SearcharxivSearch

arXiv subjects

Chih-Hang Wang

Publications and source records attributed to Chih-Hang Wang.

5 recordsLinked to original sources

Cybersickness-aware Tile-based Adaptive 360° Video Streaming

In contrast to traditional videos, the imaging in virtual reality (VR) is 360°, and it consumes larger bandwidth to transmit video contents. To reduce bandwidth consumption, tile-based streaming has been proposed to deliver the focused part of the video, instead of the whole one. On the other hand, the techniques to alleviate cybersickness, which is akin to motion sickness and happens when using digital displays, have not been jointly explored with the tile selection in VR. In this paper, we investigate Tile Selection with Cybersickness Control (TSCC) in an adaptive 360° video streaming system with cybersickness alleviation. We propose an m-competitive online algorithm with Cybersickness Indicator (CI) and Video Loss Indicator (VLI) to evaluate instant cybersickness and the total loss of video quality. Moreover, the algorithm exploits Sickness Migration Indicator (SMI) to evaluate the cybersickness accumulated over time and the increase of optical flow to improve the tile quality assignment. Simulations with a real network dataset show that our algorithm outperforms the baselines regarding video quality and cybersickness accumulation.

cs.NI

Scalable Rate Control for Traffic Engineering with Aggregated Flows in Software Defined Networks

To increase the scalability of Software Defined Networks (SDNs), flow aggregation schemes have been proposed to merge multiple mouse flows into an elephant aggregated flow for traffic engineering. In this paper, we first notice that the user bit-rate requirements of mouse flows are no longer guaranteed in the aggregated flow since the flow rate decided by the TCP allocation is usually different from the desired bit-rate of each user. To address the above issue, we present a novel architecture, named Flexible Flow And Rate Management (F$^2$ARM), to control the rates of only a few flows in order to increase the scalability of SDN, while leaving the uncontrolled flows managed by TCP. We formulate a new optimization problem, named Scalable Per-Flow Rate Control for SDN (SPFRCS), which aims to find a minimum subset of flows as controlled flows but ensure that the flow rates of all uncontrolled flows can still satisfy the minimum required rates by TCP. We prove that SPFRCS is NP-hard and design an efficient algorithm, named Joint Flow Selection and Rate Determination (JFSRD). Simulation results based on real networks manifest that JFSRD performs nearly optimally in small-scale networks, and the number of controlled flows can be effectively reduced by 50% in real networks.

cs.NI

Cross-Layer Design of Influence Maximization in Mobile Social Networks

Most prior algorithms for influence maximization focused are designed for Online Social Networks (OSNs) and require centralized computation. Directly deploying the above algorithms in distributed Mobile Social Networks (MSNs) will overwhelm the networks due to an enormous number of messages required for seed selection. In this paper, therefore, we design a new cross-layer strategy to jointly examine MSN and mobile ad hoc networks (MANETs) to facilitate efficient seed selection, by extracting a subset of nodes as agents to represent nearby friends during the distributed computation. Specifically, we formulate a new optimization problem, named Agent Selection Problem (ASP), to minimize the message overhead transmitted in MANET. We prove that ASP is NP-Hard and design an effectively distributed algorithm. Simulation results in real and synthetic datasets manifest that the message overhead can be significantly reduced compared with the existing approaches.

cs.SI

Scheduling for Multi-Camera Surveillance in LTE Networks

Wireless surveillance in cellular networks has become increasingly important, while commercial LTE surveillance cameras are also available nowadays. Nevertheless, most scheduling algorithms in the literature are throughput, fairness, or profit-based approaches, which are not suitable for wireless surveillance. In this paper, therefore, we explore the resource allocation problem for a multi-camera surveillance system in 3GPP Long Term Evolution (LTE) uplink (UL) networks. We minimize the number of allocated resource blocks (RBs) while guaranteeing the coverage requirement for surveillance systems in LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an Integer Linear Programming formulation for general cases to find the optimal solution. Moreover, we present a baseline algorithm and devise an approximation algorithm to solve the problem. Simulation results based on a real surveillance map and synthetic datasets manifest that the number of allocated RBs can be effectively reduced compared to the existing approach for LTE networks.

cs.NI

Uplink Scheduling for LTE Video Surveillance Systems

Due to the proliferation of applications for the Internet of Things, an increasing number of machine to machine (M2M) devices are being deployed. In particular, one of the M2M applications, video surveillance, has been widely discussed. Long Term Evolution (LTE), which can provide a high rate of data transmission and wide range of coverage, is a promising standard to serve as an M2M video surveillance system. In this paper, we studied a performance maximization problem in an LTE video surveillance system. Given a set of objects and a set of cameras, each camera has its own performance grade and its own coverage. The goal is to maximize the performance of the system by allocating limited resources to cameras while all objects should be monitored by the selected cameras. We propose a heuristic method to select the cameras and allocate resources to them to solve the problem. Moreover, to reduce the load of the LTE system, a dynamic adjustment method is also proposed.

cs.NI