Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Probability, statistics, and queueing theory with computer science applications
Probability, statistics, and queueing theory with computer science applications
Impossibility of distributed consensus with one faulty process
Journal of the ACM (JACM)
On the Quality of Service of Failure Detectors
IEEE Transactions on Computers
STACS '89 Proceedings of the 6th Annual Symposium on Theoretical Aspects of Computer Science
Implementation and Performance Evaluation of an Adaptable Failure Detector
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
DSN '04 Proceedings of the 2004 International Conference on Dependable Systems and Networks
An integrated experimental environment for distributed systems and networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Adaptive Timeout Policies for Wireless Links
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 01
Understanding congestion in IEEE 802.11b wireless networks
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Randomization can be a healer: consensus with dynamic omission failures
DISC'09 Proceedings of the 23rd international conference on Distributed computing
QoS self-configuring failure detectors for distributed systems
DAIS'10 Proceedings of the 10th IFIP WG 6.1 international conference on Distributed Applications and Interoperable Systems
An Adaptive Media-Aware Retransmission Timeout Estimation Method for Low-Delay Packet Video
IEEE Transactions on Multimedia
Adaptare: Supporting automatic and dependable adaptation in dynamic environments
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Algorithms for solving distributed systems problems often use timeouts as a means to achieve progress. They are designed in a way that safety is always preserved despite timeouts being too small or too large. A conservatively large static timeout value is usually selected, such that the overall system performance is acceptable in the normal case. This approach is good enough in stable environments, but it may compromise performance in more dynamic settings, such as in wireless networks. In this case, a better approach is to dynamically adjusting timeouts according to the observed network conditions. This paper clearly illustrates the achievable improvements and thus justifies the importance of using adaptive protocols in dynamic environments. We describe our pragmatic approach to transform a static timeout-based consensus protocol for ad hoc wireless networks into a fully autonomic and adaptive solution. Our comparative experiments, performed in a wireless environment, show that in contrast with the original static protocol, the adaptive solution leads to an almost constant bandwidth utilization despite increasing the number of consensus participants, and the overall consensus execution time increases linearly instead of exponentially.