Implementation Of Lossy Compression Method For Storage Saving On Fog Computing - Rachmat Indra Permadi; Dany Primanita Kartikasari; Fariz Andri Bakhtiar (Faculty of Engineering and Informatics, Universitas Multimedia Nusantara, 2021)
Video surveillance is a technology that uses a camera as an image receiver or input and a monitor/TV as an image producer or output to covers in certain areas. In its application, video surveillance monitors an area/place using a camera that has been installed in that place. The camera periodically records the situation that occurs in a place which is then sent to the virtual storage room via the internet network which is then displayed on the monitor/TV. However, video surveillance has a weakness, the data/video generated is so large that the storage space becomes full. Based on the experiments that have been carried out previously, the concept of fog computing is applied which is connected to a CCTV camera installed in a room for 24 hours. From these experiments, the results obtained are quite large recordings of 4 GB. To reduce the use of excessive storage space, resource management is carried out using the lossy compression method. In this study, the concept of fog computing is applied to compress video using the lossy compression method. The lossy compression methods used in this study include; H.263, H.264, and MJPEG. In this study, a video with the H.263 codec was produced which resulted in an average video size of 57,282 KB. While the H.264 and MJPEG codecs produce an average video size of 166,350 KB and 303,555 KB.