Efficient selective frame discard algorithms for stored video delivery across resource constrained networks

Recent advances in information and communication technology resulted in increased use of multimedia applications. Multimedia transmission over Mobile Adhoc Networks (MANETs) with high Quality of Service (QoS) is a challenging task due to mobility of the nodes. The problems associated with multimedia transmission are loss of packets or frames and delay in receiving the packets at destination. To maintain the QoS, all the multimedia applications need that packets should be delivered in sequence and order, and delay should be within the tolerable limits. Existing works mainly uses packet loss information at source station to determine whether the transmission window size should be increased or decreased In existing approaches, the source station takes decision about increasing or decreasing window size based on reception of Acknowledgement/ non-reception of Acknowledgement. The magnitude of increment/decrement in window size is predefined but not as per actual scenario in the network. This leads to poor utilization of resources. Since multimedia applications are loss-tolerant, it is important to compute the packet loss accurately as the QoS requirements for multimedia services accepts the loss of packets up to some threshold. In this paper, we model the active stations as a Poisson random process and computed the packet loss, idle period and busy period at the front end of route. This packet loss estimation is useful for precise specification of buffer size resulting in improved QoS. Our experimental results demonstrate the usefulness in designing optimal control in order to improve QoS for multimedia applications in MANETs.

As wireless networks become popular, Web surfing on mobile devices will be a hot Internet service in the near future. Mobile devices have two major constrains in their network bandwidth and memory size constraints. We propose a novel browser cache management mechanism in which a SAVUT-based gain function effectively decides the preservation value of cached objects. In addition, a partial caching mechanism is incorporated to extensively utilize the limited browser cache. Two SAVUT-based algorithms are presented to show the practical instances. The comparative simulation results are also elaborated. Although the conducted experiments are preliminary, the results show that PR-SAVUT best performs in most cases.

This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under network bandwidth and playback delay constraints. The streaming policy consists in a joint selection of the network path and of the video packets to be transmitted, along with their sending time. A simple streaming model is introduced, which takes into account the video packet importance, and the dependencies between packets. A careful timing analysis allows to compute the quality perceived by the receiver for a constrained playback delay, as a function of the streaming policy. We derive an optimization problem based on a video abstraction model, under the assumption that the server knows, or can predict accurately the state of the network. A detailed analysis of constrained multipath streaming systems provides helpful insights to design an efficient branch and bound algorithm that finds the optimal streaming strategy. This solution allows to bound the performance of any scheduling strategy, but the complexity of the algorithm becomes rapidly intractable. We therefore propose a fast heuristic-based algorithm, built on load-balancing principles. It allows to reach close to optimal performance with a polynomial time complexity. The algorithm is then adapted to live streaming scenarios, where the server has only a partial knowledge of the packet stream, and the channel bandwidth. Extensive simulations show that the proposed algorithm only induces a negligible distortion penalty compared to the optimal strategy, even when the optimization horizon is limited, or the rate estimation is not perfect. Simulation results also demonstrate that the proposed scheduling solution performs better than common scheduling algorithms, and therefore represents a very efficient low-complexity multipath streaming algorithm, for both stored and live video services

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED).

Three different advanced adaptation techniques for improving the video perception of users are proposed in this paper. The proposed techniques exploit different adaptation decision-taking and adaptation approaches to adapt particular core parameters while considering diverse contextual information and constraints to achieve improved video perception of users. The first proposed technique employs a utility-based adaptation approach to perform adaptation operations on spatial resolution, frame rate, and quality scalability parameters according to the content-related contextual information (i.e., motion activity and structural feature) while fulfilling network bandwidth and terminal display size constraints. Using this technique, video contents can be adapted with the scalability parameters best fitting users' and contextual constraints' needs to achieve improved video perception. The second technique relies on prioritizing key frame, non-key frame, and temporal layer parameter-related network abstraction layer units to adapt video contents to satisfy network bandwidth constraint. The rate-distortion performances of adapted video contents can be improved by utilizing this technique in adaptation operations both in terms of bit rate of adapted video contents and video perception of users. The third technique is based on adapting the bit rate of 3-D video contents according to the changes in ambient illumination of the viewing environment. The adaptation results evaluated by either subjective or objective quality assessment techniques prove that all of the proposed techniques are efficient to improve the video perception of users.

