Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Distributed regression: an efficient framework for modeling sensor network data
Proceedings of the 3rd international symposium on Information processing in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Spatio-temporal correlation: theory and applications for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: In memroy of Olga Casals
Gathering correlated data in sensor networks
Proceedings of the 2004 joint workshop on Foundations of mobile computing
Efficient gathering of correlated data in sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Spatial correlation-based collaborative medium access control in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Distributed source coding using syndromes (DISCUS): design and construction
IEEE Transactions on Information Theory
Computing the State of Specknets: Further Analysis of an Innate Immune-Inspired Model
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Object tracking with an AIS-inspired algorithm
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A survey on bio-inspired networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
Bio-inspired networking: from theory to practice
IEEE Communications Magazine
Immune system inspired reliable query dissemination in wireless sensor networks
ICARIS'11 Proceedings of the 10th international conference on Artificial immune systems
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Wireless sensor networks (WSNs) are event-based systems that rely on the collective effort of dense deployed sensor nodes. Due to the dense deployment, since sensor observations are spatially correlated with respect to spatial location of sensor nodes, it may not be necessary for every sensor node to transmit its data. Therefore, due to the resource constraints of sensor nodes it is needed to select the minimum number of sensor nodes to transmit the data to the sink. Furthermore, to achieve the application-specific distortion bound at the sink it is also imperative to select the appropriate reporting frequency of sensor nodes to achieve the minimum energy consumption. In order to address these needs, we propose the new Distributed Node and Rate Selection (DNRS) method which is based on the principles of natural immune system. Based on the B-cell stimulation in immune system, DNRS selects the most appropriate sensor nodes that send samples of the observed event, are referred to as designated nodes. The aim of the designated node selection is to meet the event estimation distortion constraint at the sink node with the minimum number of sensor nodes. DNRS enables each sensor node to distributively decide whether it is a designated node or not. In addition, to exploit the temporal correlation in the event data DNRS regulates the reporting frequency rate of each sensor node while meeting the application-specific delay bound at the sink. Based on the immune network principles, DNRS distributively selects the appropriate reporting frequencies of sensor nodes according to the congestion in the forward path and the event estimation distortion periodically calculated at the sink by Adaptive LMS Filter. Performance evaluation shows that DNRS provides the minimum number of designated nodes to reliably detect the event properties and it regulates the reporting frequency of designated nodes to exploit the temporal correlation in the event data whereby it provides the significant energy saving.