With the rise of Video-on-Demand (VoD) systems as a preferred way to distribute video content over IP networks, many research works and innovations have focused on improving the scalability of streaming systems by looking at distributed approaches such as peer-to-peer (P2P). One of the most critical aspects in P2P-assisted streaming system is the real-time resource allocation, which drives the performance of the system in terms of capacity utilization and VoD requests rejection rates. In this paper, we specifically focus on the problem of maximizing the P2P streaming system utilization by effectively alternating between different resource allocation strategies. Switching between different resource allocation strategies is guided by a run-time statistical analysis of performances against predicted content popularity pattern. A key contribution of this paper resides in effectively combining different, and potentially conflicting, performance objectives when deciding on which resource allocation strategy to use. Indeed, we use a Bayesian Fusion to select the most appropriate resource allocation strategy to deal with future content demand. With our P2P resource allocation framework, a VoD service operator can combine any number of resource allocation strategies and formulate different performance objectives that meet the requirements of its network and the content consumption behavior of its users.

During the past decade, Peer-to-Peer Video-on Demand (VoD) systems have proved their efficiency for large deployments. They raise new challenges such as peers resource allocation. Most literature on resource allocation tackle the problem with optimal static rules found at offline study of the system. In this paper, we use a dynamic metaheuristic, called Multiple Local-Search Algorithm for Dynamic Optimization (MLSDO) to optimize the problem at hand. The obtained results show that using a dynamic resource allocation reduces the rejection rate while enhancing the entropy of the system, in the face of a dynamically changing title demand.

In this paper we outline a vision for the Connected Car which is centred around the user's mobile device. We describe the different components of the Connected Car ecosystem and highlight why it will remain very heterogeneous for some time. We describe particular technologies in this space which have real potential to be key technologies in the Connected Car. Finally, we review online services which are relevant for automotive services.

Strong with large pools of set-top-boxes (STB) already deployed and connected to high-capacity networks, broadband operators sit on a major opportunity to introduce P2P-based VOD streaming architectures that scales up to the demand, reduce the per-service cost, and ultimately position the operators in a more competitive footing in respect to the increasingly successful Internet streaming services Achieving the required cost-efficiency in such services involves many research challenges, chief among which is the resource allocation in terms of assigning contributing STBs to stream a given VOD service. This paper1investigates resource allocation issues associated with the operation of P2P-based VOD streaming systems in the context of a broadband operator. First, we introduce basic resource allocation models that use a single-criterion (Available Uplink, Popularity Score, and Critical Score) to select contributing STBs and satisfy an incoming VOD request. We individually evaluate the performance of every single-criterion resource allocation strategy, and highlight its strengths and weaknesses in dealing with different situations.

In this article, we design, implement, and analyze a scalable Live VOD services distribution architecture that offers higher video services reliability for a fraction of the current cost. Our solution (RS-VOD) is based on a P2P retransmission system where end-users retransmit lost packets to each other, thereby reducing the retransmission burden on the video servers. Video receivers tuned to the same video stream are organized in an overlay network of retransmission peers that exchange useful statistics and performance metrics describing the network conditions affecting their respective received video streams. Signalling data exchanged among retransmission peers include: loss rate measurements, packet loss pattern, round-trip-time (RTT) measurements, etc. Based on this real-time information exchange, each receiver assesses the suitability of each retransmission peer before allocating a retransmission load for each of them. We show that the service provider can use several strategies to control the process of selecting retransmission peers and outperform in different network conditions. Several decision models have been implemented and analyzed in this article. We also highlight the major findings and tradeoffs in a P2P retransmission system.

In this paper, the system capacity of a multi-cell IEEE 802.16j system operating in transparent mode is investigated. A previous published analytical model is used and incorporates interference from neighbouring cells. The model can be used to determine downlink performance under max-min fairness constraints for both sectored and omnidirectional systems with different amounts of relays. The study provides guidelines on the design of 802.16j systems operating in transparent mode specifically, how to maximise throughput for such systems. It is shown that inter-cell interference from relays is limited in a suburban environment and that relays can deliver significant gains over single hop systems: gains of 30% and 60% can be achieved without and with spatial reuse in an omnidirectional system while 15% and 25% in a sectorised system.

Multi-source streaming is essential for the design of a large-scale P2P streaming architecture. In this paper, we focus on improving the dependability of multi-source video streaming as an alternative to the more prevalent point-to-point streaming. We have designed and implemented a dynamic FEC (D-FEC) protocol for multi-source video streaming. Our D-FEC protocol has the ability to dynamically switch between 4 different FEC techniques to adapt to varying network conditions. A comprehensive performance evaluation was performed with a full-scale system prototype that gives insights into the behavior of the different adaptive FEC schemes, and shows the feasibility of the concept of switching FEC schemes during a streaming session. Guidelines are given in order to best design a FEC protocol switching strategy taking into account the experienced loss rate, the loss burstiness, and the original video stream rate.

