Abstract
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.
Highlights
In recent years, network traffic has increased significantly, which is a direct cause of resource allocation problems
We present our solution to address the lack of appropriate mechanisms to ensure quality of experience (QoE)
Simulations were performed to analyse the number of unsatisfied users after applying three bandwidth allocation algorithms: the max-min algorithm, the proportional fairness scheme and our algorithm
Summary
Network traffic has increased significantly, which is a direct cause of resource allocation problems. Network traffic is expected to continue to grow in the few years, so the problem of fair network bandwidth allocation and the associated abandonment of applications by users will continue to be an important issue. Quality of service (QoS) parameters such as packet loss, latency, jitter and bandwidth were used to measure user satisfaction towards a service or application. When there are currently so many different devices and applications in a network, requiring completely different technical parameters, such measurement is not unambiguous and is insufficient. A need has emerged for another way of measuring a user’s satisfaction with a service based more on the subjective opinion of the user or on the user’s experience of using the service
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