Classical Cache Research Articles

TTL model for an LRU-based similarity caching policy

Similarity caching allows requests for an item to be served by a similar item. Applications include recommendation systems, multimedia retrieval, and machine learning. Recently, many similarity caching policies have been proposed, like SIM-LRU and its generalization RND-LRU, but the performance analysis of their hit ratio is still wanting. In this paper, we show how to extend the popular time-to-live approximation in classic caching to similarity caching. In particular, we propose a method to estimate the hit ratio of the similarity caching policy RND-LRU. Our method, the RND-TTL approximation, introduces the RND-TTL cache model and then tunes its parameters in such a way as to mimic the behavior of RND-LRU. The parameter tuning involves solving a fixed point system of equations for which we provide an algorithm for numerical resolution and sufficient conditions for its convergence. Our approach for approximating the hit ratio of RND-LRU is evaluated on both synthetic and real-world traces.

Decentralized coded caching for shared caches using erasure coding

In a client–server architecture data traffic varies through time. It exhibits congestion of network resources at peak hours while the network remains rather under-utilized during the off-peak hours. One of the potential techniques to smooth out this data traffic over time is to load part of the data into cache memories distributed across the network. In the classical cache framework, each user is associated to a cache and the caching process is centrally coordinated. However, for large networks, decentralized caching is more practical since decentralized caching does not require the knowledge of all the active users in the network during the prefetching phase which is a necessity for centralized caching. Furthermore, with an aim to reduce cache under-utilization in a network, caches are allowed to serve multiple clients. Such a scheme in which multiple users are allowed to share a cache is referred to as the shared caching scheme. Shared caching scheme has been explored in both centralized and decentralized setting with centralized scheme giving a superior performance. To improve the performance of the decentralized caching scheme we implement precoding at the server’s end. Precoding is done by encoding the data stored in the server using a Maximum Distance Separable (MDS) erasure code. The coded caching framework in this paper is denoted as MDS precoded decentralized shared caching. We propose a delivery scheme and derive a delivery rate for the proposed scheme. Using techniques from index coding, a lower bound is obtained for all MDS precoded decentralized shared caching linear delivery schemes delivering certain contents. The proposed lower bound is shown to meet the proposed delivery rate. The achievable delivery rate proposed in this paper is also shown to match with the rate obtained for the optimal centralized shared caching scheme for small and large cache memory sizes.

CacheNet: Leveraging the principle of locality in reconfigurable network design

Emerging optical communication technologies support the dynamic reconfiguration of datacenter network topologies depending on the traffic they serve. However, to reap the benefits of such demand-aware networks, control logic that quickly learns and adapts to traffic patterns is required. This paper presents CacheNet, a novel approach to efficiently control demand-aware networks. CacheNet consists of two components, a demand-aware links-cache, and a demand-oblivious topology. CacheNet leverages temporal and spatial locality in the traffic by managing the reconfigurable links of the optical switches as a links-cache. Network traffic, in turn, can be served either by a link from the links-cache component or by a demand-oblivious topology component. We study several classic caching algorithms like online LFU and LRU as our caching algorithms, as well as offline optimal caching as a benchmark, and provide an analytical model which captures their performance benefits compared to an all demand-oblivious topology. Our analytical results show that based on the hit ratios and the links-cache size, when considering the average packet delay, our hybrid design outperforms a design that is based only on demand-oblivious topology. We also evaluate CacheNet empirically, using both synthetic and real-world traffic traces, confirming the potential of our approach to consider reconfigurable links as a network of links-cache.

An Edge Caching Strategy Based on User Speed and Content Popularity for Mobile Video Streaming

Mobile users’ demands to delay-sensitive video streaming media put forward new requirements for mobile networks, such as architecture optimization. Edge caching as a new paradigm is proposed to enhance the quality of service (QoS) for mobile users at the network edge. Due to the limited coverage of edge cache nodes, the frequent handoffs between base stations would aggravate network traffic overhead, resulting in a bad experience of high latency and service interruption when mobile users browse videos. This paper first proposes a three-layer mobile edge network architecture and applied edge caching to video streams to build an efficient caching system. Given the user’s mobility and low latency of mobile video streaming, we propose an edge caching strategy based on user speed and content popularity. Horizontally, the user’s speed affects the spanning area and the buffer size of the cache on edge; vertically, content popularity determines the priority of cached videos. Experimental results demonstrate that our caching strategy outperforms other schemes in terms of the average delay and the cache hit ratio in mobile video streaming scenes compared with the other three classic caching methods.

