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Mitigating routing misbehavior in mobile ad hoc networks
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Source International Conference on Mobile Computing and Networking archive
Proceedings of the 6th annual international conference on Mobile computing and networking table of contents
Boston, Massachusetts, United States
Pages: 255 - 265  
Year of Publication: 2000
ISBN:1-58113-197-6
Authors
Sergio Marti  Department of Computer Science, Stanford University, Stanford, CA
T. J. Giuli  Department of Computer Science, Stanford University, Stanford, CA
Kevin Lai  Department of Computer Science, Stanford University, Stanford, CA
Mary Baker  Department of Computer Science, Stanford University, Stanford, CA
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
IEICE : Inst of Electronics, Info & Communication Engineers
IFIP WG 6.3 : IFIP WG 6.3
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
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ABSTRACT

This paper describes two techniques that improve throughput in an ad hoc network in the presence of nodes that agree to forward packets but fail to do so. To mitigate this problem, we propose categorizing nodes based upon their dynamically measured behavior. We use a watchdog that identifies misbehaving nodes and a pathrater that helps routing protocols avoid these nodes. Through simulation we evaluate watchdog and pathrater using packet throughput, percentage of overhead (routing) transmissions, and the accuracy of misbehaving node detection. When used together in a network with moderate mobility, the two techniques increase throughput by 17% in the presence of 40% misbehaving nodes, while increasing the percentage of overhead transmissions from the standard routing protocol's 9% to 17%. During extreme mobility, watchdog and pathrater can increase network throughput by 27%, while increasing the overhead transmissions from the standard routing protocol's 12% to 24%.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  214

Collaborative Colleagues:
Sergio Marti: colleagues
T. J. Giuli: colleagues
Kevin Lai: colleagues
Mary Baker: colleagues