63 Ultima Computing : Jurnal Sistem Komputer, Vol. 13, No. 2 | December 2021 ISSN 2355-3286 Implementation of Lossy Compression Method for Storage Saving on Fog Computing Rachmat Indra Permadi 1 , Dany Primanita Kartikasari 2 , Fariz Andri Bakhtiar 3 Fakultas Ilmu Komputer, Universitas Brawijaya Malang, Indonesia 1 ripermadi@student.ub.ac.id, 2 dany.jalin@ub.ac.id, 3 fariz@ub.ac.id Accepted 03 August 2021 Approved 05 September 2021 Abstract— Video surveillance is a technology that uses a camera as an image receiver and a monitor or Television (TV) as an image producer to covers certain areas. In the application, video surveillance was installed for monitoring the area using a camera. The camera will record the situation that occurs periodically, then send it to the virtual storage room via internet network and then display it on a monitor/TV. However, video surveillance has weaknesses in significant data/video output. Based on that problem, the concept of fog computing is applied, using a Cloud Circuit Television (CCTV) camera to monitoring for 24 hours. However, these experiments have a large data output until it reaches 4 GB storage. To reduce the data storage, this study uses a lossy compression method. The concept of fog computing is applied to compress video using the lossy compression method. The lossy compression codec used in this study is; H.263, H.264, and MJPEG (Motion Joint Expert Group) format. The result of a video with the H.263 codec has an excellent efficiency value than other codecs, which is 66%. Index Terms— Video Surveillance, Fog Computing, Lossy Compression I. INTRODUCTION Cloud Computing is a service that combines computer technology with virtual internet-based development [1]. Cloud computing provides services to users for access data or applications remotely and store data without using traditional hardware. However, in its application with IoT, there are weaknesses, namely bandwidth limitations to process data transfers [2]. Fog Computing is a further development of Cloud Computing is a concept in the realm of Distributed Computing, which allows services from the cloud to be pulled to the network edge that functions for distance and latency from end-users to the cloud [3]. By combining these two technologies, all computing can be performed at the network edge (fog) for the distance and latency that must be performed on the cloud. However, there are several weaknesses in fog computing, one of which lies in the storage space. The storage space contained in fog computing devices is very limited, but the limited storage capacity is used to store large videos. 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. The video recorded on the CCTV camera will go to the fog point to check using a motion detection algorithm, checking is carried out to determine whether the object is in the room or not. From these experiments, the results obtained are quite large recordings of 4 GB. The large size of the video used for computing the checking process can fill the storage space of the fog node. To overcome this problem, a lossy compression method is applied. The lossy compression method can save storage space because the burden of large video sizes is reduced by reducing the size of the video. By applying the lossy compression method to the fog node, this study makes storage efficiency in the fog node the primary goal. This research uses a lossy compression codec H.263, H.264, and MJPEG. The result of a video with the lossy compression method gets efficient results after the system performs the compression process on the video before the data is saved to the cloud. II. LITERATURE REVIEW A. Cloud Computing Cloud computing is a parallel and distributed computing system of interconnected computers with a single server to provide users based on Service Level Agreement (SLA) [1]. Cloud computing provides to users to be able for access the applications, data and do storage remotely without use a traditional hardware using third-party servers or known as cloud storage. Cloud computing has two main architecture is Front- End and Back-End. The architecture is connected to each other via the internet. The Front-End can be a sensor, client, or any application that uses a cloud service. Back-End is the cloud system which consists of computer, servers and data storage [4].