Rate Allocation Scheme for Machine-to-Machine Service Based on 3GPP in Heterogeneous Wireless Networks

In this study,an explicit adaptive traffic allocation scheme for Machine-to-Machine(M2M)service is proposed to achieve optimum distribution in heterogeneous networks.Based on the characteristics of M2M services,the presented scheme is formulated as a convex optimization problem that maximises the utility of the M2M service,and then determines how to allocate the total rate among the multiple access networks.The analysis and numerical simulations indicate that the proposed scheme makes a significant improvement in performance compared with the traditional schemes.

Optimal Rate Allocation Based on Cross-Layer Design and End-to-End Congestion Control in WCDMA Networks

In this paper, a novel idea for rate allocation combining both vertical coupling and horizontal coupling constraints is proposed, and a unified utility function to balance two paradoxical issues: efficiency and fairness, revenue and cost is elaborated in WCDMA networks. Then, the optimal rate allocation problem is formulated as a network utility maximization(NUM) model based on cross-layer design and end-to-end congestion control, aiming at exploring the impacts of wired networks and the characteristics of radio access networks(RANs) on rate allocation. Furthermore, a distributed algorithm is derived, which can effectively match load states between RANs and wired networks, followed by a detailed illustration of the practical implementations. Numerical results demonstrate a signifi cant performance improvement in the end-to-end throughput.

New Rate Allocation Method for MPEG-4 FGS Video Streaming

A new rate allocation method for fine-granular scalability (FGS) coded bitstreams is presented in order to achieve smooth quality reconstruction of frames under channel conditions with a wide range of bandwidth variation and improve the average PSNR of the whole sequence. Based on a quality weighted bit allocation method, a sliding window rate allocation method is proposed for the first time so that the window can slide along the video sequence with a certain sliding step. Experimental results show that, under dynamic bandwidth conditions, the proposed method can simultaneously satisfy the requirements for improving average PSNR of the whole video sequence greatly and reducing the fluctuations between adjacent frames greatly.

AN EFFICIENT BIT RATE ALLOCATION ALGORITHM FOR MOTION JPEG2000 TRANSPORT IN TILE ENCODING

An efficient bit rate allocation algorithm for video sequence transmission in motion JPEG2000 is presented. In many cases,the moving portions of video are often the interested regions. Based on tile encoding of JPEG2000,the important regions are discerned by two parameters. One is the complexity of a tile;the other is the motion activity of a tile. Thus an adaptive rate-allocation is re-alized in a lower complexity and the perceptive quality of a frame is improved. Experimental results show the effectiveness of this algorithm.

An optimal flow rate allocation model of the oilfield treated oil pipeline network

Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fluctuation in the demand and sales prices of the treated oil,there is an optimal flow allocation plan for the pipeline network to make the oilfield company obtain the highest social and economic benefit.In this study,a mixed integer nonlinear programming(MINLP)model is developed to determine the optimal flow rate allocation plan of the large-scale and complex treated oil pipeline network,and both the social and economic benefits are considered simultaneously.The optimization objective is the multi-objective which includes the largest user satisfaction and the highest economic benefit.The model constraints include the oilfield production capacity,refinery demand,pipeline transmission capacity,flow,pressure,and temperature of the node and station,and the pipeline hydraulic and thermal calculations.Python 3.7 is utilized for the programming of the off-line calculation procedure and the MINLP model,and GUROBI 9.0.2 is served as the MINLP solver.Moreover,the model is applied to a real treated oil pipeline network located in China,and three optimization scenarios are analyzed.For social benefit,the values of the user satisfaction of each refinery and the total network are 1 before and after optimization for scenarios 1,2,and 3.For economic benefit,the annual revenue can be increased by 0.227,0.293,and 0.548 billion yuan after the optimization in scenario 1,2,and 3,respectively.