Value‐aware cache replacement in edge networks for Internet of Things

AbstractWith the development of Internet of Things (IoT), massive amounts of data will be brought. By offloading caching from the cloud to the edge, edge caching technology represents a promising solution in the era of IoT to meet the delay requirements of IoT applications. An efficient cache decision and replacement strategy on edge caching devices is a key factor in ensuring the cache hit ratio. The existing cache replacement policies do not comprehensively consider the characteristics of cache files and are likely to result in cache pollution problems. In order to cache data reasonably, to improve the cache hit ratio, and to reduce the user request delay, we propose a concept of file cache value and a file cache value‐aware cache replacement (FCVACR) algorithm of the edge cache system in this article. File cache value is associated with three aspects of cache file: the file size, the file popularity, and the time of requests. The proposed FCVACR algorithm adopts the file cache value method, improves the utilization of edge caching space, and reduces the content transmission delay. Experimental results show that the proposed FCVACR algorithm has a higher cache hit ratio and lower user request delay than the classical cache replacement algorithms.

Heterogeneous CCN Cache Allocation Strategy With Collaboration Support

Content-Centric Networking (CCN) is regarded as a promising network architecture which has received the distinct interest from many global research communities thanks to its friendly structure, especially its caching technology has attracted the most widespread attention. However, the current caching strategies have some limitations, such as redundant content copies, low cache utilization rate and unbalanced node load. In order to further optimize cache, this paper investigates the classical cache allocation problem, i.e., distributing the cache capacity across some Content Routers (CRs) under a constrained and fixed total cache budget. At first, both topology information and traffic characteristics as two factors to determine the importance of CR, where the evaluation of network topology depends on degree centrality, betweenness centrality and closeness centrality while that of traffic characteristics depends on node load and interest preference. In particular, given the data redundancy due to the high-dimensional feature, increasing the complexity of computation, t-distributed Stochastic Neighbor Embedding (t-SNE) is used to reduce the dimensions of data. Then, for the CR with cache capacity, its Content Store (CS) is divided into collaborative region and non-collaborative region by a heuristic algorithm to facilitate the optimal performance, and the CS with collaboration needs to interact the cached information with its neighborhoods. Finally, the performance evaluation is driven by the real dataset over GTS-CE topology. The experimental results reveal that the proposed collaboration-supported cache allocation strategy is more efficient than two baselines, i.e., increasing cache hit ratio by 7.79%, increasing cache utilization rate by 11.31%, decreasing routing delay by 49.38% and decreasing load balance by 50.98%.

An adaptive cache management approach in ICN with pre-filter queues

In Information-Centric Networking (ICN), transmission does not depend on the ends of communication, but on the content itself. In-network cache plays an important role in ICN, it empowers nodes in ICN better mobility. It also shortens serving path, lightens load of server, reduces traffic and time delay, its efficiency seriously affects performance of entire network, and thus cache management in ICN draws much attention of researchers recently. Although there are a lot approaches have been proposed, a cache management scheme with better adaptability and less cost remains to be studied. To this end, we propose State-value-and-Cache-rate-Method (SCMethod) to manage cache resources in ICN, which comprises cache deployment policy and cache replacement policy. In cache level, we add pre-filter queues in front of cache queue to filter out popular content to store in cache. In the perspective of node, according to factors that node’s state and relative location on data forwarding path, we define node state and cache rate to select nodes with maximum of state value or minimum cache rate to cache content, and effectively mitigate data redundancy. In order to increase dynamics and adaptive of system for mobility of nodes, we employ cache hit ratio as feedback to dynamically adjust the number of pre-filter queues in every node. With pre-filter queues, we improve Least Recently Used (LRU) cache replacement method. We conduct extensive experiments in simulator Icarus (Saino et al., 2014) with both tree topology and realistic internet topologies, define four metrics to quantitatively evaluate performance of SCMethod and verify its efficacy of reducing latency and load. Simulation results demonstrate that SCMethod we proposed outperform several classic cache schemes of ICN.

