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CONCERT: A Context-Adaptive Content Ecosystem Under Uncertainty

CONCERT：不确定性下的上下文自适应内容生态系统

基本信息

批准号：
EP/L018535/1
负责人：
George Pavlou
金额：
$ 38.72万
依托单位：
University College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FL018535%2F1
关键词：
CONCERT Context Adaptive Content Ecosystem

项目摘要

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.

CONCERT的目标是开发一个包含所有相关参与者的内容生态系统，该生态系统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应。该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，支持内在的网络内内容操作。该项目将考虑以下两个应用领域的不确定性方面：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：最终用户异构且不断变化的服务需求、可能对内容生态系统产生不利影响的威胁，以及特定参与者可以利用的机会来降低成本。为了管理和利用这些不确定性方面，CONCERT 定义了一个跨层和跨玩家操作的二维内容和网络适应框架。首先，任何单个适应操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。最后，一些复杂的不确定性场景需要跨不同生态系统参与者协调内容和网络适应。在这种情况下，不一致甚至冲突的适应目标和不同水平的背景知识需要得到协调，这是关键的研究问题。为了获得能够应对这些不同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来解决这些不确定性。需要协商技术来解决内容生态系统中不同参与者的特定内容/网络适应目标之间的潜在冲突。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上执行，也可以在多个网络元素上以分散的方式执行。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，但通过协调来实现全局接近最优和稳定性。