Streaming Sessions Research Articles

Energy Consumption Analysis of Edge Orchestrated Virtualized Wireless Multimedia Sensor Networks

Virtualization enabled by container-based technologies is a recently emerging concept in the integration of Internet of Things (IoT) and cloud computing. Due of their lightweight nature, container-based virtualization tools improve manageability of cloud-based IoT solutions by making it possible to update application software on the fly. Although different studies have demonstrated the feasibility of efficiently running container-based virtualization on low-power IoT nodes, the implication of doing so on battery-powered nodes has been overlooked. In this paper, we investigate how much energy overhead is generated by Docker-based virtualization on battery powered camera sensor nodes. In our scenario, camera nodes are most of the time in “power off” state to save energy. They are switched on for streaming video only when activity is detected by motion sensor nodes. By means of empirical measurement and subsequent analysis, we found that starting and closing of containers in the Docker platform adds-up roughly 13 percent power consumption overhead during the boot-up and shutdown of the camera nodes. Furthermore, the fixed overhead occurring from boot-up and shutdown procedures become negligible with longer video stream sessions.

Post-Streaming Rate Analysis—A New Approach to Mobile Video Streaming with Predictable Performance

Fueled by the growth of 3G/4G mobile networks, mobile video streaming has become one of the main applications in the mobile Internet. Due to mobile networks’ inherent bandwidth fluctuations, the industry as well as researchers have developed many adaptive streaming algorithms to compensate for such fluctuations to improve streaming performance. Given the wide range of network settings, it is not surprising that existing algorithms can and do perform differently across different network and system conditions. This work breaks away from the conventional one-size-fits-all approach to designing adaptive streaming systems by developing a new framework called PSRA where past throughput trace data - captured as a by-product of streaming, are analyzed to construct a statistical model to automatically tune the adaptation algorithm for future streaming sessions according to the underlying network and system configurations. Compared to existing approaches, the PSRA-optimized streaming algorithm can achieve predictable, consistent, and controllable streaming performance across a wide-range of network and system configurations. Moreover, PSRA offers to service provider a new tool to precisely control the tradeoff between video quality and streaming performance. Results from extensive trace-driven simulations as well as experiments verified PSRA's performance under real-world mobile network and system configurations.

Public Event: Stream Sessions

The first Stream Session will be on Wednesday, March 29 from 2:00-4:00 pm at the conference room at the Burnaby Campus (8652). Stream Sessions are intended to be a colloquium where graduate students are invited to present their ideas to fellow students and faculty of the School of Communication. Topics for presentation can range from working papers to discussions of comprehensive or thesis readings to new theories and ideas still in the process of being formed. It’s an opportunity to workshop ideas among peers in a productive yet low-stakes environment while also receiving valuable feedback from students and faculty.
 For more details, please see the attached PDF. 
 The following students will be presenting work for the first Stream Sessions. Each presentation will run 10-15 minutes with 15 minutes for discussion afterward.
 Stream Sessions - Wednesday March 29 2:00-4:00 pm SFU Burnaby Room 8652
 2:00-2:30 - Alberto Lusoli (PhD Student) - “From Social to Critical Constructivism. An Exploration of the Main Schools of Thought in the Field of Science, Technology and Society"
 2:30-3:00 - Geneva Lam (Master’s Student) - “Explaining Ethnic Media through the Lens of Language, Identity and Culture “
 3:00-3:30 - Shawna-Kay Thomas (Double-Degree Master’s Student) - “‘Portia Loves the Poor’ - Portia Simpson Miller and Affective Politics in Jamaica”
 3:30-4:00 - Peter Zuurbier and Darren Fleet (PhD Students) “It Just Feels Right: Affective Veridiction in the Contemporary West.”
 Faculty Referee: Frédérik Lesage
 There will be light refreshments served. Following the event, we encourage everyone attending and participating to make their way to the Highland Pub for drinks and continued conversation.

