re-association of radios and channels. • Alternative channels selection. • Periodically allocates the link usage. • Different kinds of estimation protocols implementation: Route Reservation protocol, Expected transmission Number, Weighted Cumulative Expected Transmission time etc. • Dynamic resource allocation algorithms provides sufficient load allocation.

12. Performance Evaluation of Existing and Proposed Rerouting • Static routing represents the performance with dotted edges line. It shows the less throughput like 3MBPS. • ARS provides continuous edge line and shows the performance throughput can reach up to 13MBPS.

13. Algorithm • ARS is equipped with a reconfiguration ARSplanning algorithm that identifies local configuration changes for the recovery, while minimizing changes of healthy network settings. • Briefly, ARS first searches for feasible local configuration changes available around a faulty area, based on current channel and radio associations. Then, by imposing current network settings as constraints, • ARS identifies reconfiguration plans that require the minimum number of changes for the healthy network settings. • ARS detects a long-term (lasting for weeks or months) failures, network-wide planning algorithms can be used.

14. How is it going to be ?! • The proposed work has the following strategies: • Network construction • Link-State • Group organizer • Failure detector • Gateway planner • Plan generator • o QOS filter • benefit filter • o Optimal • o Analyser

15. Architecture

16. Implementation steps 1. Localized Reconfiguration 2. QoS aware Planning 3. Autonomous reconfiguration & link quality monitoring 4. Cross layer interaction

17. Step1: Monitoring Period • Each and every link contains link quality (link measurement). • Each and every monitoring results forwards to gateways. • Step2: Group leader election • Any link can not handle the load of packets. • It can forward the request for new channel. • New channel identification purpose we need to require group leader election.

18. Localized Reconfiguration • Multiple channels are works as a radio association channels. • ARS generates the reconfiguration plans. • Reconfiguration plans applied in failure locations with remote connections. • Step3: Planning period • Failure information forwards through gateways to group leader. • All nodes are forward the request message for new plan • Group leader provides reconfiguration plan. • Send reconfiguration plan to all nodes.

19. QoS Aware Planning • ARS provides satisfiable reconfiguration plan. • Finds out perfect channel utilization. • Generation of good reconfiguration plans. • Link Quality Monitoring: • ARS provides good link quality using distributed packets mechanism. • Changes the plan, applies the reconfiguration techniques.

20. Step 4: Reconfiguration Period • After some time changes the plan. • Apply the changes in different number of links. • Add some new neighbors for new plan. • Cross layer interaction • 1.It can provides rerouting planning. • 2.Good connectivity for recovery of networks. • 3.Recovery time use some cross layer routing protocols.

21. Planning for Localized Network Reconfiguration • Feasible Plan generation: • Avoiding a faulty channel. • Maintaining network connectivity and utilization. • Controlling the scope of reconfiguration changes.

22. Avoiding Faulty Channel

23. QoSSatisfiability Evaluation 1.Per link bandwidth estimation. 2.Examining per-link bandwidth satisfiability. 3.Avoiding cascaded link failures

24. Choosing best plan • Quantifying the fairness of a plan • Breaking a tie among multiple plan Complexity of ARS: N is the number of available channels, m is the number of radios. Complexity represents O(n+m). L is number of links represents the complexity O(l(n+m).

25. Modules 1. Multi-radio WMN 2. Link-Failure Detection 3. Leader Node 4. Network Planner

26. Multi-radio WMN A network is assumed to consist of mesh nodes, IEEE 802.11-based wireless links, and one control gateway. Each mesh node is equipped with n radios, and each radio’s channel and link assignments are initially made by using global channel/link assignment algorithms.

27. Link-Failure Detection ARS in every mesh node monitors the quality of its outgoing wireless links at every tm (e.g., 10 sec) and reports the results to a gateway via a management message. Second, once it detects a link failure(s), ARS in the detector node(s) triggers the formation of a group among local mesh routers that use a faulty channel, and one of the group members is elected as a leader and coordinating the reconfiguration.

28. Leader Node The leader node sends a planning-request message to a gateway. If any link is failed, group members send request to the particular leader after that the leader node send request to the gateway.

29. Network Planner It generates reconfiguration plans only in a gateway node. Network planner plans the diversity path for avoiding the faulty links. Then, the gateway synchronizes the planning requests—if there are multiples requests—and generates a reconfiguration plan for the request. Fourth, the gateway sends a reconfiguration plan to the leader node and the group members. Finally, all nodes in the group execute the corresponding configuration changes, if any, and resolve the group.

30. Requirement Analysis System Requirements: • Tool : Network Simulator – II • Operating System : Ubuntu Desktop 12.10 Hardware Requirements: • Hard disk : 60GB • RAM : 1GB • Processor : Intel P - IV

31. System Design

32. References [1] I. Akyildiz, X. Wang, and W. Wang, “Wireless mesh networks: A survey,” Comput. Netw., vol. 47, no. 4, pp. 445–487, Mar. 2009. [2] J. Zhao, H. Zheng, and G.-H. Yang, “Distributed coordination in dynamic spectrum allocation networks,” in Proc. IEEE DySPAN, Baltimore, MD, Nov. 2009, pp. 259–268. [3] A. Akella, G. Judd, S. Seshan, and P. Steenkiste, “Self-management in chaotic wireless deployments,” in Proc. ACM MobiCom, Cologne, Germany, Sep. 2010, pp. 185–199. [4] M. J. Marcus, “Real time spectrum markets and interruptible spectrum: New concepts of spectrum use enabled by cognitive radio,” in Proc. IEEE DySPAN, Baltimore, MD, Nov. 2010, pp. 512–517. [5] A. Brzezinski, G. Zussman, and E. Modiano, “Enabling distributed throughput maximization in wireless mesh networks: A partitioning approach,” in Proc. ACM MobiCom, Los Angeles, CA, Sep. 2010, pp. 26–37.