In this paper, we propose a fair and dynamic auction-based QoS negotiation scheme that allows users to dynamically negotiate their agreed service levels with their service provider. The scheme has three major design goals: ensuring a high degree of fairness among competing users, efficient utilization of the underlying network resources, and maximization of the service provider's revenue. A mathematical analysis is provided to demonstrate that when the three design goals are taken into account, the resource allocation function proposed in this paper represents a Pareto optimal solution.

This paper describes a new architecture and implementation of an adaptive streaming system (e.g., television over IP, video on demand) based on cross-layer interactions. At the center of the proposed architecture is the meet in the middle concept involving both bottom-up and top-down cross layer interactions. Each streaming session is entirely controlled at the RTP layer where we maintain a rich context that centralizes the collection of (i) instantaneous network conditions measured at the underlying layers (i.e.: link, network, and transport layers) and (ii) user- and terminal-triggered events that impose new real-time QoS adaptation strategies. Thus, each active multimedia session is tied to a broad range of parameters, which enable it to coordinate the QoS adaptation throughout the protocol layers and thus eliminating the overhead and preventing counter-productiveness among separate mechanisms implemented at different layers. The MPEG-21 framework is used to provide a common support for implementing and managing the end-to-end QoS of audio/video streams. Performance evaluations using peak signal to noise ratio (PSNR) and structural similarity index (SSIM) objective video quality metrics show the benefits of using the proposed Meet In the Middle cross-layer design compared to traditional media delivery approaches.

Most of QoS-capable IEEE 802.11 MAC protocols are unable to deliver sustained quality of service while maintaining high network utilization, particularly under congested network conditions. The problem often resides in the fact that flows belonging to the same service class are assigned the same MAC parameters regardless theirs respective bitrate, which leads to throughput fairness rather than perceived QoS fairness. Harmonizing MAC parameters of traffic classes's flows may further lead to sub-optimal situations since certain network configurations (in terms of per class traffic load) can not be accommodated without reassigning the basic MAC parameters. In this paper, we propose a new cross-layer MAC design featuring a delay-sensitive backoff range adaptation along with a distributed flow admission control. By monitoring both MAC queue dynamics and network conditions, each traffic class reacts based on the degree to which application QoS metrics (delay) are satisfied. Besides, we use a distributed admission control mechanism to accept new flows while protecting the active one. Simulation results show that compared to the enhanced distributed coordination function (EDCA) scheme of 802.11e, our protocol consistently excels, in terms of network utilization, bounded delays, and service-level fairness.

This paper introduces a buffer occupancy-based admission control mechanism aimed to counter link congestion while fairly sharing the bandwidth in converged IP and broadcasting networks. The proposed connection admission control (CAC) scheme favors fairness and downlink bandwidth sharing between different served satellite terminals (sub-networks) in presence of congestion events. Our CAC is intended to overcome major obstacles such as: instantaneous link capacity (available bandwidth) assessing, high computational complexity in flows characterization, and use of traffic descriptors with new flows. This makes the scheme more suitable for DVB-S2 environments where the link capacity may vary as consequence of physical layer adaptive coding/modulation during noisy periods. Simulations results show that the proposed system can avoid uplink and downlink congestion and share fairly the bandwidth between satellite terminals. Further, our CAC minimize the probability of congestion events while still achieving high resources utilization.

This paper describes the issues related to IP multicast support in satellites networks. The IGMP multicast membership management protocol is considered as inappropriate for multicast group management over satellite network. In fact, IGMP leads to flooding, latency and scalability issues when used over asymmetric satellite networks. Thus, we propose a new architecture for multicast services provisioning based on IP multimedia subsystem (IMS) as a service delivery platform. The interworking between IP multicast protocol (i.e., IGMP) and IMS protocol (i.e., SIP) is demonstrated to overcome these multicast scalability issues inherent to satellite networks. Implementation and deployment of the proposed platform over an advanced satellite network emulator is also described.

