Layer Rate Allocation Research Articles

Layer rate allocation optimization algorithm with user cluster}{Layer rate allocation optimization algorithm with user cluster

The layer rate optimization of a video layered multicast, in heterogeneous network, includes the number of layers, layer rate, and bandwidth of the user links. In order to solve the NP-hard problem in layer rate optimization, a Layer Rate Allocation Optimization with User Cluster (UC-LRAO) algorithm is proposed. The number of users in each layer and the corresponding user bandwidth carrying video streaming is obtained according to the total user number. Then the video streaming link bandwidth of users of each layer is allocated by introducing the Edmonds-Karp Max-flow Min-cut algorithm and intra-layer network coding. Finally, according to the expected layer number of the layered video streaming, the video streaming is layered again and reconstructed by clustering the users. Then, the layer rate and link bandwidth are optimized and allocated. Simulation results show that the proposed algorithm can improve the system throughput.

Production Data Analysis in a Gas-Condensate Field: Methodology, Challenges and Uncertainties

Production data analysis techniques have been widely used for estimating reservoir properties such as gas in place and average pressure. Knowledge of this information is crucial for proper reservoir management. The present study discusses the roadmap, challenges and uncertainties for analyzing production data in an Iranian gas-condensate offshore field. This work is an integrated study involving the quality check of production data, platform process simulation, orifice simulation, modeling choke performance, well modeling, and Rate Transient Analysis (RTA). The study is an inverse analysis which starts from production platform and continues down to the reservoir. To perform data analysis, we propose five general steps which are: Data gathering/extraction/quality check, well rate determination, well bottom hole pressure estimation, layer rate allocation, and reservoir property estimation. In this study, these steps are discussed elaborately. Furthermore, challenges of each step are presented and discussed. In addition, the required input and also missing data for each step is mentioned. Also, to cope with lack and/or uncertainties of data, feasible solutions are proposed for the current field situation as well as future developments. This paper can help petroleum engineers to know where to start and how to proceed to get to the final step of the analysis, i.e. estimating field gas in place. It also provides insights to challenges and uncertainties of the production analysis in gas-condensate fields.

Optimisation of layer rate and wavelength allocation based on network coding for multirate optical multicast

Layered multicast, one of the multirate multicast, is effective in optimising network throughput for heterogeneous WDM (wavelength division multiplexed) networks. Compared with single layer multicast, layered multicast can achieve the maximal network throughput, making each layer multicast member receive the data with its maximal capacity. However, how to optimise each layer rate for multirate multicast network is a classical NP-hard problem. In this study, the authors propose a layer rate optimal allocation algorithm based on network coding (NC-LROA) to get the optical multicast network maximal throughput and to reduce wavelength number required by multicast. In the NC-LROA algorithm, the multicast layered rate is optimised with the heuristic algorithm, which runs to reachable network maximal throughput rather than the minimal value in each destination node's maximal flow. The authors use the network coding to compress the transmitting information among wavelength channels, which have high links sharing degree so as to improve wavelength utilisation. The high sharing degree links have the priority to assign wavelength bandwidth in the inter-layer multicast routing. Simulation results show that the proposed algorithm can, by optimising the layer rate, get network maximal throughput and at the same time reduce the wavelength bandwidth consumption for the optical multicast network.

Optimal Layer Rate Allocation in Layered Media Multicast Based on Network Coding

Optimal Layer Rate Allocation in Layered Media Multicast Based on Network Coding

Downlink TCP performance under cross layer rate and power allocation in infrastructure TH-PPM UWB networks

Ultra wideband (UWB) systems are currently an important wireless infrastructure for efficient short-range communications and mobile applications. To improve the system efficiency while guaranteeing the radio link level quality of services, the transmission rate and power of the mobile nodes in UWB based infrastructure networks can be dynamically adjusted by executing an optimization algorithm at the access points (APs). In this paper, we present a cross layer rate and power allocation algorithm based on the multilayer model of time hopping (TH) pulse position modulation (PPM) UWB multimedia networks. We consider the performance of the TCP protocol under the proposed cross layer allocation scheme in various realistic UWB based infrastructure networking scenarios.

Effective Video Multicast over Wireless Internet: Rate Allocation and End-System Based Adaptation

With the rapid growth of wireless networks and great success of Internet video, wireless video services are expected to be widely deployed in the near future. As different types of wireless networks are converging into all IP networks, i.e., the Internet, it is important to study video delivery over the wireless Internet. This paper proposes a novel end-system based adaptation protocol called Wireless Hybrid Adaptation Layered Multicast (WHALM) protocol for layered video multicast over wireless Internet. In WHALM the sender dynamically collects bandwidth distribution from the receivers and uses an optimal layer rate allocation mechanism to reduce the mismatches between the coarse-grained layer subscription levels and the heterogeneous and dynamic rate requirements from the receivers, thus maximizing the degree of satisfaction of all the receivers in a multicast session. Based on sampling theory and theory of probability, we reduce the required number of bandwidth feedbacks to a reasonable degree and use a scalable feedback mechanism to control the feedback process practically. WHALM is also tuned to perform well in wireless networks by integrating an end-to-end loss differentiation algorithm (LDA) to differentiate error losses from congestion losses at the receiver side. With a series of simulation experiments over NS platform, WHALM has been proved to be able to greatly improve the degree of satisfaction of all the receivers while avoiding congestion collapse on the wireless Internet.

An End-to-End Adaptation Protocol for Layered Video Multicast Using Optimal Rate Allocation

Layered transmission is a promising solution to video multicast over the heterogeneous Internet. However, since the number of layers is practically limited, noticeable mismatches would occur between the coarse-grained layer subscription levels and the heterogeneous and dynamic rate requirements from the receivers. In this paper, we show that such mismatch can be effectively reduced using a dynamic and fine-grained layer rate allocation on the sender's side. Specifically, we study the optimization criteria for rate allocation, and propose a metric called application-aware fairness index. This metric takes into consideration 1) the nonlinear relation between the perceived video quality and the delivered rate and 2) the degree of satisfaction for receivers with heterogeneous bandwidth requirements. We formulate the rate allocation into an optimization problem with the objective of maximizing the expected fairness index for all receivers in a multicast session. We then derive an efficient and scalable solution, and demonstrate that it can be seamlessly integrated into an end-to-end adaptation protocol, called hybrid adaptation layered multicast (HALM). This protocol takes advantage of the emerging fine-grained layered coding, and is fully compatible with the best-effort Internet infrastructure. Simulation and numerical results show that HALM noticeably improves the degree of fairness, and interacts with TCP traffic better than static allocation based protocols. More important, increasing the number of layers in HALM generally improves the degree of fairness; it is sufficient to obtain satisfactory performance with a small number of layers (three to five layers).