In this digital era, illegitimate redistribution and protection of digital multimedia have to turn out to be the critical issue. Therefore, digital watermarking has been introduced for avoiding illegitimate works and also to ensure security and authentication as well. “Digital video watermarking is a method to hide some kind of data like audio, image, text into digital video sequences which is nothing but orders of successive still images.” This paper intends to formulate a novel video watermarking framework that includes three stages, such as (i) optimal video frame prediction, (ii) watermark embedding process and (iii) watermark extraction process. Very first, the optimal frames are determined using a new hybrid algorithm termed trial-based update on Jaya plus firefly (TU-JF) algorithm, in such a way that the peak signal-to-noise ratio (PSNR) should be maximal. The frames are assigned with a label of one or zero, where label one denotes the frame with better PSNR (can select for embedding process) and label zero denotes the frame with reduced PSNR (cannot be used for embedding). Consequently, a data library is formed from the obtained results, where each frame of videos is determined with their gray-level co-occurrence matrix (GLCM) features and labels (can embed or not). As in the proposed model, the optimal frame prediction is carried out using deep belief network (DBN) framework; the obtained data are then trained in the model. The optimal frames could be predicted in an efficient manner while testing. The significant contribution of this work concerns the optimization of hidden neurons in the DBN framework, which helps to enhance prediction accuracy. At last, the “watermark embedding process” and “watermark extraction process” are done by which the image could be embedded within the optimal frames.

A growing trend has emerged in network architecture research to switch focus from Quality of Service (QoS) to Quality of Experience (QoE) optimization. In this paper, we first present QoE models that characterize user satisfaction of video, audio, and data services over wireless networks. We then develop a novel packet scheduling algorithm for multi-hop wireless networks that jointly optimizes the delivery of multiple video, audio, and data flows according to the QoE metrics. We formulate a multidimensional optimization problem that minimizes the overall distortion across all flows for the given network resources on wireless links. Fairness constraints over the flows are also considered as part of the optimization. Our experimental results, obtained with the NS-2 IEEE 802.16 MESH-mode simulator, show that distortion-aware scheduling can significantly increase the perceived quality of different wireless services under bandwidth constraints. Additionally, improved fairness across the competing flows is demonstrated relative to conventional scheduling techniques.

Developing real time multimedia applications for best effort networks such as the Internet requires prohibitions against jitter delay and frame loss. This problem is further complicated in wireless networks as the rate of frame corruption or loss is higher in wireless networks while they generally have lower data rates compared to wired networks. On the other hand, variations of the bandwidth and the receiving device characteristics require data rate adaptation capability of the coding method. Multiple Description Coding (MDC) methods are used to solve the jitter delay and frame loss problems by making the transmitted data more error resilient, however, this results in reduced data rate because of the added overhead. MDC methods do not address the bandwidth variation and receiver characteristics differences. In this paper a new method based on integrating MDC and the scalable video coding extension of H.264 standard is proposed. Our method can handle both jitter delay and frame loss, and data rate adaptation problems. Our method utilizes motion compensating scheme and, therefore, is compatible with the current video coding standards such as MPEG-4 and H.264. Based on the simulated network conditions, our method shows promising results and we have achieved up to 36dB for average Y-PSNR.

In general, optimal control problems rely on numerically rather than analytically solving methods, due to their nonlinearities. The direct method, one of the numerically solving methods, is mainly to transform the optimal control problem into a nonlinear optimization problem with finite dimensions, via discretizing the objective functional and the forced dynamical equations directly. However, in the procedure of the direct method, the classical discretizations of the forced equations will reduce or affect the accuracy of the resulting optimization problem as well as the discrete optimal control. In view of this fact, more accurate and efficient numerical algorithms should be employed to approximate the forced dynamical equations. As verified, the discrete variational difference schemes for forced Birkhoffian systems exhibit excellent numerical behaviors in terms of high accuracy, long-time stability and precise energy prediction. Thus, the forced dynamical equations in optimal control problems, after being represented as forced Birkhoffian equations, can be discretized according to the discrete variational difference schemes for forced Birkhoffian systems. Compared with the method of employing traditional difference schemes to discretize the forced dynamical equations, this way yields faithful nonlinear optimization problems and consequently gives accurate and efficient discrete optimal control. Subsequently, in the paper we are to apply the proposed method of numerically solving optimal control problems to the rendezvous and docking problem of spacecrafts. First, we make a reasonable simplification, i.e., the rendezvous and docking process of two spacecrafts is reduced to the problem of optimally transferring the chaser spacecraft with a continuously acting force from one circular orbit around the Earth to another one. During this transfer, the goal is to minimize the control effort. Second, the dynamical equations of the chaser spacecraft are represented as the form of the forced Birkhoffian equation. Then in this case, the discrete variational difference scheme for forced Birkhoffian system can be employed to discretize the chaser spacecraft's equations of motion. With further discretizing the control effort and the boundary conditions, the resulting nonlinear optimization problem is obtained. Finally, the optimization problem is solved directly by the nonlinear programming method and then the discrete optimal control is achieved. The obtained optimal control is efficient enough to realize the rendezvous and docking process, even though it is only an approximation of the continuous one. Simulation results fully verify the efficiency of the proposed method for numerically solving optimal control problems, if the fact that the time step is chosen to be very large to limit the dimension of the optimization problem is noted.

