Browsing by Author "Nyamtiga, Baraka William"

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Blockchain-based secure storage management with edge computing for IoT
(MDPI, 2014) Nyamtiga, Baraka William; Sicato, Jose Costa Sapalo; Rathore, Shailendra; Sung, Yunsick; Park, Jong Hyuk
As a core technology to manage decentralized systems, blockchain is gaining much popularity to deploy such applications as smart grid and healthcare systems. However, its utilization in resource-constrained mobile devices is limited due to high demands of resources and poor scalability with frequent-intensive transactions. Edge computing can be integrated to facilitate mobile devices in offloading their mining tasks to cloud resources. This integration ensures reliable access, distributed computation and untampered storage for scalable and secure transactions. It is imperative therefore that crucial issues of security, scalability and resources management be addressed to achieve successful integration. Studies have been conducted to explore suitable architectural requirements, and some researchers have applied the integration to deploy some specific applications. Despite these efforts, however, issues of anonymity, adaptability and integrity still need to be investigated further to attain a practical, secure decentralized data storage. We based our study on peer-to-peer and blockchain to achieve an Internet of Things (IoT) design supported by edge computing to acquire security and scalability levels needed for the integration. We investigated existing blockchain and associated technologies to discover solutions that address anonymity, integrity and adaptability issues for successful integration of blockchain in IoT systems. The discovered solutions were then incorporated in our conceptual design of the decentralized application prototype presented for secure storage of IoT data and transactions.
Edge-computing-assisted virtual reality computation offloading: an empirical study
(IEEE Access, 2022) Nyamtiga, Baraka William; Hermawan, Airlangga Adi; Luckyarno, Yakub Fahim; Kim, Tae-wook; Jung, Deok-young; Kwak, Jin sam; Yun, Ji-hoon
Offloading heavy virtual reality (VR) computational operations to a network edge computation entity is receiving increasing attention as a tool to wirelessly and energy efficiently provide low-end client devices with high-quality and immersive interactive VR services anytime and anywhere across the globe. In this work, we aim to provide an understanding of various characteristics of VR computation offloading through comprehensive experiments conducted using a prototype testbed for edge-assisted VR processing and streaming. First, we investigate the benefits of VR offloading in terms of computational load and power consumption reduction for a client device compared to standalone operation. Next, we measure VR traffic patterns, including frame size and data and packet rates with various settings, such as different resolution and encoding options. We also measure several performance metrics associated with the quality of experience, namely, frame rate, packet loss rate, and image quality, with various configuration settings. Then, we present latency measurement studies and investigate per-component latency with various settings. Furthermore, we report the rigorous experiments performed to study the impacts of latency and motion patterns on the black borders formed due to image reprojection and the overfilling technique used to eliminate these black borders.