TY - GEN
T1 - Self-adaptive resource allocation for event monitoring with uncertainty in sensor networks
AU - Hu, Nan
AU - La Porta, Thomas
AU - Bartolini, Novella
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/28
Y1 - 2015/12/28
N2 - Event monitoring is an important application of sensor networks. Multiple parties, with different surveillance targets, can share the same network, with limited sensing resources, to monitor their events of interest simultaneously. Such a system achieves profit by allocating sensing resources to missions to collect event related information (e.g., Videos, photos, electromagnetic signals). We address the problem of dynamically assigning resources to missions so as to achieve maximum profit with uncertainty in event occurrence. We consider time-varying resource demands and profits, and multiple concurrent surveillance missions. We model each mission as a sequence of monitoring attempts, each being allocated with a certain amount of resources, on a specific set of events that occurs as a Markov process. We propose a Self-Adaptive Resource Allocation algorithm (SARA) to adaptively and efficiently allocate resources according to the results of previous observations. By means of simulations we compare SARA to previous solutions and show SARA's potential in finding higher profit in both static and dynamic scenarios.
AB - Event monitoring is an important application of sensor networks. Multiple parties, with different surveillance targets, can share the same network, with limited sensing resources, to monitor their events of interest simultaneously. Such a system achieves profit by allocating sensing resources to missions to collect event related information (e.g., Videos, photos, electromagnetic signals). We address the problem of dynamically assigning resources to missions so as to achieve maximum profit with uncertainty in event occurrence. We consider time-varying resource demands and profits, and multiple concurrent surveillance missions. We model each mission as a sequence of monitoring attempts, each being allocated with a certain amount of resources, on a specific set of events that occurs as a Markov process. We propose a Self-Adaptive Resource Allocation algorithm (SARA) to adaptively and efficiently allocate resources according to the results of previous observations. By means of simulations we compare SARA to previous solutions and show SARA's potential in finding higher profit in both static and dynamic scenarios.
UR - http://www.scopus.com/inward/record.url?scp=84964608097&partnerID=8YFLogxK
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U2 - 10.1109/MASS.2015.72
DO - 10.1109/MASS.2015.72
M3 - Conference contribution
AN - SCOPUS:84964608097
T3 - Proceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015
SP - 370
EP - 378
BT - Proceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015
Y2 - 19 October 2015 through 22 October 2015
ER -