Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
CODA: congestion detection and avoidance in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Mitigating congestion in wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Congestion control and fairness for many-to-one routing in sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
TCP symbiosis: congestion control mechanisms of TCP based on Lotka-Volterra competition model
Interperf '06 Proceedings from the 2006 workshop on Interdisciplinary systems approach in performance evaluation and design of computer & communications sytems
A survey on wireless multimedia sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A conceptual framework for bio-inspired congestion control in communication networks
Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems
| Hi-index | 0.00 |
Next generation communication networks are moving towards autonomous infrastructures that are capable of working unattended under dynamically changing conditions. The new network architecture involves interactions among unsophisticated entities which may be characterized by constrained resources. From this mass of interactions collective unpredictable behavior emerges in terms of traffic load variations and link capacity fluctuations, leading to congestion. Biological processes found in nature exhibit desirable properties e.g. self-adaptability and robustness, thus providing a desirable basis for such computing environments. This study focuses on streaming applications in sensor networks and on how congestion can be prevented by regulating the rate of each traffic flow based on the Lotka-Volterra population model. Our strategy involves minimal exchange of information and computation burden and is simple to implement at the individual node. Performance evaluations reveal that our approach achieves adaptability to changing traffic loads, scalability and fairness among flows, while providing graceful performance degradation as the offered load increases.