WiFlix: Adaptive Video Streaming in Massive MU-MIMO Wireless Networks

We consider the problem of simultaneous on-demand streaming of stored video to multiple users in a multicell wireless network where multiple unicast streaming sessions are run in parallel and share the same frequency band. Each streaming session is formed by the sequential transmission of video “chunks,” such that each chunk arrives into the corresponding user playback buffer within its playback deadline. We formulate the problem as a network utility maximization (NUM) where the objective is to fairly maximize users’ video streaming quality of experience (QoE) and then derive an iterative control policy using Lyapunov optimization, which solves the NUM problem up to any level of accuracy and yields an online protocol with control actions at every iteration decomposing into two layers interconnected by the users’ request queues : 1) a video streaming adaptation layer reminiscent of dynamic adaptive streaming over HTTP (DASH), implemented at each user node; and 2) a transmission scheduling layer where a max-weight scheduler is implemented at each base station. The proposed chunk request scheme is a pull strategy where every user opportunistically requests video chunks from the neighboring base stations and dynamically adapts the quality of its requests based on the current size of the request queue. For the transmission scheduling component, we first describe the general max-weight scheduler and then particularize it to a wireless network where the base stations have multiuser multiple-input multiple-output (MU-MIMO) beamforming capabilities. We exploit the channel hardening effect of large-dimensional MIMO channels (massive MIMO) and devise a low complexity user selection scheme to solve the underlying combinatorial problem of selecting user subsets for downlink beamforming, which can be easily implemented and run independently at each base station. Furthermore, through simulations, we show that deploying MU-MIMO significantly improves video streaming performance and also that the proposed cross-layer approach is able to serve users more fairly than a baseline scheme representative of current systems running independently designed protocol layers.

A Control-Theoretic Approach to Adaptive Video Streaming in Dense Wireless Networks

Recently, the way people consume video content has been undergoing a dramatic change. Plain TV sets, that have been the center of home entertainment for a long time, are losing grounds to Hybrid TV's, PC's, game consoles, and, more recently, mobile devices such as tablets and smartphones. The new predominant paradigm is: watch what I want, when I want, and where I want. The challenges of this shift are manifold. On the one hand, broadcast technologies such as DVB-T/C/S need to be extended or replaced by mechanisms supporting asynchronous viewing, such as IPTV and video streaming over best-effort networks, while remaining scalable to millions of users. On the other hand, the dramatic increase of wireless data traffic begins to stretch the capabilities of the existing wireless infrastructure to its limits. Finally, there is a challenge to video streaming technologies to cope with a high heterogeneity of end-user devices and dynamically changing network conditions, in particular in wireless and mobile networks. In the present work, our goal is to design an efficient system that supports a high number of unicast streaming sessions in a dense wireless access network. We address this goal by jointly considering the two problems of wireless transmission scheduling and video quality adaptation, using techniques inspired by the robustness and simplicity of Proportional-Integral-Derivative (PID) controllers. We show that the control-theoretic approach allows to efficiently utilize available wireless resources, providing high Quality of Experience (QoE) to a large number of users.

Optimal Selection of Adaptive Streaming Representations

Adaptive streaming addresses the increasing and heterogeneous demand of multimedia content over the Internet by offering several encoded versions for each video sequence. Each version (or representation) is characterized by a resolution and a bit rate, and it is aimed at a specific set of users, like TV or mobile phone clients. While most existing works on adaptive streaming deal with effective playout-buffer control strategies on the client side, in this article we take a providers' perspective and propose solutions to improve user satisfaction by optimizing the set of available representations. We formulate an integer linear program that maximizes users' average satisfaction, taking into account network dynamics, type of video content, and user population characteristics. The solution of the optimization is a set of encoding parameters corresponding to the representations set that maximizes user satisfaction. We evaluate this solution by simulating multiple adaptive streaming sessions characterized by realistic network statistics, showing that the proposed solution outperforms commonly used vendor recommendations, in terms of user satisfaction but also in terms of fairness and outage probability. The simulation results show that video content information as well as network constraints and users' statistics play a crucial role in selecting proper encoding parameters to provide fairness among users and to reduce network resource usage. We finally propose a few theoretical guidelines that can be used, in realistic settings, to choose the encoding parameters based on the user characteristics, the network capacity and the type of video content.