Deep Learning Based Proactive Caching for Effective WSN‐Enabled Vision Applications

Wireless Sensor Networks (WSNs) have a wide range of applications scenarios in computer vision, from pedestrian detection to robotic visual navigation. In response to the growing visual data services in WSNs, we propose a proactive caching strategy based on Stacked Sparse Autoencoder (SSAE) to predict content popularity (PCDS2AW). Firstly, based on Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies, a distributed deep learning network SSAE is constructed in the sink nodes and control nodes of the WSN network. Then, the SSAE network structure parameters and network model parameters are optimized through training. The proactive cache strategy implementation procedure is divided into four steps. (1) The SDN controller is responsible for dynamically collecting user request data package information in the WSNs network. (2) The SSAEs predicts the packet popularity based on the SDN controller obtaining user request data. (3) The SDN controller generates a corresponding proactive cache strategy according to the popularity prediction result. (4) Implement the proactive caching strategy at the WSNs cache node. In the simulation, we compare the influence of spatiotemporal data on the SSAE network structure. Compared with the classic caching strategy Hash + LRU, Betw + LRU, and classic prediction algorithms SVM and BPNN, the proposed PCDS2AW proactive caching strategy can significantly improve WSN performance.

Endurable SSD-Based Read Cache for Improving the Performance of Selective Restore from Deduplication Systems

Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based (i.e., SSD-based) read cache can be deployed for speeding up by caching popular restore contents dynamically. Unfortunately, frequent data updates induced by classical cache schemes (e.g., LRU and LFU) significantly shorten SSDs’ lifetime while slowing down I/O processes in SSDs. To address this problem, we propose a new solution — LOP-Cache — to greatly improve the write durability of SSDs as well as I/O performance by enlarging the proportion of long-term popular (LOP) data among data written into SSD-based cache. LOP-Cache keeps LOP data in the SSD cache for a long time period to decrease the number of cache replacements. Furthermore, it prevents unpopular or unnecessary data in deduplication containers from being written into the SSD cache. We implemented LOP-Cache in a prototype deduplication system to evaluate its performance. Our experimental results indicate that LOP-Cache shortens the latency of selective restore by an average of 37.3% at the cost of a small SSD-based cache with only 5.56% capacity of the deduplicated data. Importantly, LOP-Cache improves SSDs’ lifetime by a factor of 9.77. The evidence shows that LOP-Cache offers a cost-efficient SSD-based read cache solution to boost performance of selective restore for deduplication systems.

Pannier

Classic caching algorithms leverage recency, access count, and/or other properties of cached blocks at per-block granularity. However, for media such as flash which have performance and wear penalties for small overwrites, implementing cache policies at a larger granularity is beneficial. Recent research has focused on buffering small blocks and writing in large granularities, sometimes called containers, but it has not explored the ramifications and best strategies for caching compound blocks consisting of logically distinct, but physically co-located, blocks. Containers may have highly diverse blocks, with mixtures of frequently accessed, infrequently accessed, and invalidated blocks. We propose and evaluate Pannier, a flash cache layer that provides high performance while extending flash lifespan. Pannier uses three main techniques: (1) leveraging block access counts to manage cache containers, (2) incorporating block liveness as a property to improve flash cache space efficiency, and (3) designing a multi-step feedback controller to ensure a flash cache reaches its desired lifespan while maintaining performance. Our evaluation shows that Pannier improves flash cache performance and extends lifespan beyond previous per-block and container-aware caching policies. More fundamentally, our investigation highlights the importance of creating new policies for caching compound blocks in flash.

Two New Burial Grounds with Cremations of Saltiv-Mayaky Culture around Sukha Homolsha Village in Kharkiv Region

Presented to scientific circles is information on two new Saltiv-Mayaky burial grounds with cremations (Sukha Homolsha Gully and Plaskyi Ravine) discovered in Verkhniy Donets River upper region in Zmiyiv Region of Kharkiv Oblast. Archaeological prospecting in 2013 and 2016 showed that both burial grounds are almost completely destroyed by modern diggers. Plaskyi Ravine burial ground is comparable with its size with the known Sukha Homolsha burial ground with cremations. Archaeological prospecting also showed that the latter site has its extension and can’t be perceived as fully studied. Sukha Homolsha Gully burial ground is at least ten times larger than the one at Plaskyi Ravine. A cache and a cremation in pit were discovered in trenches 1 and 2 correspondingly at Sukha Homolsha burial ground. The burial was traced on an area 0,75 by 0,35 m and was recorded at a depth 0,3 m from the ground surface. The edges of the burial pit were not traced with the archaeological methods. This fact probably testifies that the burial was made on the original surface: bones and funeral goods were just poured out on the ground. Funeral goods included iron piece for starting fire, iron ring, buckle frame, and pincers, as well as six bronze plates from a belt set and an Abbasid dinar (753—754) probably plated with gold in antiquity. In a trench at Plaskyi Ravine burial ground, a classic Saltiv culture cache and a silver Khawarijian dirham of 179 AH (795—796) found in cultural layer at the site. The materials from caches find broad analogies in assemblages with cremations in the region. Numismatic finds discovered at burial grounds with cremations for the first time present chronologic datum points for dating the elements of belt sets.

