Autonomously recover from wireless link failure through "Autonomous Network Reconfiguration System" (ARS) with multi-radio in WMN

Inhalt

1.INTRODUCTION

2. EXISTING SYSTEM
2.1 Localized reconfiguration
2.2 Qo S-Constraints
2.3 Cross-layer interaction
2.4 Limitations of Existing System

3.proposed system
3.1 The ARS Architecture
3.2 Multi-radio WMN (mr-WMNs)
3.3 Localized Network Reconfiguration
3.3.1 Generating feasible plans
3.3.2 Qo S-Satisfiability Evaluation
3.3.3 Choosing the best plan
3.4 Complexity of ARS
3.5 Advantages of proposed system

4. PERFORMANCE Evaluation
4.1 Methodology
4.1.1 Simulation Environment
4.2 Module Descriptions

5. Results And Analysis

6.CONCLUSION

7.FUTURE WORK

8.REFERENCES

Abstract This paper describes the technique to recover from the failures that occurs in Wireless Mesh networks(WMN) like node failure, link failures etc , due to channel interference, dynamic obstacles or application bandwidth demands. This paper present an Autonomous network Reconfiguration System (ARS) that enables a multi-radio WMN to autonomously recover from local link failures to preserve network performance. ARS has been implemented and evaluated extensively on our IEEE 802.11-based WMN test-bed as well as through ns-2-based simulation . By using channel and radio diversities in WMNs, ARS generates necessary changes in local radio and channel assignments in order to recover from failures. Next ARS’s on-line reconfigurability allows for real-time failure detection and network reconfiguration, thus improving channel-efficiency by 92%.. Our evaluation results demonstrated the effectiveness of ARS in recovering from local link-failures and in satisfying application’s diverse Qo S demands.

KEYWORDS:Wireless mesh networks,autonomous network reconfiguration system,channel and radio diversity,on-line reconfigurability.

1.INTRODUCTION:

A Wireless Mesh network (WMN) is dynamically self-organized and self-configured, with the nodes in the network automatically establishing and maintaining mesh connectivity among themselves. WMNs will deliver wireless services for a large variety of applications in personal, local, campus, and metropolitan areas networks. Still it is a challenging problem for preserving the required performance of such WMNs, due to heterogeneous and fluctuating wireless link conditions. For example, some links of a WMN may experience significant channel interference. Links in a certain area (e.g., a hospital or police station) might not be able to use some frequency channels because of spectrum etiquette or regulation.

To overcome from the wireless link failures many solutions has been proposed in WMNs, but still they have several limitations as follows. First, resource-allocation algorithms, even though their approach provides a comprehensive and optimal network configuration plan, they often require “global” configuration changes, which are undesirable in case of frequent local link failures. Second, a greedy channel-assignment algorithm can reduce the requirement of network changes by changing settings of only the faulty link(s),this greedy change might not be able to realize full improvements. Third, fault-tolerant routing protocols, i.e, local re-routing or multi-path routing , they rely on detour paths or redundant transmissions, which may require more network resources than link-level network reconfiguration.

We propose an Autonomous network Reconfiguration System (ARS) to overcome from above limitations , this technique allows a multi-radio WMN (mr-WMN) to autonomously reconfigure its local network settings for real-time recovery from link failures. 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. Next, ARS also includes a monitoring protocol that enables a WMN to perform real-time failure recovery in conjunction with the planning algorithm. The accurate link-quality information from the monitoring protocol is used to identify network changes that satisfy applications’ new Qo S demands or that avoid propagation of Qo S failures to neighboring links. Based on the measurement information, ARS detects link failures and/or generates Qo S-aware network reconfiguration plans upon detection of a link failure. ARS can be implemented and evaluated extensively via experimentation on our multi-radio WMN test-bed as well as via ns2-based simulation. ARS out performance.

First, ARS’s planning algorithm effectively identifies reconfiguration plans that maximally satisfy the applications’ Qo S demands, accommodating twice more flows than static assignment. Next, ARS avoids the ripple effect via Qo S-aware reconfiguration planning, unlike the greedy approach. Third, ARS’s local reconfiguration improves network throughput and channel-efficiency by more than 26% and 92%, respectively, over the local re-routing scheme.

2. EXISTING SYSTEM:

First, resource-allocation algorithms can provide (theoretical) guidelines for initial network resource planning. However, even though their approach provides a comprehensive and optimal network configuration plan, they often require “global” configuration changes, which are undesirable in case of frequent local link failures. Next, a greedy channel-assignment algorithm can reduce the requirement of network changes by changing settings of only the faulty link(s). However, this greedy change might not be able to realize full improvements, which can only be achieved by considering configurations of neighboring mesh routers in addition to 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.

2.1 Localized reconfiguration:

Network reconfiguration needs a planning algorithm that keeps necessary network changes (to recover from link failures) as local as possible, as opposed to changing the entire network settings. Even though these algorithms are suitable for static or periodic network planning, they may cause network service disruption and thus are unsuitable for dynamic network reconfiguration that has to deal with frequent local link failures. Next, the greedy channel-assignment algorithm, which considers only local areas in channel assignments might do better in reducing the scope of network changes. Finally, interference-aware channel-assignment algorithms can minimize interference by assigning orthogonal channels as closely as possible geographically. For example, in Fig. 2, if channel 5 is lightly-loaded in a faulty area, the second radio of node C can re-associate itself with the first radio of node I, avoiding configuration changes of other links.

