In the RFID system, multiple tags respond in the process of identifying multiple tags in the reader's interrogation zone, resulting in collisions. Tag collision occurs when two or more tags respond to one reader, so that the reader cannot identify any tags. These collisions make it hard for the reader to identify all tags within the interrogation zone and delays the identifying time. In some cases, the reader cannot identify any tags. The reader needs the anti-collision algorithm which can quickly identify all the tags in the interrogation zone. The proposed algorithm efficiently divides tag groups through an efficient separation to respond, preventing collisions. Moreover, the proposed algorithm identifies tags without checking all the bits in the tags. The prediction with
Wi-Fi Direct allows battery powered mobile devices to form a wireless ad hoc network. Since one member of the network called Group Owner (GO) takes the role of managing the network, the network lifetime is mainly affected by the energy efficiency of GO. Hence, Wi-Fi Direct defines power saving schemes that allow GO to save the energy by turning off its radio interface during the periods called absence periods. However, the Wi-Fi Direct specification does not specify how to set parameters (denoted by PS parameters) determining the schedule of the absence periods. In this paper, we therefore propose a novel traffic-aware power saving scheme for Wi-Fi Direct networks. In particular, the proposed scheme estimates the application-level traffic load and adaptively tunes the PS parameters according to the estimated value.
The Streganography method for digital images has to insert secret data into the image without image distortion. Side match method is that size of secret data is calculated by difference of embedded pixel value and mean value of side pixels. And the secret value is embedded into the embedded pixel. Therefore, the more secret data increases, the more image distortion increases, too. In this paper, we propose the enhanced method that calculates embedded pixel value by difference of secret value and mean value of side pixels. In proposed method, more secret data is embedded and image distortion has to decreases.
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