The aim is to provide corresponding quality of service (QoS) guarantee for real-time video data transmission. To ensure the high quality and smooth playback of video sequence at the receiving end, the design of multimedia transmission is made. In view of the shortcomings of selective frame loss, this paper adopts the active frame loss algorithm, which discards the nonkey frames according to the probability. With the increase of the frame loss rate at the transmitter, the proportion of decoded frames increases rapidly and reaches the maximum when the frame loss rate is 0.1. It is proved that active frame loss can control the bit rate more accurately to make full use of bandwidth resources and avoid the waste of bandwidth resources.

Multimedia applications such as digital video and audio often have stringent quality-of-Service (QoS) requirements. In recent years, several new architectures have been developed for supporting such applications. One Important element that is still missing from these architectures is QoS routing, namely routing based on QoS requirements.In traditional data networks, routing has been primarily concerned with connectivity. Routing Protocols usually characterize the network with a single metric such as hop-count or delay. However to support a wide range of QoS requirements, there is a need to consider multiple metrics such as bandwidth, delay and loss probability while making routing decisions. The problem of determining a path that satisfies multiple constraints is computationally very demanding and in most cases, such problems have been shown to be NP complete.In this paper, we first examine the basic problem of QoS routing and then propose a new, efficient learning algorithm for selection of the optimum path. This algorithm is subsequently utilized to make routing decisions in various routing architectures.

Heuristic algorithms for packing of multiple-group multicasting

The key contribution of the work herein described is an integrated network service architecture for airborne networks (ANs), wherein a set of robust and auto-configurable network service mechanisms are designed to handle network dynamics and bandwidth constraints in AN environments. Instead of covering all possible network services, address configuration and name resolution are addressed in this paper. For address configuration, the designed IP address auto-configuration mechanism provides automatic conflict-free address assignment with bandwidth-efficiency. Additionally, it is integrated with a domain maintenance mechanism to further support network dynamics, such as domain splitting and merging. For naming service, the concept of Domain Name System (DNS) is extended by adding dynamic server configurations and linkages to enhance its robustness and efficiency. Both the address configuration and name resolution services have been evaluated, and the simulation results demonstrate their promising performance.

In cyber-physical systems (CPSs) operating under complex communication environments characterized by dynamic network topologies and bandwidth constraints, the performance of control loops can be significantly degraded by various types of interference, such as signal noise, time-varying delays, and malicious attacks. This paper investigates the output tracking control (OTC) performance of CPSs under the influences of deception attack and hybrid attacks, by proposing a trade-off performance index blends tracking error and channel input power constraints. Given the stochastic nature of cyber-attacks in CPSs, the investigated deception attacks and Denial-of-Service (DoS) attacks are formally modeled as two mutually independent Bernoulli-distributed random variables. Through frequency-domain and the Youla parameterization method, this study establishes two closed-form analytical expressions. The results reveal that the OTC performance is fundamentally constrained by the inherent characteristics of the plant and the attack parameters. Finally, simulation validations are conducted through a given single-input-single-output plant and an inverted pendulum system.

Fog Computing is created to efficiently store and access data without the limitations challenging Cloud Computing deployments, such as network latency or bandwidth constraints. This is achieved by performing most of the processing on servers located as close as possible to where data is being collected. When mobile devices are equipped with limited resources and small capabilities, it would be convenient to make their associated computing and network resources follow them as much as possible. In this paper, migration process is studied and an algorithmic model is designed, selecting a generic Fat Tree architecture as the underlying topology, which may be useful to get a list of all devices being traversed through each of the redundant paths available.