In this paper, we propose a resilient and fast block transmission system for Hyperledger Fabric in multi-cloud environments. The goal of the proposed system is to improve the scalability, transaction throughput, and resilience of Hyperledger Fabric by minimizing the block synchronization time among nodes. To achieve this goal, the proposed system is designed to deliver blocks quickly and reliably to all the participating nodes in time-varying multi-cloud environments. The proposed system includes the delay estimating process with O(N) control message overhead over the P2P network, the effective bandwidth estimating process for block transmission, the Gaussian Mixture Model-based clustering and cluster leader selecting process, and hybrid P2P multicast tree constructing process. In addition, a control message format and delivery process are proposed to efficiently provide hybrid P2P multicast tree and neighbor nodes information to all the participating nodes. And we propose a pull-based local block loss recovery process that can receive lost blocks from multi-node without complicated scheduling using a rateless code. The proposed system is fully implemented by using well-known open sources (e.g., Hyperledger Fabric, Docker, Containernet, and Mininet) and Go/C/Python. Experiment results show that the proposed system can reduce the maximum block arriving time among all the participating nodes by approximately 50%~95% compared to the existing algorithms. This improves not only blockchain transaction per second, but also resilience to various network-layer vulnerabilities and attacks that may occur when the block propagation delay increases.

This work presents a novel HTTP adaptive streaming system to maximize overall video streaming service quality of all the clients over SDN-enabled Wi-Fi APs. To archive the goal, the proposed system employs multipath technology to overcome the limitation of a Wi-Fi AP, and SDN technology to effectively harmonize multiple Wi-Fi APs. During the streaming services, SDN controller periodically monitors the traffic information collected from the APs, and then determines video bitrate and segment transmission schedule based on this information. The proposed system is fully implemented in real Wi-Fi network environments.

Summary This paper proposes a novel congestion‐aware HTTP adaptive streaming (HAS) system to improve video quality of clients over software‐defined network (SDN)–enabled Wi‐Fi network. The proposed system employs SDN technology to efficiently control the network resources and video quality over the competing Wi‐Fi network. In the proposed system, an SDN‐enabled access point (AP) can monitor the streaming status of clients, such as the buffered playback time and information of requested segments. An SDN controller collects not only the streaming status of clients but also the Wi‐Fi network conditions from the AP using OpenFlow. Additionally, when a congestion is going to occur, it determines the segment bitrate of each client to provide seamless and high‐quality streaming services. The proposed system is fully implemented using open‐source programs, such as ONOS and hostapd, and is examined in a real Wi‐Fi network. The experimental results verify that the proposed system can provide seamless and high‐quality HAS services for the clients compared with existing systems.

In this work, we propose an energy-efficient HTTP adaptive streaming with hybrid TCP/UDP over heterogeneous wireless networks. Unlike the existing HTTP adaptive streaming system, the proposed system can utilize both TCP and UDP to overcome the performance degradation problem of TCP and improve the energy efficiency. The proposed system handles the types of transport protocols, requested video quality, and amount of data received through each wireless network as control variables based on network conditions, buffer occupancy, and energy condition of mobile terminal. When UDP is selected, the proposed system employs Raptor code as a forward error correction scheme to support a reliable data delivery, and adaptively chooses the proper Raptor code parameters such as symbol size and amount of redundant data, and requests redundant data from the server to reduce the overhead. The proposed system is fully implemented in an Android-based mobile terminal and tested in real WiFi and LTE networks. The experiment results show that the proposed system can achieve good energy efficiency while providing a seamless high-quality HTTP adaptive streaming service.

This paper presents a reliable and energy-efficient hybrid screen mirroring multicast system for sharing high-quality real-time multimedia service with adjacent mobile devices over WiFi network. The proposed system employs overhearing-based multicast transmission scheme with Raptor codes and NACK-based retransmission to overcome well-known WiFi multicast problems such as low transmission rate and high packet loss rate. Furthermore, to save energy on mobile devices, the proposed system not only shapes the screen mirroring traffic, but also determines the target sink device and Raptor encoding parameters such as the number of source symbols, symbol size, and code rate while considering the energy consumption and processing delay of the Raptor encoding and decoding processes. The proposed system is fully implemented in Linux-based single board computers and examined in real WiFi network. Compared to existing systems, the proposed system can achieve good energy efficiency while providing a high-quality screen mirroring service.