Resource Allocation and User Association for HTTP Adaptive Streaming in Heterogeneous Cellular Networks with Small Cells

Video streaming,especially hypertext transfer protocol based(HTTP) adaptive streaming(HAS) of video,has been expected to be a dominant application over mobile networks in the near future,which brings huge challenge for the mobile networks.Although some works have been done for video streaming delivery in heterogeneous cellular networks,most of them focus on the video streaming scheduling or the caching strategy design.The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users is largely ignored.In this paper,the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied,we model the optimization problem as a mixed integer programming problem.And to reduce the computational complexity,an optimal rate allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved.Then we use the many-to-one matching model to analyze the user association problem,and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed.Finally,extensive simulation results are illustrated to demonstrate the performance of the proposed scheme.

Energy-Efficient Resource Allocation for Small-Cell Networks：A Stable Queue Perspective

The small-cell technology is promising for spectral-efficiency enhancement. However, it usually requires a huge amount of energy consumption. In this paper, queue state information and channel state information are jointly utilized to minimize the time average of overall energy consumption for a multi-carrier small-cell network, where the inter-cell interference is an intractable problem. Based on the Lyapunov optimization theory, the problem could be solved by dynamically optimizing the problem of user assignment, carrier allocation and power allocation in each time slot. As the optimization problem is NP-hard, we propose a heuristic iteration algorithm to solve it. Numerical results verify that the heuristic algorithm offers an approximate performance as the brute-force algorithm. Moreover, it could bring down the overall energy consumption to different degrees according to the variation of traffic load. Meanwhile, it could achieve the same sum rate as the algorithm which focuses on maximizing system sum rate.

Optimal Rate Allocation Algorithm for Multiple Source Video Streaming

Video streaming is one of the most important applications used in the best-effort Internet. This paper presents a new scheme for multiple source video streaming in which the traditional fine granular scal-able coding was rebuilt into a multiple sub-streams based transmission model. A peak signal to noise ratio based stream rate allocation algorithm was then developed based on the transmission model. In tests, the algorithm performance is about 1 dB higher than that of a uniform rate allocation algorithm. Therefore, this scheme can overcome bottlenecks along a single link and smooth jitter to achieve high quality and stable video.

A new encoder rate-allocation method for distributed video coding

Distributed video coding(DVC)is a new video coding architecture.Compared with traditional video coding schemes,DVC has a simple encoder and complex decoder,which makes it suitable for circumstances where the encoder equipments are simple but the decoder equipments are complex.Most of the existing DVC architectures use decoder rate allocation method with the help of feedback channel.According to the results of the current decoding round,the decoder informs the encoder by feedback channel whether more parity bits are needed.The use of feedback channel not only increases the system delay,but also limits the use of DVC to instances where there is no feedback channel.In this paper,we propose a novel encoder rate allocation method.First,the simple three-step motion estimation is introduced into the encoder to estimate the side information of the decoder,and then the number of parity bits the decoder needs for each bitplane is allocated at the encoder according to the difference of the estimated side information and the current Wyner-Ziv(WZ)frame.Experiment results indicate that the accuracy of the proposed method is 5.18%-52.93% higher than that of the method proposed by Morbee.

A probabilistic approach for predictive congestion control in wireless sensor networks

Any node in a wireless sensor network is a resource constrained device in terms of memory, bandwidth, and energy, which leads to a large number of packet drops, low throughput, and significant waste of energy due to retransmission. This paper presents a new approach for predicting congestion using a probabilistic method and controlling congestion using new rate control methods. The probabilistic approach used for prediction of the occurrence of congestion in a node is developed using data traffic and buffer occupancy. The rate control method uses a back-off selection scheme and also rate allocation schemes, namely rate regulation(RRG) and split protocol(SP), to improve throughput and reduce packet drop. A back-off interval selection scheme is introduced in combination with rate reduction(RR) and RRG. The back-off interval selection scheme considers channel state and collision-free transmission to prevent congestion. Simulations were conducted and the results were compared with those of decentralized predictive congestion control(DPCC) and adaptive duty-cycle based congestion control(ADCC). The results showed that the proposed method reduces congestion and improves performance.