Understanding the impact of network dynamics on mobile video user engagement

Mobile network operators have a significant interest in the performance of streaming video on their networks because network dynamics directly influence the Quality of Experience (QoE). However, unlike video service providers, network operators are not privy to the client- or server-side logs typically used to measure key video performance metrics, such as user engagement. To address this limitation, this paper presents the first large-scale study characterizing the impact of cellular network performance on mobile video user engagement from the perspective of a network operator. Our study on a month-long anonymized data set from a major cellular network makes two main contributions. First, we quantify the effect that 31 different network factors have on user behavior in mobile video. Our results provide network operators direct guidance on how to improve user engagement --- for example, improving mean signal-to-interference ratio by 1 dB reduces the likelihood of video abandonment by 2%. Second, we model the complex relationships between these factors and video abandonment, enabling operators to monitor mobile video user engagement in real-time. Our model can predict whether a user completely downloads a video with more than 87% accuracy by observing only the initial 10 seconds of video streaming sessions. Moreover, our model achieves significantly better accuracy than prior models that require client- or server-side logs, yet we only use standard radio network statistics and/or TCP/IP headers available to network operators.

Optimizing content placement in a peer-assisted VoD architecture

Recently, a new peer-assisted architecture to build content delivery systems has been presented. This architecture is based on the use of the storage capacity of end-users’ set-top boxes (STBs), connected in a peer-to-peer (P2P) manner in order to help the content servers in the delivery process. In these systems, the contents are usually split into a set of smaller pieces, called sub-streams, which are randomly injected at the STBs. The present paper is focused on Video on Demand (VoD) streaming and it is assumed that the STB-based content delivery system is deployed over the global Internet, where the clients are distributed over different ISP networks. In this scenario, three different strategies are studied for increasing the percentage of data uploaded by peers, in order to offload the content servers as much as possible. First of all, a new mechanism is presented which determines which sub-stream has to be placed at which STB by a Non-Linear Programming (NLP) formulation. A different strategy for reducing the content server load is to take advantage of the available bandwidth in the different ISP networks. In this sense, two new mechanisms for forwarding the VoD requests to different ISP networks are presented. Finally, the present paper also shows that in some situations the available uplink bandwidth is associated with STBs that do not have the required sub-streams. Regarding this concern, a new mechanism has been designed that dynamically re-allocates some streams, which are being transmitted from specific STBs, to different STBs, in order to find the necessary resources to start new streaming sessions.

Design and analysis of a peer-assisted VOD provisioning system for managed networks

With the rise of VOD (Video-on-Demand) services provisioning as a successful service on the Internet and managed networks, we are witnessing a drive towards cost-efficiency and economies of scale. Many broadband operators around the world are experimenting with P2P (Peer-to-Peer) systems centered on STBs (Set-Top-Boxes) to increase the competitiveness of their VOD services offering. By leveraging the storage and uplink bandwidth capacities available at a certain number of STBs operated by the broadband operator, the savings in terms of backend streaming capacities will represent sizable and decisive gains in cost. In these systems, video contents are usually fragmented into a number of complementary content fragments, called sub-streams, which are randomly injected in the network of STBs, and the VOD service is essentially provisioned through multisource streaming sessions from neighboring STBs to the requesting STB. One of the main challenges in such peer-assisted streaming systems remains the maximization of the utilization of STB resources utility for a given content popularity pattern. In this paper, we specifically focus on the content injection strategy and how the different content fragments should be dispatched in the network to achieve the highest performance in the VOD services provisioning epoch. We demonstrate that the random injection strategy is not appropriate for maximizing the number of simultaneous VOD streaming sessions in the network. Our objective is to first gain a better understanding of the factors driving P2P-based VOD streaming systems and provide guidelines to better operate such systems and ultimately give service operators the tools to achieve different performance objectives and/or fit specific network configurations. Further, we propose a new content dispatching strategy that maximizes the number of served VOD sessions by balancing the streaming load among the different STBs. Finally, we propose a complementary streaming resources reprovisioning mechanism that acts in real-time to reprovision the resources for serving VOD sessions to new STBs and to release trapped resources for new incoming VOD service requests.

