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- 저자 : Psannis, Kostas E. (검색결과 4 건)
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Algorithms for Efficient Digital Media Transmission over IoT and Cloud Networking
Stergiou, Christos,Psannis, Kostas E.,Plageras, Andreas P.,Ishibashi, Yutaka,Kim, Byung-Gyu Korea Multimedia Society 2018 The journal of multimedia information system Vol.5 No.1
In recent years, with the blooming of Internet of Things (IoT) and Cloud Computing (CC), researchers have begun to discover new methods of technological support in all areas (e.g. health, transport, education, etc.). In this paper, in order to achieve a type of network that will provide more intelligent media-data transfer new technologies were studied. Additionally, we have been studied the use of various open source tools, such as CC analyzers and simulators. These tools are useful for studying the collection, the storage, the management, the processing, and the analysis of large volumes of data. The simulation platform which have been used for our research is CloudSim, which runs on Eclipse software. Thus, after measuring the network performance with CloudSim, we also use the Cooja emulator of the Contiki OS, with the aim to confirm and access more metrics and options. More specifically, we have implemented a network topology from a small section of the script of CloudSim with Cooja, so that we can test a single network segment. The results of our experimental procedure show that there are not duplicated packets received during the procedure. This research could be a start point for better and more efficient media data transmission.
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IoT-based health and emotion care system
Andreas P. Plageras,Kostas E. Psannis 한국통신학회 2023 ICT Express Vol.9 No.1
A “Smart Healthcare-Room” has been installed in a local network. This form of network grants controlled network access to patients and tenders huge safety of their data which have been swapped at the time cure is given and the time the patient stays in the room. In order to manage the “Data Learning” approach from all the procedures and the communication of the sensors, an “Emotion Care System” has been installed. The data will be sent through the network to the IoT framework application which will notify the medical staff for the health and emotional condition of the patient.
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Optimized UAV-based data collection from MWSNs
Vasileios A. Memos,Konstantinos E. Psannis 한국통신학회 2023 ICT Express Vol.9 No.1
In this paper, we formulate an Energy Efficient (EE) deployment for Mobile Wireless Sensor Networks (MWSNs) that consists of multiple clusters of sensor nodes, one mobile sink in each of them, and an Unmanned Aerial Vehicle (UAV) for the whole MWSN. The UAV receives the collected sensed data from the mobile sinks wirelessly in order to deliver them to various IoT-based users’ devices. Experimental results show that the proposed model can achieve optimization in terms of energy consumption minimization and network lifetime enhancement.
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Saha, Avishek,Lee, Young-Woon,Hwang, Young-Sup,Psannis, Kostas E.,Kim, Byung-Gyu Springer-Verlag 2018 Personal and ubiquitous computing Vol.22 No.1
<P>Shaping video data into fast-responding transmission and high resolution output video using cost-effective video processing is desirable in many applications including Internet of Things (IoT) applications. In association with rapid development of IoT smart sensor applications, real-time processing of huge-amount of data for a video signal has become necessary leading to video compression technology. Motion estimation (ME) is necessary for improving the quality, but it has high computational complexity in video compression system. The present article, therefore, proposes a context-aware adaptive pattern-based ME algorithm for multimedia IoT platform to improve video compression. In the proposed algorithm, the motions are classified into large or small based on distortion value. Accordingly, the search pattern is chosen either small diamond search pattern (SDSP) or large diamond search pattern (LDSP) in each and every step of ME; allowing adaptive processing of large and small abstract information. Compared to conventional fast algorithms, the experimental results demonstrate up to 40 and 36% reduction in encoding time for low-delay main (LB-main) and random access main (RA-main) profiles respectively in HEVC test model 16.10 encoder with bit-rate loss of 0.071 and 0.246% for both the profiles, ensuring quality video and searching precision.</P>
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