In-Network Puncturing for Delay-Efficient Rate Control of Distributed Video Coding in Wireless Video Sensor Networks

Wyner-Ziv Video Coding （WZVC） is considered as a promising video coding scheme for Wireless Video Sensor Networks （WVSNs） due to its high compression efficiency and error resilience functionalities, as well as its low encoding complex- ity. To achieve a good Rate-Distortion （R-D） per- formance, the current WZVC paradi^prls usually a- dopt an end-to-end rate control scheme in which the decoder repeatedly requests the additional deco- ding data from the encoder for decoding Wyner-Ziv frames. Therefore, the waiting time of the additional decoding data is especially long in multihop WVSNs. In this paper, we propose a novel pro- gressive in-network rate control scheme for WZVC. The proposed in-network puncturing-based rate control scheme transfers the partial channel codes puncturing task from the encoder to the relay nodes. Then, the decoder can request the addition- al decoding data from the relay nodes instead of the encoder, and the total waiting time for deco- ding Wyner-Ziv frames is reduced consequently. Simulation results validate the proposed rate con- trol scheme.

Evolution Handoff Strategy for Real-Time Video Transmission over Practical Cognitive Radio Networks

The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.

Next Generation Mobile Video Networking

HWANG Jenq-Neng received his Ph.D. degree from the University of Southern California, USA. In the summer of 1989, Dr. HWANG joined the De- partment of Electrical Engineering of the Universi- ty of Washington in Seattle, USA, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research fi＇om 2003 to 2005, and from 2011-2015. He is current- ly the Associate Chair for Global Affairs and Inter- national Development in the EE Depamnent. Hehas written more than 330 journal papers, conference papers and book chapters in the areas of machine learning, muhimedia signal processing, and muhimedia system integration and networking, including an au- thored textbook on ＂Multimedia Networking： from Theory to Practice,＂ published by Cambridge University Press. Dr. HWANG has close work- ing relationship with the industry on muhimedia signal processing and nmltimedia networking.

Research on tasks schedule and data transmission of video sensor networks based on intelligent agents and intelligent algorithms

As a novel application technology,wireless video sensor networks become the current research focus,especially on target tracking and surveillance scenario.Based on multiple agents＇ technique,this article introduces a series of intelligent algorithms such as simulated annealing algorithm（SA）,genetic algorithm（GA）,and ant colony optimization algorithm（ACO） or their mixed algorithms,to resolve the optimization of tasks schedule and data transmission.This article analyzes the performance of abovementioned algorithms and verifies their feasibility associated with agents.The simulations demonstrates that the mixed algorithms based on SA and GA obtain the optimal solution to tasks schedule,and those combined with SA-ACO show advantages on multimedia sensor networks routing optimization.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.

Optimization-Based Fragmental Transmission Method for Video Data in Opportunistic Networks

Multimedia data have become popularly transmitted content in opportunistic networks. A large amount of video data easily leads to a low delivery ratio. Breaking up these big data into small pieces or fragments is a reasonable option. The size of the fragments is critical to transmission efficiency and should be adaptable to the communication capability of a network. We propose a novel communication capacity calculation model of opportunistic network based on the classical random direction mobile model, define the restrain facts model of overhead, and present an optimal fragment size algorithm. We also design and evaluate the methods and algorithms with video data fragments disseminated in a simulated environment. Experiment results verified the effectiveness of the network capability and the optimal fragment methods.

Real-time ultra-wideband video streaming in long-reach passive optical networks with wireless radiation in the 10 and 60 GHz bands

Real-time video streaming using ultra-wideband(UWB) technology is experimentally demonstrated along long-reach passive optical networks(LR-PONs) with different wired and wireless reaches. Experimental tests using external and direct modulation with UWB wireless radiation in the 10- and 60-GHz bands are performed. An ultra-bendable fiber is also considered for a last-mile distribution. The video quality at the output of the optical fiber infrastructure of the LR-PON is assessed using the error vector magnitude(EVM), and the link quality indicator(LQI) is used as a figure of merit after wireless radiation. An EVM below –17 dB is achieved for both externally and directly modulated LR-PONs comprising up to 125 km of optical fiber. EVM improvement is observed for longer LR-PONs when directly modulated lasers(DMLs) are used because of the amplitude gain provided by the combined effect of dispersion and DML's chirp. Compared with optical back-to-back operation, the LQI level degrades to the maximum around 20% for LR-PONs ranging between 75 and 125 km of fiber reach and with a wireless coverage of 2 m in the 10-GHz UWB band. The same level of LQI degradation is observed using the 60-GHz UWB band with a LR-PON integrating 101 km of access network, a last-mile distribution using ultra-bendable fiber, and a 5.2-m wireless link.

Edge Video CDN： A Wi-Fi Content Hotspot Solution

The emergence of smart edge-network content item hotspots, which are equipped with huge storage space （e.g., several GBs）, opens up the opportunity to study the possibility of delivering videos at the edge network. Different from both the conventional content item delivery network （CDN） and the peer-to-peer （P2P） scheme, this new delivery paradigm, namely edge video CDN, requires up to millions of edge hotspots located at users＇ homes/offices to be coordinately managed to serve mobile video content item. Specifically, two challenges are involved in building edge video CDN, including how edge content item hotspots should be organized to serve users, and how content items should be replicated to them at different locations to serve users. To address these challenges, we propose our data-driven design as follows. First, we formulate an edge region partition problem to jointly maximize the quality experienced by users and minimize the replication cost, which is NP-hard in nature, and we design a Voronoi-like partition algorithm to generate optimal service cells. Second, to replicate content items to edge-network content item hotspots, we propose an edge request prediction based replication strategy, which carries out the replication in a server peak offioading manner. We implement our design and use trace-driven experiments to verify its effectiveness. Compared with conventional centralized CDN and popularity-based replication, our design can significantly improve users＇ quality of experience, in terms of users＇ perceived bandwidth and latency, up to 40%.

Network video quality assessment based on fuzzy inference system

The objective assessment method of network video quality is a challenge, because the video quality will be distorted by various factors, including transmission and compression. In order to improve the objective method, an objective assessment method based on fuzzy inference system of Mamdani is proposed. Firstly, six quality parameters are introduced. All the quality parameters are inputted to fuzzy logic controller system. Secondly, the outputs are used as next inputs and inferred by another fuzzy logic controller system to obtain the objective quality of network video. Lastly, the performance of proposed method is validated on four videos with different network environment. Meanwhile this method is compared with other methods. The experimental results show that the proposed method can improve the similarity between subjective and objective assessment.

Cloud-based video communication and networking: an architectural overview

Cloud-based video communication and networking has emerged as a promising new research paradigm to significantly improve the quality of experience for video consumers.An architectural overview of this promising research area was presented.This overview with an end-to-end partition of the cloud-based video system into major blocks with respect to their locations from the center of the cloud to the edge of the cloud was started.Following this partition,existing research efforts on how the principles of cloud computing can provide unprecedented support to 1)video servers,2)content delivery networks,and 3)edge networks within the global cloud video ecosystems were examined.Moreover,a case study was exemplfied on an edge cloud assisted HTTP adaptive video streaming to demonstrate the effectiveness of cloud computing support.Finally,by envisioning a list of future research topics in cloud-based video communication and networking a coclusion is made.