Abbildung in dieser Leseprobe nicht enthalten

Fig. 1. Multi-radio WMN: A WMN has an initial assignment of frequency channels as shown above. The network often experiences wireless link failure and needs to reconfigure its settings. While this approach can improve overall network capacity by using additional channels, the algorithm could further improve its flexibility by considering both radio diversity (i.e., link association) and local traffic information.

2.2 Qo S-Constraints:

Reconfiguration has to satisfy Qo S constraints on each link as much as possible. First, given each link’s bandwidth constraints, existing channel-assignment and scheduling algorithms can provide approximately optimal network configurations. However, these algorithms may require global network configuration changes from changing local Qo S demands, thus causing network disruptions. We need instead a reconfiguration algorithm that incurs only local changes while maximizing the chance of meeting the Qo S demands. For example, if link EH in Fig.1 experiences a Qo S failure on channel 1, then one simple reconfiguration plan would be to re-associate R1 of node H to R2 of node E in channel 5, which has enough bandwidth. The greedy algorithm might be able to satisfy particular links’ Qo S demands by replacing a faulty channel with a new channel.

2.3 Cross-layer interaction:

Network reconfiguration has to jointly consider network settings across multiple layers. In fault-tolerant routing protocols, such as local re-routing or multi-path routing , allow for flow reconfiguration to meet the Qo S constraints by exploiting path diversity, they consume more network resources than link reconfiguration, because of their reliance on detour paths or redundant transmissions.

2.4 Limitations of Existing System:

1. Cannot avoid propagation of Qo S failures to neighboring links.
2. Unsuitable for dynamic network reconfiguration.

3.proposed system:

To overcome the above limitations, we propose an Autonomous Network Reconfiguration System (ARS) that allows a multi-radio WMN to autonomously reconfigure its local network settings—channel, radio, and route assignment—for real-time recovery from link failures. In its core, ARS is equipped with a reconfiguration planning 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. It detects a long-term (lasting for weeks or months) failures, network-wide planning algorithms can be used. Note that hardware failures or broadband-channel failures.

3.1 The ARS Architecture:

Abbildung in dieser Leseprobe nicht enthalten

Fig 2: ARS is implemented across network and link layers as a loadable module of Linux 2.6 kernel.

The above figure shows the software architecture of ARS. First, ARS in the network layer is implemented using netfilter, which provides ARS with a hook to capture and send ARS-related packets such as group-formation messages. In addition, this module includes several important algorithms and protocols of ARS: (i) network planner, which generates reconfiguration plans only in a gateway node; (ii) group organizer, which forms a local group among mesh routers; (iii) failure detector, which periodically interacts with a network monitor in the device driver and maintains an up-to-date link-state table; and (iv) routing table manager, through which ARS obtains or updates states of a system routing table. Next, ARS components in the device driver are implemented in an open source MADWi Fi device driver. This driver is designed for Atheros chipset-based 802.11 NICs and allows for accessing various control and management registers (e.g., longretry, txrate) in the MAC layer, making network monitoring accurate. The module in this driver includes

(i) network monitor, which efficiently monitors link-quality and is extensible to support as many multiple radios as possible ; and (ii) NIC manager, which effectively reconfigures NIC’s settings based on a reconfiguration plan from the group organizer.

3.2 Multi-radio WMN (mr-WMNs):

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. ARS is a distributed system that is easily deployable in IEEE802.11-based mr-WMNs.

ARS self-reconfigurability has following distinct features:

- Localized reconfiguration: On multiple channels and radio associations , ARS generates reconfiguration plans that allow for changes of network configurations only in the vicinity where link failures occurred, while retaining configurations in areas remote from failure locations.

- Qo S-aware planning: Qo Ssatisfiable reconfiguration plans ARS identifies by (i) estimating the Qo Ssatisfiability of generated reconfiguration plans and (ii) deriving their expected benefits in channel utilization.

- Autonomous reconfiguration via link-quality monitoring:

ARS accurately monitors the quality4 of links of each

node in a distributed manner. Furthermore, based on the measurements and given links’ Qo S constraints, ARS detects local link failures and autonomously initiates network reconfiguration.

- Cross-layer interaction: ARS actively interacts across the network and link layers for planning. This interaction enables ARS to include a re-routing for reconfiguration planning in addition to link-layer reconfiguration. ARS can also maintain connectivity during recovery period with the help of a routing protocol.

A lgorithm.1 ars operation at Mesh node i

(1) Monitoring period (tm)

1: for every link j do
2: measure link-quality (lq) using passive monitoring;
3: end for
4: send monitoring results to a gateway g;

(2) Failure detection and group formation period (tf)

5: if link l violates link requirements r then
6: request a group formation on channel c of link l;
7: end if
8: participate in a leader election if a request is received;

(3) planning period ( M , tp )

9: if node i is elected as a leader then
10: send a planning request message (c, M) to a gateway;
11: else if node i is a gateway then
12: synchronize requests from reconfiguration groups Mn
13: generate a reconfiguration plan (p) for Mi;
14: send a reconfiguration plan p to a leader of Mi;
15: end if

(4) Reconfiguration period (p , tr)

16: if p includes changes of node i then
17: apply the changes to links at t;
18: end if
19: relay p to neighbouring members, if any

ARS operation has define in above algorithm as follows:

First, 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 using the well-known bully algorithm, for coordinating the reconfiguration.

Third, the leader node sends a planning-request message to a gateway. Then, the gateway synchronizes the planning request 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.

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