Preface: Special issue SAGO08

The international workshop, Stochastic and Applied Global Optimization, was held during 19–22 July 2008. What made this workshop different to those previously held in global optimization, was the opportunities offered to the participants to view the game and natural beauty of South Africa alongside discussing research. The workshop was organized in the Skukuza Camp of the South African national game reserve, the Kruger National Park. The Skukuza Camp is located in the southern part of the Kruger National Park and is well known for its lion sightings. The presentations were scheduled in single stream sessions in such a way that there was ample time for the participants to view game in the mornings and late evenings. The participants were treated to the rare sight of each of the ‘big five’ (Lion, Rhinoceros, Buffalo, Elephant and Leopard). Round trips from Johannesburg to the Skukuza Camp were organized for the all participants to see the spectacular scenic beauties of South Africa. A total of 46 scholars from twelve countries attended the workshop. The participants were invited to submit their contribution to a special issue. Papers dealing with all aspects of global optimization, ranging from theories to applications, were submitted. The usual referee process, where three experts per paper were invited to referee, led to the final acceptance of six papers. Papers in both stochastic and heuristic methods for global optimization, in combinatorial optimization, in scheduling, and application areas such as location analysis are representative of the special issue. We are grateful to Professor Panos Pardalos, the Editor-in-chief of the Journal of Global Optimization, for granting this special issue and for his encouragement and guidance during the preparations and publication of the issue.

Bandwidth-effective streaming of educational medical videos

Real-time delivery of medical videos requires high level of quality of service that shows no tolerance to loss and delay. In this study, how content-adaptive streaming can aid to maintain high-quality streaming sessions is investigated. The proposed strategy allocates a specific amount of bandwidth to streaming sessions and takes advantage of the general structure of instructional medical videos to decrease bandwidth consumption below this limit. The main contribution of the proposed mechanism is that it eliminates the need for rate adaptation which is common in traditional streaming by employing a proper bandwidth management scheme that enables constant bandwidth consumption below the allocated capacity. A streaming system based on the proposed mechanism has been implemented and its performance has been tested via emulation. Experimental results indicate that content-adaptive streaming successfully eliminates the need of rate adaptation during the delivery of critical data and hence preserves viewers' satisfaction.

Layer 5 Session Handoff: Mobility Management for Video Streaming Sessions among Heterogeneous Networks and Devices

In the past decade, mature video processing and Internet technologies have made video services over IP feasible and increasingly popular, e.g., video-on-demand (VoD) and IPTV. Considering mobile life over heterogeneous networks, a user can exploit any device to enjoy/share pictures, videos and music at anytime and anywhere, and he may change his currently used device or attached network to another one. To manage video streaming sessions among heterogeneous networks and devices, we developed a Ubiquitous Multimedia Service Platform for Mobile Life over the Digital Home Environment (UMS-MLDH) in a 3-year (2006-2009) National Telecommunication Project (NTP). Many distinct-domainsˇ core techniques are devised and well integrated in UMS-MLDH, including session mobility management, session signaling and communication and adaptive layered video streaming over a 3-tier server-proxy-client network architecture. In our experiments, the system integration, implementation and merits of UMS-MLDH are exhibited over a hybrid Home-Vehicular-Office network.

Analysis of a large-scale VOD architecture for broadband operators: a P2P-based solution

VOD services distribution is gaining unprecedented interest from the consumer communication industry due to its growing success in both the Internet and residential broadband market. In this article we present a scalable VOD distribution architecture for broadband operators. The solution is based on a P2P streaming concept in which a VOD streaming session requested by a given STB is actually provisioned via a multisource streaming session. This solution has the advantage of scaling naturally with the number of STBs in the network. In this article we focus on efficiently translating the popularity distribution into content availability in the network. Different aspects related to this issue are analyzed and challenges highlighted.

RStream: Resilient and Optimal Peer-to-Peer Streaming with Rateless Codes

Due to the lack of stability and reliability in peer-topeer networks, multimedia streaming over peer-to-peer networks represents several fundamental engineering challenges. First, multimedia streaming sessions need to be resilient to volatile network dynamics and node departures that are characteristic in peer-to-peer networks. Second, they need to take full advantage of the existing bandwidth capacities, by minimizing the delivery of redundant content and the need for content reconciliation among peers during streaming. Finally, streaming peers need to be optimally selected to construct high-quality streaming topologies, so that end-to-end latencies are taken into consideration. The original contributions of this paper are two-fold. First, we propose to use a recent coding technique, referred to as rateless codes, to code the multimedia bitstreams before they are transmitted over peer-to-peer links. The use of rateless codes eliminates the requirements of content reconciliation, as well as the risks of delivering redundant content over the network. Rateless codes also help the streaming sessions to adapt to volatile network dynamics. Second, we minimize end-to-end latencies in streaming sessions by optimizing towards a latency-related objective in a linear optimization problem, the solution to which can be efficiently derived in a decentralized and iterative fashion. The validity and effectiveness of our new contributions are demonstrated in extensive experiments in emulated realistic peer-to-peer environments with our rStream implementation.