Invalidation Method for Wireless Mobile Network to Maintain Consistency

This paper is proposed for the distributed cache invalidation mechanism (DCIM), it is a client-based cache consistency scheme which is implemented on the top of a previously proposed architecture for the caching data items in mobile ad hoc networks (MANETs), namely COACS, where special nodes cache the queries and the addresses of the nodes that store the responses to these queries. Caching frequently accessed data items on the client side is an effective technique for improving performance in a mobile environment. The classical cache invalidation strategies are not suitable for the mobile environments due to frequent disconnections and mobility of the clients. The huge amount of demand has been created due to trend toward wireless communications and advances in mobile technologies are which increasing the consumer demands for ubiquitous access to Internet-based information and services. DCIM can be implemented using ns2, and compared against the client-based and server-based schemes to assess its performance experimentally. Hear introduce DCIM that is totally client-based. DCIM is a pull- based algorithm that implements adaptive time to live (TTL), piggybacking, and pre-fetching, and provides near strong consistency capabilities. Keywordsdata caching, pull-based, TTL, shared data.

Efficient Extraction for Mobile Web Access Log with Caching Strategy

Mobile web access log file plays an important role in the analysis about demand of mobile terminal market or user behavior. However, the log file data is highly dimensional, disorganized and semi-structured, which heightens the difficulty of data extracting accuracy; while it generates and transmits continuously, which poses an extracting efficiency challenge. It is highly desirable to extract the information embedded in log files as disorder or hidden situation efficiently and accurately. This paper proposes an efficient extracting method for mobile web access log with cache strategy. Firstly of all, data dictionary sets are built for each kind of complex field before extracting. Then, data is extracted based on the dictionaries, and the dictionaries will be completed simultaneously. Furthermore, with the discovery of the distribution of some data in the log generally following Zipf-like distribution, cache strategy is considered to be an auxiliary way to reduce mapping time. In addition, the classical cache strategy LFU is chosen. Ultimately, the experiment shows that the data could be extracted from the log accurately, and the extracting efficiency speeds up remarkably with LFU cache strategy.

Cost-Aware Caching: Caching More (Costly Items) for Less (ISPs Operational Expenditures)

Albeit an important goal of caching is traffic reduction, a perhaps even more important aspect follows from the above achievement: the reduction of internet service provider (ISP) operational costs that comes as a consequence of the reduced load on transit and provider links. Surprisingly, to date this crucial aspect has not been properly taken into account in cache design. In this paper, we show that the classic caching efficiency indicator, i.e., the hit ratio, conflicts with cost. We therefore propose a mechanism whose goal is the reduction of cost and, in particular, we design a cost-aware (CoA) cache decision policy that, leveraging price heterogeneity among external links, tends to store with more probability the objects that the ISP has to retrieve through the most expensive links. We provide a model of our mechanism, based on Che's approximation, and, by means of a thorough simulation campaign, we contrast it with traditional cost-blind schemes, showing that CoA yields a significant cost saving, that is furthermore consistent over a wide range of scenarios. We show that CoA is easy to implement and robust, making the proposal of practical relevance.

Efficient cache availability management in Information-Centric Networks

In-network caching is one of the fundamental operations of Information-Centric Networks (ICN). The default caching strategy taken by most of the current ICN proposals is caching along-default-path, which makes popular objects to be cached redundantly across the network, resulting in a low utilization of available cache space. On the other hand, efficient use of network-wide cache space requires possible cooperation among caching routers without the use of excessive signaling burden. While most of the cache optimization efforts strive to improve the latency and the overall traffic efficiency, we have taken a different path in this work and improved the storage efficiency of the cache space so that it is utilized to its most.In this work we discuss the ICN caching problem, and propose a novel distributed architecture to efficiently use the network-wide cache storage space based on distributed caching. The proposal achieves cache retention efficiency by means of controlled traffic redirection and selective caching. We utilize the ICN mechanisms and routing protocol messages for decision making, thus reducing the overall signaling need. Our proposal achieves almost 9-fold increase in cache storage efficiency, and around 20% increase in server load reduction when compared to the classic caching methods used in contemporary ICN proposals.

