Larry C. Llewellyn, Kenneth M. Hopkinson, Member, IEEE, Scott R. Graham, Member, IEEE

Presented by Devarsh Patel

Outline

Introduction Related Work Quality-of-Service Routing Using FDCB Fault Tolerance in QoS AD HOC

Networks Problem Definition Analysis And Results

Introduction Quality of Service – A defined level of performance in

a communications network required by a type of network traffic.

QoS requirement for effective Mobile Ad Hoc Networks (MANET’s) include fault tolerance and fast recovery

Problems in routing QoS traffic in mobile networks: Stability – Broadcast packets used to discover QoS

parameters of neighbors and negotiate QoS paths flood the network ○ Solution – Clustered Approach

Recoverability – Minimizing QoS impact due to network failures. Two approaches are there:

Global fault-tolerant algorithm Local fault-tolerant algorithm

○ Experiments shows local fault-tolerant algorithm has benefits over global alternative

Related Work Quality-of-Service Routing

Proportional Sticky Routing (PSR) - First localized QoS routing scheme

Credit-Based Routing (CBR) - Uses a credit scheme that rewards a path for flow acceptance and penalizes rejection.

Quality-Based Routing (QBR) - Determines paths based on QoS metric values. QBR monitors a path and translates flow values into average path qualities.

Delay-Based QoS Routing (DBR) - Uses the average delay on a path to make its routing decisions.

Stable and Delay Constraints Routing (SDCR) – Works in two major phases: routing discovery and maintenance.

Related Work Multiconstrained QoS Routing

NP-Hard problem Involves finding and reserving routes that satisfy

multiple constraints Centralized routing Distributed routing Hierarchical routing

Quality-of-Service Routing Using MPLS and Multicommodity Flows

Quality-of-Service Routing Using Heuristics

Quality-of-Service Routing Using FDCB Fully Distributed Cluster Based (FDCB)

is similar to hierarchical routing Each cluster node only maintains QoS

information of a fraction of a network Result – increase in nodes should not

increase memory or runtime Benefits – The distributed nature of FDCB

allows it to avoid unmanageable shared global state

Quality-of-Service Routing Using FDCB

TABLE 1

Sequence of Operations for Maintaining Communications

Drawbacks Though support for cluster joins and leaves

are provided, problem on mitigating the impact on QoS in the event of an unpredicted node leave/failure is untreated

Fault Tolerance in QoS Ad Hoc Networks First technique - To repair the broken path at the failed node

by shifting traffic to a neighboring node and then routing around the breaking point.

Second technique – Multilevel path redundancy which establishes multiple paths for the same connection

TABLE 2

Cases of Disruption

Problem Definition

EFDCB routing protocol – A fault tolerant modification to FDCB routing

EFDCB extends FDCB to provide the scalability, efficiency, and fault tolerance critical to maintain QoS connections in a mobile environment.

Goal - To determine if EFDCB provides efficient QoS route recovery by testing it against FDCB.

Approach To achieve efficient fault tolerance, FDCB is

augmented so that the cluster-head has complete “cluster-state” knowledge

Connectivity awareness - QoS connections currently supported by each cluster member, each member’s resource availability, and the cluster topology.

Design Clustering:

○ Clustering algorithm adopted here is a modified version of the Generalized Distributed and Mobility Adaptive Clustering (GDMAC) to support fault tolerance in QoS supporting MANETs.

QoS Routing FDCB uses on-demand reactive routing

scheme EFDCB uses Clustered Fisheye State

Routing (CFSR) to reduce redundant broadcast routing control messages

Result – Lower overhead by limiting the messages from much of the network

Disadvantage - routing control messages traverse the network at a lower rate since a smaller fraction of network nodes broadcast full control messages.

CFSR is QoS ready with the addition of bandwidth and channel quality information to the link state entry.

TABLE 3 CFSR definitions

CFSR significantly reduces the broadcast

control packets over pure proactive protocols.

