A Dynamic Caching Algorithm Based on the Pheromone for Content Distribution Networks

Content Delivery Networks (CDNs) have emerged as a dominant mechanism to deliver content over the Internet. Despite their importance, to our best knowledge, large-scale analysis of CDN cache performance is lacking in prior literature. A CDN serves many content publishers simultaneously and thus has unique workload characteristics; it typically deals with extremely large content volume and high content diversity from multiple content publishers. CDNs also have unique performance metrics; other than hit ratio, CDNs also need to minimize network and disk load on cache servers. In this paper, we present measurement and analysis of caching workload at a large commercial CDN. Using detailed logs from four geographically distributed CDN cache servers, we analyze over 600 million content requests accounting for more than 1.3 petabytes worth of traffic. We analyze CDN workload from a wide range of perspectives, including request composition, size, popularity, and temporal dynamics. Using real-world logs, we also evaluate cache replacement algorithms, including two enhancements designed based on our CDN workload analysis: N-hit and content-aware caching. The results show that these enhancements achieve substantial performance gains in terms of cache hit ratio, disk load, and origin traffic volume.

The development of Network Function Virtualization (NFV) and Software Defined Networks (SDN) standards is an opportunity for Mobile Network Operators (MNOs) to deploy Content Delivery Network (CDN) functionalities into the mobile network edge, such as Base Stations (BSs). In this paper, we investigated the content placement problem for the BS-based wireless CDN system. We call the storage resources implemented on BSs as storage helpers. Due to the limited helper storage capacity and the limited user population served per BS, helpers exhibit low hit ratio comparing to traditional CDN edge servers serving a wide area. Then, cooperation is a suitable means to enhance the performance of the wireless CDN system. We propose that BSs close to each other cooperate in replicating content and replying user requests. We formulate the optimum content placement problem to minimize the traffic pressure on mobile network gateways, and show the problem complexity is NP-Hard. We then transform the problem into a multiple-Maximum Weighted Independent Set problem, and propose a heuristic algorithm. The evaluation shows that the hit ratio is improved by our algorithm comparing to the traditional Least Frequently Used (LFU) policy without cooperation.

The presence of bottlenecks in the Internet reduces the performance of content delivery in typical client-server applications such as Web browsing and media streaming. Caching and server farm architectures have been a good solution to this problem since the World Wide Web became very popular, but now they are not enough to support new e-business solutions. Content delivery networks (CDNs) distribute content by placing it on several surrogate servers across the Internet and try to overcome these bottlenecks. In CDN scenarios a good request routing algorithm selects the best surrogate for a client's request; it makes its decision using metrics received by the network and the surrogate. Typical metrics are network latency, hop count, available Internet bandwidth, and surrogate load. We analyze the impact of different request routing algorithms on the delivery performance of CDNs. A new request routing algorithm, called WSE (worst surrogate exclusion), is proposed. Worst surrogate exclusion excludes those surrogates that provide the client with low performance and prevents surrogates overloading. Simulation results show that WSE can reduce users average response time and efficaciously exploit the CDN's capacity.

Web caching and replication tune capacity with performance and they have become essential components of the Web. In practice, caching and replication techniques have been applied in proxy servers and Content Distribution Networks (CDNs) respectively. In this paper, we investigate the benefits of integrating caching policies on a CDN’ s infrastructure. Using a simulation testbed, our results indicate that there is much room for performance improvement in terms of perceived latency, hit ratio and byte hit ratio. Moreover, we show that the combination of caching with replication fortifies CDNs against flash crowd events.

Along with the continuing evolution of the Internet and its applications, Content Delivery Networks (CDNs) have become a hot topic with both opportunities and challenges. CDNs were mainly proposed to solve content availability and download time issues by delivering content through edge cache servers deployed around the world. In our previous work, we presented a novel CDN architecture based on a Fog computing environment as a promising solution for real-time applications. In such architecture, we proposed to use a name-based routing protocol following the Information Centric Networking (ICN) approach, with a popularity-based caching strategy to guarantee overall delivery performance. To validate our design principle, we have implemented the proposed Fog-based CDN architecture with its major protocol components and evaluated its performance, as shown through this article. On the one hand, we have extended the Optimized Link-State Routing (OLSR) protocol to be content aware (CA-OLSR), i.e., so that it uses content names as routing labels. Then, we have integrated CA-OLSR with the popularity-based caching strategy, which caches only the most popular content (MPC). On the other hand, we have considered two similar architectures for conducting performance comparative studies. The first is pure Fog-based CDN implemented by the original OLSR (IP-based routing) protocol along with the default caching strategy. The second is a classical cloud-based CDN implemented by the original OLSR. Through extensive simulation experiments, we have shown that our Fog-based CDN architecture outperforms the other compared architectures. CA-OLSR achieves the highest packet delivery ratio (PDR) and the lowest delay for all simulated numbers of connected users. Furthermore, the MPC caching strategy shows higher cache hit rates with fewer numbers of caching operations compared to the existing default caching strategy, which caches all the pass-by content.

