Sensors · 2007 · 91 citations · 20 references
ComputingComputer SystemsSystems EngineeringReal-time SystemsSchedulingSensorsFuzzy LogicReal-time Resource ManagementSensor NetworksWireless NetworksWireless Sensor NetworksAdaptive Fuzzy ControlDeadline Miss HandlingDeadline Miss RatioFuzzy ControlFuzzy Control SystemsNode SchedulingQos ManagementWireless Data Transmission
Wireless sensor/actuator networks (WSANs) are rapidly emerging, yet research on their quality‑of‑service management remains limited, making QoS a critical yet underexplored issue. This study proposes a fuzzy‑logic‑based QoS management (FLC‑QM) scheme for resource‑constrained WSANs operating in dynamic, unpredictable environments. The FLC‑QM employs a feedback‑control framework with a fuzzy logic controller at each source sensor node that adapts the sampling period to the observed deadline‑miss ratio, thereby mitigating the impact of traffic‑load fluctuations. Simulation results demonstrate that the FLC‑QM keeps the deadline‑miss ratio at a desired level, offering generality, scalability, and simplicity while providing effective QoS support for WSANs.
Wireless sensor/actuator networks (WSANs) are emerging rapidly as a newgeneration of sensor networks. Despite intensive research in wireless sensor networks(WSNs), limited work has been found in the open literature in the field of WSANs. Inparticular, quality-of-service (QoS) management in WSANs remains an important issue yetto be investigated. As an attempt in this direction, this paper develops a fuzzy logic controlbased QoS management (FLC-QM) scheme for WSANs with constrained resources and indynamic and unpredictable environments. Taking advantage of the feedback controltechnology, this scheme deals with the impact of unpredictable changes in traffic load on theQoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adaptsampling period to the deadline miss ratio associated with data transmission from the sensorto the actuator. The deadline miss ratio is maintained at a pre-determined desired level sothat the required QoS can be achieved. The FLC-QM has the advantages of generality,scalability, and simplicity. Simulation results show that the FLC-QM can provide WSANswith QoS support.
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