Fault tolerance:

Fig. 1. Clustered ad hoc network

TABLE 4 Cases causing QoS Path Breakage

TABLE 5 EFDCB Definitions

EFDCB Protocol

Message driven Procedure executed by the node

depends on the message it receives. At cluster set up, or when a node is

added to the network, its variables are initialized as follows:

Assumptions All nodes have a unique identifier. Two nodes can be members of the same cluster Nodes signal their presence via a periodic beacon

message. When a node does not hear from a known neighbor

within a set timespan, it assumes the neighbor is either “dead” or out of range due to mobility

Determining a node has failed or moved out of range will prompt the corresponding procedure.

All procedures are atomic except Route_traffic(u) and the procedures executed to respond to the PATH(v.rsrcs, dst) and CTS(u) messages.

Messages and Procedures Summary of the key messages

TABLE 6

Messages

Fig. 2. Overview diagram of Node_failure and Init Procedures of EFDCB.

Following procedures are initiated when the corresponding message is received

On receiving PARAMS(u.NT, u.AT, Cluster-head): performed by the Cluster-head (in this case, node v)

On receiving PARAMS(CT, Cluster-head) On receiving REPAIR(ConnexParams(p), v,

Clusterhead) On receiving LINK_REPAIRED(failed_node,

u, x) On receiving REPAIR_FAILURE(u, Cluster-

head)

On receiving FAILED_CONNEX(failed_node, u, v)

On receiving QOS_VALID(v, u) On receiving HELLO(u, Cluster-head,

Init) On receiving MYNGHBRS((u) Cluster-

head) On receiving PATH(u.rsrcs, dst) On receiving CTS(u) On receiving JOIN(u, z) On receiving RESIGN(w)

Analysis And Results System Boundaries focuses on EFDCB’s ability to reduce

recovery time for QoS traffic. Clustering portion of EFDCB is

bootstrapped CFSR also bootstrapped

Workload Rate at which nodes in the network fail Different node failure rate used for each

group of simulations Node that fails is chosen randomly

Performance Metrics connection recovery time, number of

dropped packets, throughput, and amount of sustainable flow bandwidth.

Experimental Factors System ○ EFDCB’s distributed nature resilient to many

factors which affect FDCB ○ Bandwidth a key factor

Workload ○ The primary interests here are connection

recovery time, number of dropped packets, throughput, and the sustainable flow bandwidth.

Failure Rate

TABLE 7 TABLE 8 Experimental Design for the First Phase of Experiments Experimental Design for the Second Phase of Experiments

Evaluation Technique Fig. 3. Experimental network architecture.

goal is to balance the gateway interconnections, the number of cluster, and the overall size and complexity in the scenario tested.

Preliminary Testing

Fig. 4. Recovery time versus number of hops. Fig. 5. Mean failures versus failure rate.

Result of Simulations

Fig. 6. Raw data plot of recovery time versus failure rate.

TABLE 9 Initial Experimentation Based on Source-Destination Hop Distance

Fig. 7. Mean recovery time versus failure rate.

Fig. 8. Fitted line plot for FDCB mean recovery time versus failure rate.

Fig. 9. Fitted line plot for FDCB mean recovery time versus failure rate.

Fig. 10. Raw data plot of dropped packets versus failure rate.

Fig. 11. Mean dropped packets versus failure rate.

Fig. 12. Mean percentage of dropped packets versus failure rate.

Fig. 13. Fitted line plot for FDCB mean dropped packets versus failure rate. Fig. 14. Fitted line plot for EFDCB mean dropped packets versus failure rate.

Fig. 15. Raw data plot of throughput versus failure. Fig. 16. Mean throughput versus failure rate.

Fig. 17. Percentage of optimal throughput versus failure rate. Fig. 18. Sustained flow bandwidth versus failure rate.

Fig. 19. Confidence interval graphs of: (a) dropped packets for EFDCB versus FDCB, (b) recovered packets for EFDCB versus FDCB, (c) number of failures for EFDCB versus FDCB, (d) recovery time for EFDCB versus FDCB.

Thank You