A network of sensors polled by a mobile agent (the SENMA paradigm) is used for detection purposes, with both the remote nodes and the mobile agent implementing Wald’s sequential tests. When polled, each remote node transmits its local decision (if any) to the agent, and two network/agent communication schemes are considered. One of these is designed with specific care to the network’s energy consumption. In both cases, collisions over the common communication channel are precluded by the sequentiality of the sensors’ query. The system performances in terms of average decision time, error probability, and network energy consumption are derived in exact analytical form. A tradeoff exists between the amount and the reliability of the information that the rover may collect: At optimality, the decentralized system overcomes a single supernode by orders of magnitude in terms of decision time, while only 30% of the sensors encountered by the mobile agent spend energy to reveal themselves. The remaining sensors contribute to the detection process by their silence.
Cross-Layer Design of Sequential Detectors in Sensor Networks
MARANO, Stefano;MATTA, Vincenzo;
2006-01-01
Abstract
A network of sensors polled by a mobile agent (the SENMA paradigm) is used for detection purposes, with both the remote nodes and the mobile agent implementing Wald’s sequential tests. When polled, each remote node transmits its local decision (if any) to the agent, and two network/agent communication schemes are considered. One of these is designed with specific care to the network’s energy consumption. In both cases, collisions over the common communication channel are precluded by the sequentiality of the sensors’ query. The system performances in terms of average decision time, error probability, and network energy consumption are derived in exact analytical form. A tradeoff exists between the amount and the reliability of the information that the rover may collect: At optimality, the decentralized system overcomes a single supernode by orders of magnitude in terms of decision time, while only 30% of the sensors encountered by the mobile agent spend energy to reveal themselves. The remaining sensors contribute to the detection process by their silence.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
