Ensuring the QoE-Related Fairness to Reduce the User Abandonment Ratio

Nowadays, it is quite a challenge for app owners to keep users engaged with an app. Currently, the level of user abandonment is one of the key parameters that application owners are interested in. To meet these challenges, we conduct an extended study of a previously proposed solution that significantly reduces the abandonment rate of a given application. The investigated solution is based on the methods of fairness using the QoE and QoS approach. This paper shows that application abandonment ratios can be reduced by using an appropriate approach to fair bandwidth allocation. Adjusting the bandwidth allocation to users, taking into account the quality of the user experience, has a more effective effect on reducing app abandonment ratios than if quality of service is taken into account. This is because the users make the decision to abandon the application based on their feelings rather than technical parameters. In order to effectively reduce application abandonment ratios, a suitable bandwidth allocation algorithm must be used. This paper presents the impact of using different algorithms on the abandonment ratio and compares the popularly used algorithms and the previously proposed bandwidth allocation algorithm.

High Throughput Data Relay in UAV Wireless Networks

As a result of their high mobility and reduced cost, Unmanned Aerial Vehicles (UAVs) have been found to be a promising tool in wireless networks. A UAV can perform the role of a base station as well as a mobile relay, connecting distant ground terminals. In this paper, we dispatch a UAV to a disaster area to help relay information for victims. We involve a bandwidth efficient technique called the Dual-Sampling (DS) method when planning the UAV flight trajectory, trying to maximize the data transmission throughput. We propose an iterative algorithm for solving this problem. The victim bandwidth scheduling and the UAV trajectory are alternately optimized in each iteration, meanwhile a power balance mechanism is implemented in the algorithm to ensure the proper functioning of the DS method. We compare the results of the DS-enabled scheme with two non-DS schemes, namely a fair bandwidth allocation scheme and a bandwidth contention scheme. The DS scheme outperforms the other two non-DS schemes regarding max-min average data rate among all the ground victims. Furthermore, we derive the theoretical optimal performance of the DS scheme for a given scenario, and find that the proposed approach can be regarded as a general method to solve this optimization problem. We also observe that the optimal UAV trajectory for the DS scheme is quite different from that of the non-DS bandwidth contention scheme.

Joint AP Association and Bandwidth Allocation Optimization Algorithm in High-Dense WLANs

Regarding access point (AP) overload and performance anomaly which is caused by mobile terminals with different bitrates, a joint AP association and bandwidth allocation optimization algorithm is presented in this paper. Meanwhile, load balancing and proportional fairness are analyzed and formulated as an optimization model. Then, we present a Fair Bandwidth Allocation algorithm based on clients’ Business Priority (FBA-BP), which allocates bandwidth based on the bandwidth demand of clients and their business priority. Furthermore, we propose a Categorized AP Association algorithm based on clients’ demands (CAA-BD), which classifies APs by different types of clients and chooses an optimal associating AP for a new client according to AP categories and the aggregated demand transmission time that are calculated by the FBA-BP algorithm. The CAA-BD can achieve load balance and solve the performance anomaly caused by multi-rate clients coexisting. The simulation results show that our proposed algorithm obtains significant performance in terms of AP utilization, throughput, transmission delay and channel fairness in different client density levels compared with the categorized and Strong Signal First (SSF) algorithms.