Quality of service based routing: a performance perspective
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Power-aware routing in mobile ad hoc networks
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
QoS routing in networks with inaccurate information: theory and algorithms
IEEE/ACM Transactions on Networking (TON)
Evaluating the impact of stale link state on quality-of-service routing
IEEE/ACM Transactions on Networking (TON)
OLSR Performance Measurement in a Military Mobile Ad-hoc Network
ICDCSW '04 Proceedings of the 24th International Conference on Distributed Computing Systems Workshops - W7: EC (ICDCSW'04) - Volume 7
Information Collection Services for QoS-Aware Mobile Applications
IEEE Transactions on Mobile Computing
Extending network knowledge: making OLSR a quality of service conducive protocol
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Load-Balanced Routing in Wireless Networks: State Information Accuracy Using OLSR
WIMOB '07 Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
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To support energy-efficient routing, accurate state information about energy level should be available. But due to bandwidth constraints, communication costs, high loss rate and the dynamic topology of MANETs, collecting and maintaining up-to-date state information is a very complex task. In this work, we use Optimized Link State Routing (OLSR) as the underlying routing protocol. We report the quantification of state information accuracy under different traffic rates. We are focusing on energy level as QoS metric, which has been used for routing decisions in many energy-efficient routing protocol proposals. State information accuracy is defined as the average difference between perceived energy level (by the node making a routing decision) and its actual value. The results show that state information is inaccurate, especially under high traffic rates. Tuning the OLSR protocol parameters has no noticeable impact on inaccuracy levels. Based on our inaccuracy level analysis, we propose three additional techniques as an attempt to reduce inaccuracies. We compare the different techniques against each other and against the basic OLSR protocol. Two of our proposed techniques show significant improvements in inaccuracy levels. In particular, a technique we call smart prediction achieves highly accurate perceived energy levels under all traffic loads.