CONCERT: A Context-Adaptive Content Ecosystem Under Uncertainty

CONCERT的目标是开发一个内容生态系统，包括所有相关的参与者，这将能够在不确定的高度动态条件下执行智能内容和网络适配。这个生态系统将以新兴的以信息/内容为中心的网络技术为基础，这些技术支持固有的网络内内容操作。该项目将考虑以下两个应用领域的不确定性：a）基于用户生成内容的社交媒体网络和B）类似CDN的专业内容分发。将解决三个方面的不确定性：最终用户的服务需求多样化和不断变化，可能对内容生态系统产生不利影响的威胁，以及特定参与者为降低成本而可以利用的机会。为了管理和利用这些不确定性方面，CONCERT定义了一个二维内容和网络适配框架，该框架跨层和跨播放器操作。首先，任何单个自适应动作的决策都需要考虑来自内容应用层和底层网络的上下文信息。其次，我们考虑联合内容和网络适配，以同时实现优化的服务性能和网络资源利用率。最后，一些复杂的不确定性场景需要不同生态系统参与者之间协调的内容和网络适应。在这种情况下，不一致甚至相互冲突的适应目标和不同程度的背景知识需要协调，这是关键的研究问题，为了实现能够应对这些不同的不确定性的适应解决方案，该项目将开发先进的学习、决策和谈判技术。需要学习来根据所获得的上下文知识导出准确的系统行为模式。这将推动决策职能，采取最适当的适应行动，解决这些不确定性。协商技术需要解决内容生态系统中不同参与者之间特定内容/网络适配目标之间的潜在争斗。该项目将考虑集中式和分布式方法，其中关于适应行动的学习和决策过程可以在中央适应域控制器或以分散方式跨多个网络元素进行。在后一种情况下，新兴的以信息/内容为中心的网络将变得更加智能，内容感知设备根据自己的上下文知识进行自适应，但通过协调，以实现全局接近最优和稳定。

The CONCERT objective is to develop a content ecosystem, encompassing all relevant players, which will be able to perform intelligent content and network adaptation in highly dynamic conditions under uncertainty. This ecosystem will have as basis emerging information-/content-centric networking technologies which support intrinsic in-network content manipulation. The project will consider uncertainty aspects in the following two application domains: a) social media networks based on user generated content and b) CDN-like professional content distribution. Three dimensions of uncertainties will be addressed: heterogeneous and changing service requirements by end users, threats that may have adverse impacts on the content ecosystem, as well as opportunities that can be exploited by specific players in order to have their costs reduced. In order to manage and exploit these uncertainty aspects, CONCERT defines a two-dimensional content and network adaptation framework that operates both cross-layer and cross-player. First, the decision on any single adaptation action needs to take into account context information from both the content application layer and the underlying network. Second, we consider joint content and network adaptation in order to simultaneously achieve optimised service performance and network resource utilisation. Finally, some complex uncertainty scenarios require coordinated content and network adaptation across different ecosystem players. In this case, inconsistent or even conflicting adaptation objectives and different levels of context knowledge need to be reconciled and are key research issues.In order to achieve adaptation solutions capable of coping with these different uncertainties, the project will develop advanced learning, decision-making and negotiation techniques. Learning is required for deriving accurate system behavioural patterns according to the acquired context knowledge. This will then drive decision-making functions for taking the most appropriate adaptation actions to address these uncertainties. Negotiation techniques are required for resolving potential tussles between specific content/network adaptation objectives by different players in the content ecosystem. The project will consider both centralised and distributed approaches in which learning and decision-making processes on adaptation actions can be performed either at the central adaptation domain controller or in a decentralised manner across multiple network elements. In the latter case, emerging information-/content-centric networks will become much more intelligent, with content-aware devices performing self-adaptation according to their own context knowledge but through coordination in order to achieve global near-optimality and stability.