In this paper, the pricing and bandwidth allocation in heterogeneous wireless access networks is studied. Demand modeling and resource allocation in heterogeneous wireless access networks is carried out using the theories of microeconomics in competitive markets. A competitive market model for bandwidth allocation and pricing is presented where new relaxation models and propositions are developed to address various aspects of the operation of wirless access networks such as roaming and hand off control. We used the existing market theories to develop a solution for pricing of a unit of bandwidth of each network based on the marginal cost of the product. The client preferences with regard to available networks are also modeled in our network market model. On the other hand, network providers also adjust their product offering according to the market price. We prove that the user and bandwidth assignment made on the basis of this model where all agents have rational behavior is Pareto optimum that maximizes the utility of networks and clients.

There are several ways for bandwidth allocation for users acting based on policy of network administrators in computer networks. Due to the diversity of users and so amount of bandwidth usage per user, providing suitable bandwidth rate to meet their needs in various situations play an important role in terms of performance and implementation of bandwidth management systems. In this paper, we propose a dynamic and balanced approach, called normal weight allocation for determining amount of bandwidth for each user taking into account the importance of user in caomparision with other online concurrent users. In this regard, to obtain a user weight as the importance of user, we apply Fuzzy AHP technique for eliciting indecisive expert ideas. Ease of implementation and taking the advantage of maximal usage of available bandwidth are the features of the proposed approach.

An important problem for the WiMAX networks is how to provide a guaranteed quality of service for applications. A key aspect of this problem is how BSs should share bandwidth capacity between different classes of traffic. This decision needs to be made for each incoming packet, and is known as the packet scheduling problem.A major challenge in packet scheduling is that the behavior of each traffic class may not be known in advance, and can vary dynamically.In this paper, we describe how we have modeled the packet scheduling problem as an application for reinforcement learning (RL). We demonstrate how our RL approach can learn scheduling policies that satisfy the quality of service requirements of multiple traffic classes under a variety of conditions. The proposed solution has been designed to have an ability to accommodate integrated traffic in the networks with effective scheduling schemes. A series of simulation experiments have been carried out to evaluate the performance of the proposed scheduling algorithm. The results reveal that the proposed solution performs effectively to the integrated traffic composed of messages with or without time constraints and achieves proportional fairness among different types of traffic.

In this paper, a model based on meta-heuristic algorithms for optimal allocation of IoT resources based on fog calculations is proposed. In the proposed model, the user request is first given to the system as a workflow; For each request, the resource requirements (processing power, storage memory, and bandwidth) are first extracted. This component determines the requested traffic status of the application in terms of real-time. If the application is not real-time and is somewhat resistant to latency, the request will be referred to the cloud environment, but if the application needs to respond promptly and is sensitive to latency, it will be dealt with as a fog calculation. It will be written to one of the Cloudletes. In this step, in order to select the best solution in allocating resources to serve the users of the IoT environment, the ant milk optimization algorithm was used. The proposed method is simulated in MATLAB software environment and to evaluate its performance, five indicators of fog cells energy consumption, response time, fog cell imbalance, latency and bandwidth have been used. The results show that the proposed method reduces the energy consumption, latency rate in fog cells, bandwidth consumption rate, load balance rate and response time compared to the base design (ROUTER) 22, 18, 12, 22 and 47, respectively. Percentage has improved.

Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will be merged, and vice versa, they will remain fine with severe variability. Bandwidth variation can be effective in upscaling results. Therefore, determining the optimal bandwidth in this method is essential. For each bandwidth, the upscaled model has a number of upscaled blocks and an upscaling error. Obviously, higher thresholds or bandwidths cause a lower number of upscaled blocks and a higher sum of squares error (SSE). On the other hand, using the smallest bandwidth, the upscaled model will remain in a fine scale, and there will be practically no upscaling. In this work, different approaches are used to determine the optimal bandwidth or threshold for upscaling. Investigation of SSE changes, the intersection of two charts, namely SSE and the number of upscaled block charts, and the changes of SSE values versus bandwidths, are among these approaches. In this particular case, if the goal of upscaling is to minimize the upscaling error, the intersection method will obtain a better result. Conversely, if the purpose of upscaling is computational cost reduction, the SSE variation approach will be more appropriate for the threshold setting.

In this paper a rectangular dielectric resonator antenna (DRA) fed by a microstrip line is studied. Therefore, at first radiation performance of DRA is studied, and the improvement techniques are reviewed. Then propose a novel configuration for broadening of the impedance bandwidth. In the proposed arrangement, by using multi-segment structure with different dimensions, increase the antenna impedance bandwidth. However for decreasing the design parameters, variations limited to the segments width. So, with the non-uniform configuration by variable width, it is possible to create remarkable increase in frequency bandwidth. Utilizing the symmetrical seven-segment DRA and skillfully varying its aspect ratio, an appropriate structure is obtained that illustrates more than 52% impedance bandwidth for S11>10.