Content Distribution Networks (CDN) appeared a decade ago as a method for reducing latencies, improving performance experienced by Internet users, and limiting the effect of flash-crowds, so as balance load in servers. Content Distribution has evolved in different ways (e.g. cloud computing structures and video streaming distribution infrastructures). The solution proposed in early CDN was the location of several controlled caching servers close to clients, organized and managed by a central control system. Many companies deployed their own CDN infrastructure– and so demonstrating the resulting effectiveness. However, the business model of these networks has evolved from the distribution of static web objects to video streaming. Many aspects of deployment and implementation remain proprietary, evidencing the lack of a general CDN model, although the main design concepts are widely known. In this work, the authors represent the structure of a CDN and the performance of some of its parameters, using queuing theory, simplifying the redirection schema and studying the elements that could determine the improvement in performance. The main contribution of the work is a general expression for a CDN environment and the relationship between different variables like caching hit ratios, network latency, number of surrogates, and server capacity; this proves that the use of CDN outperform the typical client/server architecture.

This paper describes issues in current multicast content delivery network (CDN) architecture and presents a framework for multicast CDN to satisfy the requirements for content delivery service (Hayashi et al., 2005). In our experience, requirements for CDN (Hayashi et al., 2005) are not perfectly covered by possible current methods using current group management protocols such as IGMP (B. Cain et al., 2002) and MLD (R. Vida et al., 2004). Therefore, we propose a new framework for multicast CDN to support authentication authorization & accounting (AAA) and QoS control

Content-based services are gaining tremendous popularity recently with the proliferation of a wide range of contents. Traditionally, hosting and distribution of these ubiquitous contents are accomplished using content distribution networks (CDNs). CDNs distribute contents in multiple hosting locations for load balancing, availability, and easy access. However, scalability and cost of CDNs are becoming major challenges due to the increase of content-based services. To combat these problems, peer-to-peer (P2P) systems are being considered in combination with CDN to complement each other in a hybrid system. Research works and practical deployments have shown that hybrid CDN–P2P systems are feasible, inexpensive, and scalable. However, P2P-based content distribution systems are known to consume more system-wide energy than traditional CDNs. Hence, energy efficiency of such a hybrid system must be taken into consideration before wider implementation. In our study, we analyze the energy consumption of a hybrid CDN–P2P system in an IP-over-WDM network and show that, due to its hybrid nature, it is possible to exploit the P2P system to significantly reduce load on the CDN and at the same time constrain—and in some cases reduce—energy consumption. We propose energy-aware as well as energy-unaware content source selection mechanisms to help service providers achieve this win–win situation. Using simulations, we show that, for example, in case of a moderately popular content the server load can be reduced by 30%–40% while reducing the system-wide energy consumption by 10%–20% when compared with a traditional CDN.

Content delivery network (CDN) with a high quality-of-service (QoS) requirement deals with three challenging problems: 1) a cache server deployment problem to determine where to locate cache servers, 2) a request routing problem to settle which cache server serves a user request, and 3) a content replication problem to decide which content is stored in a cache server. Cooperation among cache servers significantly improves the user QoS by increasing the cached content diversity of the network. Since the aforementioned problems are tightly coupled, we formulate a new CDN model which jointly considers all the three problems under the cooperative content replication with optimal solutions using integer linear programming. As the joint optimization problem is an NP-hard problem, we propose a greedy heuristic algorithm which is close to the optimal solution. We consider two scenarios for application of the algorithm, where the popularities of contents are identical and are different among nodes. The performance of the algorithm is investigated on the actual topology sampled from the Level 3 CDN network. By increasing the cached content diversity in the network, the joint optimization problem under the cooperative content replication shows higher performance than that of the non-cooperation case.

Content delivery networks (CDNs) provide an efficient support for serving http and streaming media content white minimizing the network impact of content delivery as well as overcoming the server overload problem. For serving the large documents and media files, there is an additional problem of the original content distribution across the CDN edge servers. We propose an algorithm, called ALM-fastreplica, for optimizing replication of large files across the edge servers in CDNs. The original file is partitioned into k subfiles, and each subfile is replicated via a correspondingly constructed multicast tree. Nodes from the different multicast trees use additional cross-nodes connections to exchange their corresponding subfiles such that each node eventually receives an entire file. This new replication method significantly reduces file replication time, up to 5-15 times compared to the traditional unicast (or point-to-point) schema. Since a single node failure in the multicast tree during the file distribution may impact the file delivery to a significant number of nodes, it is important to design an algorithm which is able to deal with node failures. We augment ALM-FastReplica with an efficient reliability mechanism, that can deal with node failures by making local repair decisions within a particular replication group of nodes. Under the proposed algorithm, the load of the failed node is shared among the nodes of the corresponding replication group, making the performance degradation gradual.

