Cache "less for more" in information-centric networks (extended version)

Ubiquitous in-network caching is one of the key aspects of information-centric networking (ICN) which has received widespread research interest in recent years. In one of the key relevant proposals known as Content-Centric Networking (CCN), the premise is that leveraging in-network caching to store content in every node along the delivery path can enhance content delivery. We question such an indiscriminate universal caching strategy and investigate whether caching less can actually achieve more. More specifically, we study the problem of en route caching and investigate if caching in only a subset of nodes along the delivery path can achieve better performance in terms of cache and server hit rates. We first study the behavior of CCN's ubiquitous caching and observe that even naïve random caching at a single intermediate node along the delivery path can achieve similar and, under certain conditions, even better caching gain. Motivated by this, we propose a centrality-based caching algorithm by exploiting the concept of (ego network) betweenness centrality to improve the caching gain and eliminate the uncertainty in the performance of the simplistic random caching strategy. Our results suggest that our solution can consistently achieve better gain across both synthetic and real network topologies that have different structural properties. We further find that the effectiveness of our solution is correlated to the precise structure of the network topology whereby the scheme is effective in topologies that exhibit power law betweenness distribution (as in Internet AS and WWW networks)

Study and analysis of mobility, security, and caching issues in CCN

Existing architecture of Internet is IP-centric, having capability to cope with the needs of the Internet users. Due to the recent advancements and emerging technologies, a need to have ubiquitous connectivity has become the primary focus. Increasing demands for location-independent content raised the requirement of a new architecture and hence it became a research challenge. Content Centric Networking (CCN) paradigm emerges as an alternative to IP-centric model and is based on name-based forwarding and in-network data caching. It is likely to address certain challenges that have not been solved by IP-based protocols in wireless networks. Three important factors that require significant research related to CCN are mobility, security, and caching. While a number of studies have been conducted on CCN and its proposed technologies, none of the studies target all three significant research directions in a single article, to the best of our knowledge. This paper is an attempt to discuss the three factors together within context of each other. In this paper, we discuss and analyze basics of CCN principles with distributed properties of caching, mobility, and secure access control. Different comparisons are made to examine the strengths and weaknesses of each aforementioned aspect in detail. The final discussion aims to identify the open research challenges and some future trends for CCN deployment on a large scale

Adaptive Caching Strategy Based on Big Data Learning in ICN

In-network caching, a typical feature of information centric networking (ICN) architecture, has played an important role on the network performance. Existing caching management strategies mainly focus on minimizing the redundancy content by exploiting either node data or content data respectively, which may not lead to effectively improve the caching performance, as there is no consideration on supplementary action of these two types of data. In this paper, the correlation between node data and content data brought by the big data are analyzed and mined to determine whether the selected content are cached in a few suitable nodes, and a Big data driven Adaptive In-network Caching management strategy (BAIC) is proposed. Driven by the current state of node and content, a novel multidimensional state attribution data model including network, node and content data is proposed. Based on the data model, the mapping relationship between the status data and the matching relationship value is further analyzed and mined. And then utilizing this mapping relationship function, the matching algorithm to predict the matching relationship between the node and the content in the next time period is proposed. The simulation experiments demonstrate that the proposed BAIC has significantly improved the network performance

Novel applications and contexts for the cognitive packet network

Autonomic communication, which is the development of self-configuring, self-adapting, self-optimising and self-healing communication systems, has gained much attention in the network research community. This can be explained by the increasing demand for more sophisticated networking technologies with physical realities that possess computation capabilities and can operate successfully with minimum human intervention. Such systems are driving innovative applications and services that improve the quality of life of citizens both socially and economically. Furthermore, autonomic communication, because of its decentralised approach to communication, is also being explored by the research community as an alternative to centralised control infrastructures for efficient management of large networks. This thesis studies one of the successful contributions in the autonomic communication research, the Cognitive Packet Network (CPN). CPN is a highly scalable adaptive routing protocol that allows for decentralised control in communication. Consequently, CPN has achieved significant successes, and because of the direction of research, we expect it to continue to find relevance. To investigate this hypothesis, we research new applications and contexts for CPN. This thesis first studies Information-Centric Networking (ICN), a future Internet architecture proposal. ICN adopts a data-centric approach such that contents are directly addressable at the network level and in-network caching is easily supported. An optimal caching strategy for an information-centric network is first analysed, and approximate solutions are developed and evaluated. Furthermore, a CPN inspired forwarding strategy for directing requests in such a way that exploits the in-network caching capability of ICN is proposed. The proposed strategy is evaluated via discrete event simulations and shown to be more effective in its search for local cache hits compared to the conventional methods. Finally, CPN is proposed to implement the routing system of an Emergency Cyber-Physical System for guiding evacuees in confined spaces in emergency situations. By exploiting CPN’s QoS capabilities, different paths are assigned to evacuees based on their ongoing health conditions using well-defined path metrics. The proposed system is evaluated via discrete-event simulations and shown to improve survival chances compared to a static system that treats evacuees in the same way.Open Acces

