A cognitive scheme for gateway protection in wireless sensor network

In wireless sensor networks, sensor readings are gathered at a gateway for processing and forwarding to a remote command center. The potential closeness of the gateway to dangerous events, e.g. fires, exposes it to damage and thus risks making the network dysfunctional. Therefore, protecting the gateway by repositioning it away from safety-hazardous spots is critical for the operation of the network. However, moving the gateway too far from the sensors that report on active events would have negative effect on the network performance, e.g. throughput and energy consumption. Therefore, balancing the gateway safety and network performance goals will be necessary. In this paper, we present GRISP, a novel Gateway Relocation algorithm for Improved Safety and Performance. GRISP employs an evolutionary neural network model to assess the safety of the gateway at the various locations. The model is then used to direct the search in an area of interest for a safer position that would enhance or at least maintain an acceptable level of network performance. In addition, GRISP guides the gateway during the move by finding safe paths leading to the new location. Our experimental validation results demonstrate the effectiveness of GRISP.