Characterizing Peer-to-Peer Streaming Flows

The fundamental advantage of peer-to-peer (P2P) multimedia streaming applications is to leverage peer upload capacities to minimize bandwidth costs on dedicated streaming servers. The available bandwidth among peers is of pivotal importance to P2P streaming applications, especially as the number of peers in the streaming session reaches a very large scale. In this paper, we utilize more than 230 GB of traces collected from a commercial P2P streaming system, UUSee, over a four-month period of time. With such traces, we seek to thoroughly understand and characterize the achievable bandwidth of streaming flows among peers in large-scale real-world P2P live streaming sessions, in order to derive useful insights towards the improvement of current-generation P2P streaming protocols, such as peer selection. Using continuous traces over a long period of time, we explore evolutionary properties of inter-peer bandwidth. Focusing on representative snapshots of the entire topology at specific times, we investigate distributions of inter-peer bandwidth in various peer ISP/area/type categories, and statistically test and model the deciding factors that cause the variance of such inter-peer bandwidth. Our original discoveries in this study include: (1) The ISPs that peers belong to are more correlated to inter-peer bandwidth than their geographic locations; (2) There exist excellent linear correlations between peer last-mile bandwidth availability and inter-peer bandwidth within the same ISP, and between a subset of ISPs as well; and (3) The evolution of inter-peer bandwidth between two ISPs exhibits daily variation patterns. Based on these insights, we design a throughput expectation index that facilitates high-bandwidth peer selection without performing any measurements.

Load balancing for video streaming services in hierarchical wireless networks

Wireless networks have focused on voice call services or wireless Internet access services. These days, the application service domain of wireless networks is rapidly expanding, and a wide variety of new services is emerging. Video streaming service is one of the most promising examples, evidenced by 3GPP's MBMS (Multimedia Broadcast Multicast Service) and IMS (IP Multimedia Subsystem). In this paper, we consider the provision of video streaming services in hierarchical wireless networks with multiple layers of cells. We particularly focus on optimal load balancing among the cells, aiming at the minimization of frame drop ratio for given video streaming sessions. From this objective function, we derive the optimal load balancing condition. Load balancing is essentially the issue of which users are assigned to which cell, i.e., the user assignment problem. In our user assignment algorithm, we compute thresholds to divide users into groups according to the user characteristics, and map the user groups to proper cells. The optimal load balancing condition can be reached by adaptively adjusting the threshold at run time. This process does not require prior knowledge about the system status, such as the system capacity or user traffic requests, which warrants the practicality of the proposed scheme. Via simulations, we demonstrate that the proposed scheme achieves optimal load balancing in various realistic environments.

A session‐oriented approach in modeling hierarchies of streams

AbstractData stream systems became recently the focus of intense research activity. Sensor measurements, financial data, network packets and log files can all be seen as data streams. The ability to query data streams is of increasing importance and has been identified as a crucial element for modern organizations and agencies. This article identifies an interesting class of applications where stream sessions may be organized into a hierarchical fashion—i.e. sessions may consist of subsessions. For example, log streams from call centers belong to different call sessions and call sessions consist of services subsessions. We may want to monitor statistics and perform accounting at any level on this hierarchy, relative to any other (higher) level (e.g. monitoring the average service session per call vs the average service session for the entire system). We argue that data streams of this kind have rich procedural semantics—i.e. behaviour—and therefore a semantically rich model should be used: a session may be defined by opening and closing conditions, may have data and methods and may consist of subsessions. We propose a simple conceptual model based on the notion of ‘session’—similar to a class in an object‐oriented environment having lifetime semantics. Queries on top of this schema can be formulated via HSA (hierarchical stream aggregate) expressions. We give an algorithm describing how stream data ‘flow down’ session hierarchies and discuss potential evaluation and optimization techniques for HSAs. We finally present NESTREAM, a prototype implementation incorporating many of these concepts. Copyright © 2007 John Wiley & Sons, Ltd.