With the steadily growing synergy between existing heterogeneous networks, the wireless LAN appears as the de-facto wireless access network in the end-to-end multimedia services distribution chain. Unlike in the traditional wired multi-hop networks (Internet) where congestions increase persistently both delays and losses, wireless packet losses are often location- and time-varying. Particularly, WLAN communication is characterized by high bit error rates that translates into tight loss dependency. The loss process may rapidly shift between different loss correlations levels, resulting in poor forward error correction (FEC) recovery capabilities. In this paper, we address this issue by providing a combined loss model to accurately characterize the wireless loss distribution features. We use control theory guided parameter tuning in order to urge the convergence of the loss models towards seizing the instantaneous loss distribution trends. Finally, we derive a new loss-specific QoS metrics for new FEC block allocation scheme.

With the widespread IEEE 802.11 networks use, strong needs to enhance quality of service (QoS) has appeared. The IEEE 802.11 medium access control (MAC) protocol provides a contention-based distributed channel access mechanism that allow for wireless medium sharing. This protocol involves a significant collision rate as the network gets fairly loaded. Although the contention window (CW) is doubled after each collision, active stations may randomly select a backoff timer value smaller than the preceding one. This is obviously sub-optimal since the backoff values should rather increase after each collision in order to further space between successive transmissions and thus absorbing the growing contending flows. In this paper, we propose a novel backoff mechanism, namely "determinist contention window algorithm" (DCWA), which further separates between the different backoff ranges associated to the different contention stages. Instead of just doubling the upper bound of the CW, DCWA increases both backoff range bounds (i.e., upper and lower bounds). On the other hand, after each successful transmission the backoff range is readjusted by taking into account current network load and past history. Simulation results show that DCWA outperforms both the distributed coordination function (DCF) and the slow decrease (SD) scheme in terms of responsiveness to network load fluctuations, network utilization, and fairness among active stations.

Many works have recently addressed the IEEE 802.11 QoS issues by proposing different monitoring-based contention window (CW) differentiation techniques. In network saturation, however, it is difficult to guarantee firm services differentiation while achieving high network exploitation. Particularly, most existing QoS-capable MAC protocols rely on a backoff interval sampled from a dynamic range [0 CW/sub i/]. In order to ensure more deterministic service differentiation, we propose a new MAC protocol featuring a sliding contention window (SCW) for each network flow. The different flows are now able to select backoff intervals from different (separated) CW ranges. The SCW dynamically adjusts to changing network conditions, but remains within a per-class predefined range, in order to maintain a separation between different service classes. Simulation results show that compared to the EDCA scheme of 802.11e, SCW consistently excels, in terms of network utilization, strict service separation, and service-level fairness.

Recently, many active queue management (AQM) algorithms have been proposed to address performance degradations of end-to-end congestion control. However, these AQM algorithms present weaknesses for stabilizing delays in heavily loaded networks. In this paper, we describe a novel adaptive fuzzy control algorithm to improve best effort TCP/IP networks performance. Compared to traditional AQM algorithms (RED, PID and others), our proposal avoids buffer overflows/underflows, and minimizes packet dropping. We propose an on-line adaptation mechanism that captures fluctuating network conditions, while classical AQM algorithms require static tuning. The algorithm stability is mathematically proven. Simulation results show that for the same link utilization, our fast adaptive fuzzy controller provides better performance than RED and PID.

Robust video streaming over wireless local area networks (IEEE 802.11) faces many challenges, including bandwidth channel variations, data errors/losses, and terminal capacity heterogeneity. This is worsen by the TCP/IP architecture that does not offer any quality of service QoS guarantees to demanding applications such as video streaming. In order to improve error resilience and user-perceived video quality, a novel error control protocol, called "unequally interleaved forward error correction" (UI-FEC), is proposed. UI-FEC is particularly efficient for adaptive MPEG-4 video multicast over wireless LAN. The proposed protocol is composed of (1) a coordinated unequal and interleaved MPEG-4 data protection mechanism, that gracefully degrades video quality at receivers while minimizing the overall link bandwidth consumption; (2) an adaptive MPEG-4 video fragmentation and encapsulation protocol for a higher wireless link utilization.

In this article, we investigate efficient transmission of object-based MPEG-4 video over IP networks with QoS management capabilities. MPEG-4 audio visual objects (AVOs) are classified based on application-level QoS criteria and AVOs semantic descriptors according to MPEG-7 framework MPEG-4 AVOs requiring same QoS performance form the network are automatically classified and multiplexed within one of the IP DiffServ PHB (per hop behaviours). Object data-packets within the same class are then transmitted over the selected transport layer with the corresponding bearer capability and priority level. We propose to extend the MPEG-4 system architecture with a new "media QoS classification layer". This layer provides automatic and accurate mapping between MPEG-4 application-level QoS metrics and underlying transport network with QoS mechanisms such as IP DiffServ. The "media QoS classification layer" makes use of a neural network classification model that is transparent to application and network layers. Implementation and performance evaluation of the proposal are also described.