Study of Distance Vector Routing Protocols for Mobile Ad Hoc Networks

Yi Lu, Weichao Wang, Bharat Bhargava

CERIAS and Department of Computer Sciences

Purdue University

March 24th, 2003*The research is supported by NSF, CERIAS, and CISCO

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Index

Research motivation Our contribution Introduction to studied protocols Simulation and analysis Our approach: Congestion aware

distance vector (CADV) protocol Conclusion

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Research motivation

The hybrid of Internet, cellular system and mobile ad hoc networks is emerging. It enables the pervasive computing at any where, any time. [S. Bush, GE Research ’99]

The limited resources available to mobile nodes put challenges to the design of ad hoc routing protocols. [Corson & Macker, IETF MANET WG ’02]

More than ten routing protocols have been proposed. A protocol tends to outperform others in some network

environments. [Jiang et al, ICCCN ’01] Research is required to ascertain the reasons that lead to

the difference in performance and guide the design of a more adaptable protocol.

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Our contribution

The linear dependence between network topology changes and node mobility is investigated

The suitable network environments for AODV and DSDV are identified

The major cause for packet drop is studied A new protocol integrating congestion

avoidance is proposed

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Destination sequenced distance vector (DSDV) Proposed by Perkins in [SigCOMM ’94]; The nodes periodically broadcast the routing tables and

proactively construct the routes; Using destination sequence numbers to avoid routing loop

and identify the freshness of the information; Advantages:

Short delay brought by the proactive feature Difficult for the attackers to control the propagation of false

information Disadvantages:

Difficult to scale to large networks Computation and communication resources wasted on

unused routes

Introduction to DSDV

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Ad hoc on-demand distance vector (AODV) Proposed by Perkins and Royer [Mobile Com and App

’99]; The routes are detected only when they are needed

by the applications; Broadcast routing request (RREQ) and unicast routing

reply (RREP) Using destination sequence numbers to avoid routing

loop and identify the freshness of the information; Advantages:

Low overhead and smaller routing tables in light load networks

Fast expiration of unused routes Disadvantages:

On-demand feature brings a longer delay for the first packet Malicious nodes have more flexibility on conducting attacks

Introduction to AODV

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The frequency of link changes and route changes directly impact the overhead and adaptability of routing protocols;

However, no network model is available to give out mathematical analysis;

Our simulation will show that: Link changes and route changes fit into linear

functions of the maximum moving speed of node when pause time is fixed;

Link changes and route changes fit into linear functions of the node pause time when maximum moving speed is fixed

Thus, topology changes can be measured by node mobility.

Correlation between link change and node mobility

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Correlation between link change and node mobility (con’d)

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AODV and DSDV are studied by varying network environment parameters;

Input parameters: Node mobility (maximum moving speed) Traffic load (number of connections) Network size (number of mobile nodes)

Output parameters: Delivery ratio Average packet delay Normalized protocol overhead Normalized power consumption

Simulation experiments

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Simulation setup

Simulator ns-2

Examined protocols AODV and DSDV

Simulation duration 1000 seconds

Simulation area 1000 m x 1000 m

Transmission range 250 m

Movement model Random waypoint

Maximum speed 4 – 24 m/s

Traffic type CBR (UDP)

Data payload 512 bytes/packet

Packet rate 4 packets/sec

Node pause time 10 seconds

Bandwidth 1 Mb/s

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Purpose: study the impact of mobility on the performance;

Observation: Delivery ratio of DSDV drops faster as node mobility

increases; The normalized overhead of AODV is 2—4 times

more than DSDV when the network is loaded; The overhead of DSDV keeps stable as node mobility

increases; The power consumption of both protocols is stable

and close to each other;

Experiment 1: varying maximum speed

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Simulation results of varying maximum speed

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Purpose: examine the performance of both protocols under different loads;

Observation:Delivery ratios of both protocols drop

drastically as the network is fully loaded;The normalized overhead of AODV increases

faster when the network is fully loaded;The power consumption of both protocols is

stable and close to each other;

Experiment 2: varying traffic load

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Simulation results of varying traffic load

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Purpose: investigate the reasons that cause packet loss, and guide the design of response;

Observation: In both protocols, congestion is the primary

reason for packet dropDSDV is easier to lead to congestionDSDV does not drop packets for “no route”; In DSDV, when links break, the intermediate

nodes will buffer packets until new routes are available. This reduces packet drop.

Experiment 3: Reasons for packet drop

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Simulation results of packet drop

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Purpose: study the impact of node density on protocol performance;

Observation:When the number of connections > 50, the

delivery ratio of DSDV is better than AODV.The protocol overhead of AODV is larger than

DSDV when the network is fully loaded.

Experiment 4: varying network size

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Simulation results of varying network size

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The proactive protocols have advantages in supporting:Applications requiring QoS in ad hoc

networks; Intrusion detection requiring distributed, global

traffic monitoring; Design objective:

Dynamically detect and avoid congestion and route packets through light-loaded paths;

Improve network performance

Congestion Aware Distance Vector (CADV)

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Congestion Aware Distance Vector (con’d)

Components: Real time traffic monitor Packet scheduler and traffic control Route maintenance module

Route determination policy: Every node estimates the expected delay of

sending a packet as:

Apply a function f( E [ D ], distance) to choose route

Ln

DDE i][

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Congestion Aware Distance Vector (con’d)

Performance of CADV: The delivery ratio of CADV outperforms AODV

and DSDV The end-to-end delay becomes longer The protocol overhead is larger than DSDV. but

because it is a pro-active protocol, the overhead does not increase as the traffic load increases.

The power consumption does not vary much

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Preliminary results of CADV

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The link changes and route changes are, with a high probability, linear functions of the maximum speed, and node pause time

In less stressful environments, AODV outperforms DSDV for all metrics except protocol overhead. DSDV performs better in denser networks with a heavier load

On-demand protocols propagate the link changes faster, and reduce the packet drop caused by them

Network congestion is the dominant reason for packet drop. The performance of the protocols can be improved by congestion avoidance

Observations & Conclusions

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Develop a complete approach that considers more parameters such as available queue length and the delay on a path during the route determination

Introduce the random feature into route determination to avoid traffic fluctuation

Develop a fast response mechanism (local repair) in proactive protocols to reduce packet drop cause by route changes

Future work