With Online Social Networking (OSN) services coming to prominence as a major platform for the popularization of Web content, recent research has focused on using information gleaned from these services to improve the performance of Content Distribution Networks (CDN). In this paper we find that contrary to popular belief, the simple cache replacement policy LRU outperforms methods based on OSN input. To establish this we propose an OSN-assisted caching strategy which we evaluate using a large Twitter dataset and through simulation. Our results show that vanilla LRU mostly outperforms the OSN-aided mechanisms. We study the reasons for this and find that if at any time there is a large enough percentage of highly popular content, which becomes popular within a short enough time span, CDN can do well by just following an LRU principle. While we do not claim generalizability to other workloads, or other caching architectures on the Internet, our results are important as they apply to the common use-case and show that simple algorithms do quite well.

Content streaming is the dominant application in today's Internet, which is typically distributed via content delivery networks (CDNs). CDNs usually use caching as a means to reduce user access latency so as to enable faster content downloads. Typical analysis of caching systems either focuses on content admission, which decides whether to cache a content, or content eviction to decide which content to evict when the cache is full. This paper instead proposes a novel framework that can simultaneously learn both content admission and content eviction for caching in CDNs. To attain this goal, we first put forward a lightweight architecture for content next request time prediction. We then leverage reinforcement learning (RL) along with the prediction to learn the time-varying content popularities for content admission, and develop a simple threshold-based model for content eviction. We call this new algorithm RL-Belady (RLB). In addition, we address several key challenges to design learning-based caching algorithms, including how to guarantee lightweight training and prediction with both content eviction and admission in consideration, limit memory overhead, reduce randomness and improve robustness in RL stochastic optimization. Our evaluation results using $3$ production CDN datasets show that RLB can consistently outperform state-of-the-art methods with dramatically reduced running time and modest overhead.

A Content Delivery Network (CDN) is a dynamic and complex service system. It causes a huge amount of traffic on the network infrastructure of Internet Service Providers (ISPs). Oftentimes, CDN providers and ISPs struggle to find an efficient and appropriate way to cooperate for mutual benefits. This challenge is key to push the quality of service (QoS) for the end-user. We model, simulate, and optimize the behavior of a CDN to provide cooperative solutions and to improve the QoS. Therefor, we determine reasonable server locations, balance the amount of servers and improve the user assignments to the servers. These aspects influence run time effects like caching at the server, response time and network load at specific links. Especially, user request history and profiles are considered to improve the overall performance. Since we consider multiple objectives, we aim to provide a diverse set of pareto optimal solutions using simulation based optimization.

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7-14 days in young adults with type 1 diabetes. In addition, person-level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined. In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring over 6-14 days. At baseline, participants completed the Psychomotor Vigilance Test, the Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries. Forty-six participants (mean age, 22.3 ± 3.2 years) wore a wrist actigraph and underwent continuous glucose monitoring concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences; r = .33, P = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences; r = .50, P = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for type 1 diabetes duration (P > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, P = .010, pr2 = 0.40) after controlling for type 1 diabetes duration and accounting for higher daytime sleepiness. Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with type 1 diabetes. Sleep habits in this population may explain higher glucose variability, and optimizing sleep may improve overall diabetes management. Griggs S, Hickman RL Jr, Strohl KP, Redeker NS, Crawford SL, Grey M. Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes. J Clin Sleep Med. 2021;17(9):1865-1874.

In order to optimize energy efficiency, network operators try to switch off as many network devices as possible. Recently, there is a trend to introduce content caches as an inherent capacity of network equipment, with the objective of improving the efficiency of content distribution and reducing the network congestion. In this work, we study the impact of using in-network caches and content delivery network (CDN) cooperation on an energy-efficient routing. We formulate this problem as Energy Efficient Content Distribution, we propose an integer linear program (ILP) and a heuristic algorithm to solve it. The objective of this problem is to find a feasible routing, so that the total energy consumption of the network is minimized while the constraints given by the demands and the link capacity are satisfied. We exhibit for which the range of parameters (size of caches, popularity of content, demand intensity, etc.) it is useful to use caches. Experimental results show that by placing a cache on each backbone router to store the most popular content, along with well choosing the best content provider server for each demand to a CDN, we can save about 20% of power in average of all the backbone networks considered.