Make Caching Decisions Research Articles

Fast media caching for geo-distributed data centers

Recent years have witnessed a phenomenal increase in video traffic. Virtual content delivery networks (vCDNs) coordinate video content delivery through the use of computing and storage resources from the cloud and distributes content to edge nodes near consumers to reduce network traffic and improve service experience. An important objective of vCDNs is operation cost minimization. Since cloud data centers are geo-distributed, content transfer costs vary significantly with different data centers, i.e., the cost is high for retrieval from distant data centers and lower for nearby retrievals. Many popular caching algorithms in use today, such as Lru, do not consider cost when making caching decisions, and as a result, suffer from high data transfer costs and increased network congestion. On the other hand, cost-aware caching algorithms such as LandLord [1] are computationally inefficient, with time complexity scaling linearly to the amount of content in the vCDN. Such algorithms are unable to keep pace with the exponential growth in video content over time. In this paper, we propose Fmc(fast media caching), a cost-aware and highly efficient caching algorithm for vCDN delivery over geo-distributed data centers. The load cost of each content item is determined by both the item’s size and distance from the data center it is loaded from. We first prove that Fmc is kk−h+1 competitive under the resource augmentation paradigm, where Fmc and the optimal offline adversary have k and h amount of cache, resp., and k ≥ h. Also, we show our algorithm is straightforward and efficient, requiring only O(log m) time per cache access, where m is the number of data centers and is a small constant in practice. We conduct experimental studies on Fmc using both synthetic and YouTube traces. Our results show that Fmc has on average 50% and up to 66.7% lower cost than Lru. Besides, we show Fmc is much faster than LandLord, and the speedup scales linearly with cache size.

Cooperative Local Caching under Heterogeneous File Preferences

Local caching is an effective scheme for leveraging the memory of the mobile terminal (MT) and short range communications to save the bandwidth usage and reduce the download delay in the cellular communication system. In particular, the MTs first cache in their local memories in off-peak hours and then exchange the requested files with each other in the vicinity during peak hours. However, prior works largely overlook MTs’ heterogeneity in file preferences and their selfish behaviors. In this paper, we practically categorize the MTs into different interest groups according to the MTs’ preferences. Each group of MTs aims to increase the probability of successful file discovery from the neighboring MTs (from the same or different groups). Hence, we define the groups’ utilities as the probability of successfully discovering the file in the neighboring MTs, which should be maximized by deciding the caching strategies of different groups. By modeling MTs’ mobilities as homogeneous Poisson point processes, we analytically characterize MTs’ utilities in the closed form. We first consider the fully cooperative case where a centralizer helps all groups to make caching decisions. We formulate the problem as a weighted-sum utility maximization problem, through which the maximum utility tradeoffs of different groups are characterized. Next, we study two benchmark cases under selfish caching, namely, partial and no cooperation, with and without inter-group file sharing, respectively. The optimal caching distributions for these two cases are derived. Finally, numerical examples are presented to compare the utilities under different cases and show the effectiveness of the fully cooperative local caching compared with the two benchmark cases.

Energy Efficient Dynamic Content Distribution

Consider a network of prosumers of media content in which users dynamically create and request content objects. The request process is governed by the objects’ popularity, which may vary across network regions and over time. In order to meet user requests, content objects can be stored and transported over the network, characterized by the capacity and efficiency of its storage and transport resources. The energy-efficient dynamic content distribution problem aims at finding the evolution of the network configuration, in terms of the placement and routing of content objects over time, that meets user requests, satisfies network resource capacities and minimizes overall energy use. We present 1) an information-centric linear programming formulation for the energy efficient dynamic content distribution problem that captures multicasting and caching over the network, per-object system dynamics, and delivery deadlines; 2) an offline solution that characterizes the minimum energy use achievable with global knowledge of user requests and network resources; and 3) an efficient distributed online solution that allows network nodes to make caching decisions based on their local estimate of the global energy benefit. Using a custom-built content distribution network simulator as well as a real prototype implementation in an information-centric networking testbed, we show the significant energy savings that can be obtained via the efficient and lightweight cache cooperation induced by our service and energy aware distributed online solution with respect to state of the art approaches.

A distributed in-network caching scheme for P2P-like content chunk delivery

In-network content caching has recently emerged in the context of information-centric networking (ICN), which allows content objects to be cached at the intermediate router side. In this paper, we specifically focus on in-network caching of peer-to-peer (P2P)-like content objects for improving both service and operation efficiencies. We propose a fully distributed in-network caching protocol for P2P-like content chunks, aiming to reduce P2P based content traffic load and also to achieve improved content distribution performances. Toward this end, the proposed holistic decision-making logic takes into account context information of both the underlying network and the P2P characteristics, such as chunk availability, popularity and peer distances. In addition, we also analyse the benefit of coordination between neighbouring content routers when making caching decisions in order to avoid duplicated P2P chunk caching nearby. An analytical modelling framework is developed to quantitatively evaluate the efficiency of the proposed in-network caching scheme. Extensive experiments are also conducted to validate the analytical results.

An energy-efficient distributed in-network caching scheme for green content-centric networks

Due to the in-network caching capability, Content-Centric Networking (CCN) has emerged as one of the most promising architectures for the diffusion of contents over the Internet. Most existing works on CCN focus on network resource utilization, and the energy consumption aspect is largely ignored. Moreover, the existing centralized schemes for CCN may not be practical to be implemented in realistic networks due to the distributed architecture of the Internet. In this paper, we propose an energy-efficient distributed in-network caching scheme for CCN. In the proposed scheme, each content router only needs locally available information to make caching decisions considering both caching energy consumption and transport energy consumption. We formulate the energy-efficient distributed in-network caching problem as a non-cooperative game. Through rigorous mathematical analysis, we prove that pure strategy Nash equilibria exist in the distributed solution, and it always has a strategy profile that implements the socially optimal configuration, even if the routers are self-interested in nature. Simulation results reveal that the proposed scheme is competitive to the centralized scheme, and has superior performance compared to the other widely used schemes in CCN. Besides, it exhibits a fast convergence speed when the capacity of content routers varies.