Video streaming: Implementation and evaluation in an undergraduate nursing program

Video streaming technology enables video content, held on the web sites, to be streamed via the web. We report the implementation and evaluation of video streaming in an undergraduate nursing program in a metropolitan university in Australia. Students (n=703) were emailed a survey with a 15% response rate. We found that 91% (n=74) of respondents stated that video streaming assisted their learning. Forty-six percent(n=50) of students had difficulty accessing video streaming (particularly at the beginning of the study period). Over a 97-day period there were 8440 "hits" to the site from 1039 different internet protocol (IP) addresses. There were 4475 video streaming sessions undertaken by users. Video streaming was used for reviewing previously attended lectures (52%, n=56), examination preparation (34%, n=37), viewing missed lectures (27%, n=29) and class preparation (9%, n=10). Our experience with the introduction of video streaming has met with general enthusiasm from both students and teaching staff. Video streaming has particular relevance for rural students.

Multi-user video streaming over multi-hop wireless networks: A distributed, cross-layer approach based on priority queuing

Emerging multi-hop wireless networks provide a low-cost and flexible infrastructure that can be simultaneously utilized by multiple users for a variety of applications, including delay-sensitive multimedia transmission. However, this wireless infrastructure is often unreliable and provides dynamically varying resources with only limited quality of service (QoS) support for multimedia applications. To cope with the time-varying QoS, existing algorithms often rely on non-scalable, flow-based optimizations to allocate the available network resources (paths and transmission opportunities) across the various multimedia users. Moreover, previous research seldom optimizes jointly the dynamic routing with the adaptation and protection techniques available at the medium access control (MAC) or physical (PHY) layers. In this paper, we propose a distributed packet-based cross-layer algorithm to maximize the decoded video quality of multiple users engaged in simultaneous real-time streaming sessions over the same multi-hop wireless network. Our algorithm explicitly considers packet-based distortion impact and delay constraints in assigning priorities to the various packets and then relies on priority queuing to drive the optimization of the various users' transmission strategies across the protocol layers as well as across the multi-hop network. The proposed solution is enabled by the scalable coding of the video content (i.e. users can transmit and consume video at different quality levels) and the cross-layer optimization strategies, which allow priority-based adaptation to varying channel conditions and available resources. The cross-layer strategies - application layer packet scheduling, the policy for choosing the relays, the MAC retransmission strategies, the PHY modulation and coding schemes - are optimized per packet, at each node, in a distributed manner. The main component of the proposed solution is a low-complexity, distributed, and dynamic routing algorithm, which relies on prioritized queuing to select the path and time reservation for the various packets, while explicitly considering instantaneous channel conditions, queuing delays and the resulting interference. Our results demonstrate the merits and need for end-to-end cross-layer optimization in order to provide an efficient solution for real-time video transmission using existing protocols and infrastructures. Importantly, our proposed delay-driven, packet-based transmission is superior in terms of both network scalability and video quality performance to previous flow-based solutions that statically allocate resources based on predetermined paths and rate requirements. In addition, the results provide important insights that can guide the design of network infrastructures and streaming protocols for video streaming.

Resource Efficient Quality-Oriented Wireless Broadcasting of Adaptive Multimedia Content

The performance of multimedia stream delivery is influenced by encoding scheme, streaming solution and network conditions. This paper studies the performance of multimedia streaming when using the Quality-Oriented Adaptive Scheme (QOAS) over an IEEE 802.11b Wireless LAN and compares it to that achieved when using other solutions that do not consider end-user quality in their delivery process such as TFRC, LDA+, and non-adaptive schemes. The performance is assessed in terms of average end-user perceived quality, number of concurrent streaming sessions, loss rate, delay, jitter and total throughput when streaming MPEG-4 encoded content. Simulation results show that the QOAS out-performs these other streaming solutions in all aspects of network delivery. QOAS can support a greater number of concurrent streaming sessions at a higher average quality. In addition, for the same number of clients QOAS achieved a higher average end-user quality, as well as better network delivery streaming performance parameters