Improved strategies and adaptive capability allocation algorithm for query result caching

Query result caching has attracted overwhelming attention in recent years to enhance the performance of search engines. In this paper, we present approaches to improve cost-aware strategies for static and dynamic caching, and further propose an adaptive capability allocation algorithm for hybrid caching. More precisely, we introduce a query repeated distance factor to improve the classical static result caching. We describe the worth of caching based on the query popularity and design a novel mechanism to further improve the dynamic policies. By designing a Queue-Hash cache internal structure, our adaptive capability allocation algorithm is employed to adjust the cache capability to further improve the efficiency in a hybrid cache combining static and dynamic caching policies. The experimental results demonstrate that the improved approaches can increase the overall system performance, particularly in terms of the average processing time.

A framework for network aware caching for video on demand systems

Video on Demand (VoD) services allow users to select and locally consume remotely stored content. We investigate the use of caching to solve the scalability issues of several existing VoD providers. We propose metrics and goals that define the requirements of a caching framework for CDNs of VoD systems. Using data logs collected from Motorola equipment from Comcast VoD deployments we show that several classic caching solutions do not satisfy the proposed goals. We address this issue by developing novel techniques for predicting future values of several metrics of interest. We rely on computed predictions to define the penalty imposed on the system, both network and caching sites, when not storing individual items. We use item penalties to devise novel caching and static content placement strategies. We use the previously mentioned data logs to validate our solutions and show that they satisfy all the defined goals.

통합 RFID 미들웨어의 응답시간 개선을 위한 효과적인 캐쉬 구조 설계

This paper proposes an efficient caching mechanism appropriate for the integrated RFID middleware which can integrate wireless sensor networks (WSNs) and RFID (radio frequency identification) systems. The operating environment of the integrated RFID middleware is expected to face the situations of a significant amount of data reading from RFID readers, constant stream data input from large numbers of autonomous sensor nodes, and queries from various applications to history data sensed before and stored in distributed storages. Consequently, an efficient middleware layer equipping with caching mechanism is inevitably necessary for low latency of request-response while processing both data stream from sensor networks and history data from distributed database. For this purpose, the proposed caching mechanism includes two optimization methods to reduce the overhead of data processing in RFID middleware based on the classical cache implementation polices. One is data stream cache (DSC) and the other is history data cache (HDC), according to the structure of data request. We conduct a number of simulation experiments under different parameters and the results show that the proposed caching mechanism contributes considerably to fast request-response times.

A scalable low-latency cache invalidation strategy for mobile environments

Caching frequently accessed data items on the client side is an effective technique for improving performance in a mobile environment. Classical cache invalidation strategies are not suitable for mobile environments due to frequent disconnections and mobility of the clients. One attractive cache invalidation technique is based on invalidation reports (IRs). However, the IR-based cache invalidation solution has two major drawbacks, which have not been addressed in previous research. First, there is a long query latency associated with this solution since a client cannot answer the query until the next IR interval. Second, when the server updates a hot data item, all clients have to query the server and get the data from the server separately, which wastes a large amount of bandwidth. In this paper, we propose an IR-based cache invalidation algorithm, which can significantly reduce the query latency and efficiently utilize the broadcast bandwidth. Detailed analytical analysis and simulation experiments are carried out to evaluate the proposed methodology. Compared to previous IR-based schemes, our scheme can significantly improve the throughput and reduce the query latency, the number of uplink request, and the broadcast bandwidth requirements.

A few examples of how to use a symmetrical multi-micro-processor

This paper presents an overview of an architecture of a multi-micro-processor architecture in which all processors are equivalent. The structure is characterized by a central memory and several caches, and is designed to avoid incoherent data. A fast mechanism of “subcontracting” between one processor and another is described. The execution of two simple programs under this architecture is studied. The parallel algorithms are described and compared with the original (sequential) algorithms; it is shown that the overhead remains small, few extra memories are necessary and synchronization do not slow down the execution unduly. Furthermore, the locality of the parallel algorithm is compared to that of the sequential algorithm and is found to be less good, but in a reasonable way. As well, an estimation of the cost of the coherence keeping mechanism is given using the difference between the miss ratio of the classical cache and the “coherence keeping cache”, respectively.