A game theoretic approach for energy-efficient in-network caching in content-centric networks

Recently, content-centric networking (CCN) has become a hot research topic for the diffusion of contents over the Internet. Most existing works on CCN focus on the improvement of network resource utilization. Consequently, the energy consumption aspect of CCN is largely ignored. In this paper, we propose a distributed energy-efficient in-network caching scheme for CCN, where each content router only needs locally available information to make caching decisions considering both caching energy consumption and transport energy consumption. We formulate the in-network caching problem as a non-cooperative game. Through rigorous mathematical analysis, we prove that pure strategy Nash equilibria exist in the proposed scheme, and it always has a strategy profile that implements the socially optimal configuration, even if the routers are self-interested in nature. Simulation results are presented to show that the distributed solution is competitive to the centralized scheme, and has superior performance compared to other popular caching schemes in CCN. Besides, it exhibits a fast convergence speed when the capacity of content routers varies.

Using Solid State Disk Array as a Cache for LHC ATLAS Data Analysis

User data analysis in high energy physics presents a challenge to spinning-disk based storage systems. The analysis is data intense, yet reads are small, sparse and cover a large volume of data files. It is also unpredictable due to users' response to storage performance. We describe here a system with an array of Solid State Disk as a non-conventional, standalone file level cache in front of the spinning disk storage to help improve the performance of LHC ATLAS user analysis at SLAC. The system uses several days of data access records to make caching decisions. It can also use information from other sources such as a work-flow management system. We evaluate the performance of the system both in terms of caching and its impact on user analysis jobs. The system currently uses Xrootd technology, but the technique can be applied to any storage system.

Alternative web caching design: a site-based approach

The existing designs and solutions for web caching systems commonly make caching decisions based on document or uniform resource locator (URL) information. While this conventional approach works, the authors deliver insights into the alternative approach using site information for web caching design. This site-based approach makes caching decisions based on the website that an object belongs to, rather than the object itself. The authors show that this new approach can benefit different scopes of cache design, ranging from internal operation of a single proxy (host level), mapping of proxy array in a local area network (LAN level), to load reduction in the global cache hierarchy (wireless area network (WAN) level). Since disks are usually the performance bottleneck in a proxy, to overcome this, the authors design a site-based cache architecture that tries to store web objects belonging to the same site in nearby disk blocks. The simulation results show that it reduces disk access time by 21–50%, compared to the conventional URL-based cache architecture. Besides, in the LAN-level design, a site-based mapping scheme can be used to map all requests targeting the same website to the same proxy, resulting in up to 50% reduction in the total transmission control protocol connection overhead. On the other hand, in the WAN-level, upper-level proxies are usually overloaded. To solve it, site information is used in lower-level proxies to decide which requests to forward to the origin servers directly (instead of upper-level proxy). As a result, proxy load is reduced by 46–59% and a reduction of 9–25% in request compliance delay can be achieved. With the merits of these three levels, it is believed that the site-based approach would contribute to the future caching designs.

Coordinated en-route Web caching

Web caching is an important technique for reducing Internet access latency, network traffic, and server load. This paper investigates cache management strategies for the en-route web caching environment, where caches are associated with routing nodes in the network. We propose a novel caching scheme that integrates both object placement and replacement policies and which makes caching decisions on all candidate sites in a coordinated fashion. In our scheme, cache status information along the routing path of a request is used in dynamically determining where to cache the requested object and what to replace if there is not enough space. The object placement problem is formulated as an optimization problem and the optimal locations to cache the object are obtained using a low-cost dynamic programming algorithm. Extensive simulation experiments have been performed to evaluate the proposed scheme in terms of a wide range of performance metrics. The results show that the proposed scheme significantly outperforms existing algorithms which consider either object placement or replacement at individual caches only.

Caching and Scheduling for Broadcast Disk Systems

Unicast connections lead to performance and scalability problems when a large client population attempts to access the same data. Broadcast push and broadcast disk technology address the problem by broadcasting data items from a server to a large number of clients. Broadcast disk performance depends mainly on caching strategies at the client site and on how the broadcast is scheduled at the server site. An on-line broadcast disk paging strategy makes caching decisions without knowing future page requests or access probabilities. This paper gives new implementations of existing on-line algorithms and reports on extensive empirical investigations. The gray algorithm [Khanna and Liberatore 2000] always outperformed other on-line strategies on both synthetic and Web traces. Moreover, caching limited the skewness of broadcast schedules, and led to favor efficient caching algorithms over refined scheduling strategies when the cache was large.

Flexible open caching for the Web

Caching plays a vital role in the performance of any large-scale distributed system and, as the variety and number of Web applications grows, is becoming an increasingly important research topic within the Web community. Existing caching mechanisms are largely transparent to their users and cater for resources which are primarily read-only, offering little support for customisable or complex caching strategies. In this paper we examine the deficiencies in these mechanisms with regard to applications with requirements for shared access to data where clients may require a variety of consistency guarantees. We present “open” caching within an object-oriented framework, an approach to solving these problems which, instead of offering caching transparency makes the caching mechanism highly visible allowing great flexibility in caching choices. Our implementation is built upon the W3Objects infrastructure and allows clients to make caching decisions for individual resources with minimal impact upon other resources which do not support our mechanisms.