Analysis and Modelling of Group-based Communication in Internet Applications for improved Edge Caching

基于组的通信是一组用户相互通信的一种通信范式，它扩展了互联网上的经典通信形式(一对一、一对多)。对于许多互联网服务来说，通信组的成员是明确已知的。此外，还有隐式通信组，其可以自发地形成并且可以例如基于移动性或兴趣动态地改变。在这样的群组中，存在着明显不同的通信行为，例如，由于合作伙伴的数量较多，通信速度加快，并且由于分发到群组内的所有接收者，用户生成内容(UGC)成倍增加。流行的、快节奏的基于群组的通信对(移动)网络造成了高负载。传统的缓存和缓存算法依赖于(当前)内容的流行程度，不能有效地使用，因为它们是针对流行内容的海量访问而定制的，没有考虑UGC的动态生命周期和向通信组的分发。UGCS的边缘缓存仍显示出进一步减少网络流量的潜力。通过考虑关于通信组的附加知识和组内通信的特征，可以优化缓存决策，从而通过更短的访问时间来缓解网络并改善体验质量(QOE)。在本研究项目中，将开发新的用于群组通信和UGCS的边缘缓存机制，以降低网络负载。这里，重点放在新内容的缓存替换算法上，而不是缓存内容的放置算法上。缓存决策应考虑例如群的规模、群的联合移动性或单个群成员的活动模式。具体方法将在项目中进行评估。我们的目标是了解基于组的通信并对其进行建模，并根据这些知识和模型比现有的缓存方法更好地降低网络负载，同时保持基于组的通信的高QOE。

Group-based communication, in which a group of users communicates with each other, is a communication paradigm, which extends the classical forms of communication in the Internet (one-to-one, one-to-many). For many Internet services, the members of a communication group are explicitly known. Additionally, there are implicit communication groups, which can form spontaneously and can change dynamically, e.g., based on mobility or interests. In such groups, there is a significantly different communication behavior, e.g., the communication speeds up due to the higher number of partners, and user-generated contents (UGCs) multiply due to the distribution to all recipients within the group.The popular, fast-paced group-based communication creates a high load on (mobile) networks. Classical caching and caching algorithms, which rely on the (current) popularity of content, cannot be used effectively, because they are tailored to massive access on popular contents and do not consider the dynamic life cycles of UGCs and the distribution to communication groups. Edge caching of UGCs still shows potentials to further reduce network traffic. By considering additional knowledge about the communication groups and the characteristics of the communication within the group, caching decision can be optimized, which relieves the network and improves the Quality of Experience (QoE) by shorter access times. In this research project, novel edge caching mechanisms for group-based communications and UGCs will be developed, which can reduce the network load. Here, the focus is on cache replacement algorithms for new contents and not on placement algorithms for cached contents. Caching decisions shall consider, for example, the group size, the joint mobility of the group, or activity patterns of individual group members. Concrete methods will be evaluated in the project. The goal is to understand and model group-based communication and – due to this knowledge and models – reduce the network load better than existing caching approaches, while maintaining a high QoE for group-based communication.