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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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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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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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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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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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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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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
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