In this work, we propose a Raptor codes-based energy-efficient screen mirroring system. To mitigate the video quality degradation caused by wireless network error, the proposed system employs systematic Raptor codes as forward error correction scheme. For energy saving at the mobile device, the proposed system not only shapes screen mirroring traffic, but also determines the Raptor encoding parameters including the symbol size, the number of source symbols, and the code rate. The proposed system is fully implemented on single board computers, and examined over real wireless network.

In this work, we propose an energy-efficient HTTP adaptive streaming for high-quality video over heterogeneous networks (HetNets). To support high-quality video and overcome the limitations of a single network, the proposed system downloads the video segments by concurrently using the HetNets. In the proposed system, the segment bitrate, number of requested segments, network sleep time, and size of requested data through each wireless network are determined adaptively to provide seamless high-quality video streaming in an energy and cost efficient way. The proposed system is fully implemented in an Android-based mobile device and tested in an actual wireless network environments.

In this work, we propose a Raptor codes-based energy-efficient multipath multimedia transport protocol over heterogeneous wireless networks (HetNets) in order to provide seamless high-quality video streaming service in an energy efficient way. In the proposed protocol, systematic Raptor codes are employed to mitigate the video quality degradation. For energy saving, the proposed protocol not only shapes a video stream into bursts, but also determines the Raptor encoding parameters including code rate, symbol size, and the number of source symbols for energy saving. The proposed protocol is fully implemented on an Android-based smartphone, and examined over real HetNets.

This work presents a multipath multimedia transport protocol (MPMTP), which exploits path diversity over heterogeneous wireless networks. The goal of MPMTP is to provide a seamless high-quality video streaming service by using multiple wireless networks simultaneously. In MPMTP, systematic Raptor codes are adopted to mitigate video quality degradation caused by wireless channel errors, as well as to alleviate a head-of-line blocking problem in multipath environments, and their encoding parameters such as code rate, symbol size, and the number of source symbols are determined on the fly by considering the wireless channel state, Raptor encoding and decoding complexity, and receiver video buffer occupancy. Furthermore, MPMTP performs packet scheduling considering not only wireless network conditions but also packet payload characteristics for smooth video playback. The proposed MPMTP is fully implemented in a Linux kernel and examined over real wireless network environments.

This paper presents a multipath multimedia transport protocol (MPMTP), which exploits path diversity over heterogeneous wireless networks. The goal of MPMTP is to provide a seamless high-quality video streaming service by using multiple wireless networks simultaneously. In MPMTP, systematic Raptor codes are adopted to mitigate video quality degradation caused by wireless channel errors as well as to alleviate a head-of-line blocking problem in multipath environments, and their encoding parameters such as code rate, symbol size, and the number of source symbols are determined on the fly by considering the wireless channel state, Raptor encoding and decoding complexity, and receiver buffer occupancy. Furthermore, MPMTP performs packet scheduling considering not only wireless network conditions but also packet payload characteristics for smooth video playback. The proposed MPMTP is fully implemented in a Linux kernel and examined over real wireless network environments.

This paper presents a seamless high-quality HTTP adaptive streaming algorithm that considers wireless network conditions and the energy consumption of a mobile device with networking cost constraints over heterogeneous wireless networks. In the proposed algorithm, the requested video segments are concurrently delivered through multiple wireless networks to overcome the limitations of a single network. The segment quality level, number of requested segments, network inactive interval, and amount of requested data through each wireless network are determined adaptively in order to provide a seamless high-quality video with low energy consumption and networking cost constraints at the mobile device. The proposed algorithm is fully implemented in an Android-based mobile device and tested in an actual wireless network environment.

Recently, the mobile cloud computing received much attention since it can provide various and powerful services for the mobile user. The service discovery technology in mobile cloud computing is very important to efficiently provide the mobile services. In this paper, we proposed a novel preference-aware skyline service discovery system in the mobile cloud system. The objective of our system is to discover preferable services in the mobile cloud system. Our proposed mobile cloud system is composed of zone-based overlay network. In the overlay network, querying user generates the query with user preference extracted by a Singular Value Decomposition method from the user's service access history. The generated query is sent to the mobile cloud system, and then the query is handled by the distributed skyline query processing mechanism to discover user preferable services with low networking communication cost in the mobile cloud system. We conduct experiments to evaluate the performance of our proposed system.