On the design of efficient caching systems

Content distribution is currently the prevalent Internet use case, accounting for the majority of global Internet traffic and growing exponentially. There is general consensus that the most effective method to deal with the large amount of content demand is through the deployment of massively distributed caching infrastructures as the means to localise content delivery traffic. Solutions based on caching have been already widely deployed through Content Delivery Networks. Ubiquitous caching is also a fundamental aspect of the emerging Information-Centric Networking paradigm which aims to rethink the current Internet architecture for long term evolution. Distributed content caching systems are expected to grow substantially in the future, in terms of both footprint and traffic carried and, as such, will become substantially more complex and costly. This thesis addresses the problem of designing scalable and cost-effective distributed caching systems that will be able to efficiently support the expected massive growth of content traffic and makes three distinct contributions. First, it produces an extensive theoretical characterisation of sharding, which is a widely used technique to allocate data items to resources of a distributed system according to a hash function. Based on the findings unveiled by this analysis, two systems are designed contributing to the abovementioned objective. The first is a framework and related algorithms for enabling efficient load-balanced content caching. This solution provides qualitative advantages over previously proposed solutions, such as ease of modelling and availability of knobs to fine-tune performance, as well as quantitative advantages, such as 2x increase in cache hit ratio and 19-33% reduction in load imbalance while maintaining comparable latency to other approaches. The second is the design and implementation of a caching node enabling 20 Gbps speeds based on inexpensive commodity hardware. We believe these contributions advance significantly the state of the art in distributed caching systems

Congestion-aware caching and search in information-centric Networks

ABSTRACT The performance of in-network caching in informationcentric networks, and of cache networks more generally, is typically characterized by network-centric performance metrics such as hit rate and hop count, with approaches to locating and caching content evaluated and optimized for these metrics. We believe that user-centric performance metrics, in particular the delay from when a content request is made by the user to the time at which the requested content has been completely downloaded, are also important. For such metrics, performance is often determined by link capacity constraints and network congestion. We investigate network cache management and search policies that account for path-level (content-server to content-requestor) congestion and file popularity in order to directly minimize user-centric, content-download delay. Through simulation, we find that our policies yield significantly better download delay performance than existing policies, even though these existing policies provide better performance according to traditional metrics such as cache hit rate and hop count

Performance Analysis and Optimisation of In-network Caching for Information-Centric Future Internet

The rapid development in wireless technologies and multimedia services has radically shifted the major function of the current Internet from host-centric communication to service-oriented content dissemination, resulting a mismatch between the protocol design and the current usage patterns. Motivated by this significant change, Information-Centric Networking (ICN), which has been attracting ever-increasing attention from the communication networks research community, has emerged as a new clean-slate networking paradigm for future Internet. Through identifying and routing data by unified names, ICN aims at providing natural support for efficient information retrieval over the Internet. As a crucial characteristic of ICN, in-network caching enables users to efficiently access popular contents from on-path routers equipped with ubiquitous caches, leading to the enhancement of the service quality and reduction of network loads. Performance analysis and optimisation has been and continues to be key research interests of ICN. This thesis focuses on the development of efficient and accurate analytical models for the performance evaluation of ICN caching and the design of optimal caching management schemes under practical network configurations. This research starts with the proposition of a new analytical model for caching performance under the bursty multimedia traffic. The bursty characteristic is captured and the closed formulas for cache hit ratio are derived. To investigate the impact of topology and heterogeneous caching parameters on the performance, a comprehensive analytical model is developed to gain valuable insight into the caching performance with heterogeneous cache sizes, service intensity and content distribution under arbitrary topology. The accuracy of the proposed models is validated by comparing the analytical results with those obtained from extensive simulation experiments. The analytical models are then used as cost-efficient tools to investigate the key network and content parameters on the performance of caching in ICN. Bursty traffic and heterogeneous caching features have significant influence on the performance of ICN. Therefore, in order to obtain optimal performance results, a caching resource allocation scheme, which leverages the proposed model and targets at minimising the total traffic within the network and improving hit probability at the nodes, is proposed. The performance results reveal that the caching allocation scheme can achieve better caching performance and network resource utilisation than the default homogeneous and random caching allocation strategy. To attain a thorough understanding of the trade-off between the economic aspect and service quality, a cost-aware Quality-of-Service (QoS) optimisation caching mechanism is further designed aiming for cost-efficiency and QoS guarantee in ICN. A cost model is proposed to take into account installation and operation cost of ICN under a realistic ISP network scenario, and a QoS model is presented to formulate the service delay and delay jitter in the presence of heterogeneous service requirements and general probabilistic caching strategy. Numerical results show the effectiveness of the proposed mechanism in achieving better service quality and lower network cost. In this thesis, the proposed analytical models are used to efficiently and accurately evaluate the performance of ICN and investigate the key performance metrics. Leveraging the insights discovered by the analytical models, the proposed caching management schemes are able to optimise and enhance the performance of ICN. To widen the outcomes achieved in the thesis, several interesting yet challenging research directions are pointed out

A review on green caching strategies for next generation communication networks

© 2020 IEEE. In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching