An analytical model for cache replacement policy performance

This article describes how the named data networking (NDN) has recently received a lot of attention as a potential information-centric networking (ICN) architecture for the future Internet. The NDN paradigm has a great potential to efficiently address and solve the current seminal IP-based IoT architecture issues and requirements. NDN can be used with different sets of caching algorithms and caching replacement policies. The authors investigate the most suitable combination of these two features to be implemented in an IoT environment. For this purpose, the authors first reviewed the current research and development progress in ICN, then they conduct a qualitative comparative study of the relevant ICN proposals and discuss the suitability of the NDN as a promising architecture for IoT. Finally, they evaluate the performance of NDN in an IoT environment with different caching algorithms and replacement policies. The obtained results show that the consumer-cache caching algorithm used with the Random Replacement (RR) policy significantly improve NDN content validity in an IoT environment.

SummaryHybrid storage systems that consist of flash‐based solid state drives (SSDs) and traditional disks are now widely used. In hybrid storage systems, there exists a two‐level cache hierarchy that regard dynamic random access memory (DRAM) as the first level cache and SSD as the second level cache for disk storage. However, this two‐level cache hierarchy typically uses independent cache replacement policies for each level, which makes cache resource management inefficient and reduces system performance. In this paper, we propose a novel adaptive multi‐level cache (AMC) replacement algorithm in hybrid storage systems. The AMC algorithm adaptively adjusts cache blocks between DRAM and SSD cache levels using an integrated solution. AMC uses combined selective promote and demote operations to dynamically determine the level in which the blocks are to be cached. In this manner, the AMC algorithm achieves multi‐level cache exclusiveness and makes cache resource management more efficient. By using real‐life storage traces, our evaluation shows the proposed algorithm improves hybrid multi‐level cache performance and also increases the SSD lifetime compared with traditional multi‐level cache replacement algorithms. Copyright © 2015 John Wiley & Sons, Ltd.

An effectiveness-based adaptive cache replacement policy

Ideally, we could solve all memory performance problems by storing everything in high performance caches. However, the associated high-cost forces us to keep only a limited amount of working sets of data in these caches and the replacement of disposable blocks of data with the desired one is a fundamental property to caches. Ultimately, the performance of a cache is heavily influenced by the replacement policy it uses. In this paper, we conduct a comparative analysis of a few replacement policies currently in use from traditional strategies to the ones that attempt to emulate optimal replacement and simulate a few replacement strategies to test the performance of multilevel cache by configuring the cache memory subsystem in the Multi2sim simulator. We have focused on the shared nature of the last Level Cache (LLC) which includes many coherence problems. This is where directories and coherence protocols come into play. However, the blocks suffer when the directory entries are themselves evicted from the directory. In this paper, we look into a cache coherence mechanism that instead of evicting the block from the private caches when the directory entry is evicted, rather than storing the entry in the LLC slice. This guarantees freedom from the Directory Eviction Victim Blocks (DEVB). We analyze the performance of our proposed replacement technique, namely, coalesce private or spill shared (CPOSS) by varying the size and associativity of the sparse directory by providing the workload from Parsec, Splash2 and FFTW benchmarks and we observe that the CPOSS outperforms the existing least recently used (LRU) in slice LLC banks in Multicore processors.

Due to the ever increasing performance gap between the processor and the main memory, it becomes crucial to bridge that gap by designing an efficient memory hierarchy capable of reducing the average memory access time. The cache replacement algorithm plays a central role in designing an efficient memory hierarchy. Many of the recent studies in cache replacement algorithms have focused on improving L2 cache replacement algorithms by minimizing the miss count. However, depending on the dependency chain, cache miss bursts, and other factors, a processor's ability to partially hide the cost of an L2 cache miss varies; that is, cache miss costs are not uniform. Therefore, a better solution would account also for the aggregate miss cost in designing cache replacement algorithms. Our proposed solution combines the two principles of locality and cost-sensitivity into one which we call: LACS: Locality-Aware Cost-Sensitive cache replacement algorithm. LACS estimates a cache block's cost from the number of instructions the processor manages to issue during a cache miss on that block and then victimizes cache blocks with low cost and poor locality in order to maximize the overall cache performance. When LACS is evaluated using a uniprocessor architecture model, it speeds up 10 L2 cache performance-constrained SPEC CPU2000 benchmarks by up to 85% and 15% on average while not slowing down any of the 20 SPEC CPU2000 benchmarks evaluated. When evaluated using a dual-core CMP architecture model, LACS speeds up 6 SPEC CPU2000 benchmark pairs by up to 44% and 11% on average.

We consider the problem of on-chip L2 cache management and replacement policies. We propose a new adaptive cache replacement policy, called Dueling CLOCK (DC), that has several advantages over the Least Recently Used (LRU) cache replacement policy.

Reliability improvement in private non-uniform cache architecture using two enhanced structures for coherence protocols and replacement policies

By rapid growth of the Internet users and devices, thenumber of servers also increase simultaneously which causes the exponentialincrement of the internet traffic and static data. Handling these huge amountsof user requests and efficiently responding to them require high bandwidthlinks, powerful servers and robust equipment, which despite the availability ofthese requirements getting the full user satisfaction is extremely difficultand a tough challenge. In order to overcome the mentioned problem, the cacheservers are being used as a suitable solution. The performance of web cacheserver directly depends on its replacement policies. Several cache replacementpolicies have been proposed in literature each having varied hit rate (HR) andbyte hit rate (BHR) performances on different networks. The replacement policyproposed in this paper is a dynamic cache replacement policy which trainsitself utilizing previous network logs and by exploiting the data miningclustering algorithm. Once the training step is completed, the proposed policyutilizes the normalization formulas to score each metric of the enquiriesincluding recency, frequency, size and delay. Simulation results showed thatthe proposed policy has the optimum performance on different networks and itnot only improved the performance of web cache server in term of HR and BHR,but also decreases the data retrieval time (Delay Ratio (DR)) of the cacheservers.

In wireless data transmission, the capacity of wireless links is typically limited. Since many applications exhibit temporal locality for data access, the cache mechanism can be built in a wireless terminal to effectively reduce the data access time. This paper studies the cache performance of the wireless terminal by considering a business-card application. We investigate the least-recently used replacement policy and two strongly consistent data access algorithms called poll-each-read and callback. An analytic model is proposed to derive the effective hit ratio of data access, which is used to validate against simulation experiments. Our study reports how the data access rate and the data update distribution affect the cache performance in a wireless terminal.

In previous research on cache replacement policies, have seen that a block usually becomes dead after some uses. By classifying the dead block and discarding them early, there are various policies have been used but still there are number of problems such as cache pollution, high cache miss rate and cache overhead existed which degrades the system performance. In this paper, a new approach for cache replacement policy has introduced which reduces the cache miss rate and cache overhead by using shared L2 level cache. In terms of less miss rate and good hit rate there is need to deploy effective replacement policies. Cache replacement techniques is one of the crucial design parameter that affects the overall processor performance and also become more important with current growing technological moves in the direction of high associative cache . Keywords: Cache pollution; Cache overhead; Cache miss rate; Cache replacement policy (LRU and LFU); Memory overhead;

Data caching in mobile clients is an important technique to enhance data availability and to improve data access time. Due to cache size limitations, cache replacement policies are used to find a suitable subset of items for eviction from the cache. In this paper, we study the issues of cache replacement for location-dependent data under a geometric location model and we have proposed a new cache replacement policy RAAR (Re-entry probability, Area of valid scope, Age, Rate of Access) by taking into account the spatial and temporal parameters. The experimental evaluations using synthetic datasets show that our replacement policy is effective in improving the system performance in terms of the cache hit ratio of mobile clients.

The World-Wide-Web has experienced exponential growth in recent years. This growth has created a tremendous increase in network and server loads that have subsequently adversely affected user-response times. Among many viable and available approaches to reducing user-response time, Web caching appears to be one approach that has recently received considerable attention. In this dissertation we explore a new approach to the study of Web cache policies, namely model-driven simulation. We present a good model of Web-access user patterns based on sound theory and principles from the information sciences. This model is justified by the empirical web access data from several different web sites. The importance of removal policies in improving cache performance motivates us to propose a dynamic and robust removal policy which incorporates the characteristics of user access patterns. We show that our proposed removal policy performs rigorously well over a variety of parameters. In this research we take a model-driven simulation approach to evaluate the impact of different factors and policies on cache performance. The results indicate that cache size, user access patterns and removal policy are major factors affecting cache performance. Continuous removal method is a good and simple method. The increase of average document size, low comfort level (less than 50% cache size) and threshold policy would degrade web cache performance. Finally, we discuss the limitations of our current research and give some directions of future research.

ProWGen: a synthetic workload generation tool for simulation evaluation of web proxy caches

In this paper, we design and implement a P2P cooperative proxy caching system based on a novel P2P cooperative proxy caching scheme. To effectively locate the cached web documents, a TTL-based routing protocol is proposed to manage the query and response messages in the P2P cooperative proxy cache system. Furthermore, we design a predict query-route algorithm to improve the TTL-based routing protocol by adding extra information in the query message packets. To select a suitable cache replacement algorithm for the P2P cooperative proxy cache system, three different cache replacement algorithms, LRU, LFU and SIZE, are evaluated using web trace based performance studies on the implemented P2P cooperative proxy cache system. The experimental results show that LRU is an overall better cache replacement algorithm for the P2P proxy cache system although SIZE based cache replacement approach produces slightly better cache hit ratio when cache size is very small. The performance studies also demonstrate that the proposed message routing protocols significantly improve the performance of the P2P cooperative proxy cache system, in terms of cache hit ratio, byte hit ratio, user request latency, and the number of query messages generated in the proxy cache system, compared to the flooding based message routing protocol.

Recently, the growing demand for rich multimedia content such as Video on Demand (VoD) has made the data transmission from content delivery networks (CDN) to end-users quite challenging. Edge networks have been proposed as an extension to CDN networks to alleviate this excessive data transfer through caching and to delegate the computation tasks to edge servers. To maximize the caching efficiency in the edge networks, different Mobile Edge Computing (MEC) servers assist each others to efficiently select which content to store and the appropriate computation tasks to process. In this paper, we adopt a collaborative caching and transcoding model for VoD in MEC networks. However, unlike other models in the literature, different chunks of the same video are not fetched and cached in the same MEC server. Instead, neighboring servers will collaborate to store and transcode different video chunks and consequently optimize the limited resources usage. Since we are dealing with chunks caching and processing, we propose to maximize the edge efficiency by studying the viewers watching pattern and designing a probabilistic model where chunks popularities are evaluated. Based on this model, popularity-aware policies, namely Proactive caching policy (PcP) and Cache replacement Policy (CrP), are introduced to cache only highest probably requested chunks. In addition to PcP and CrP, an online algorithm (PCCP) is proposed to schedule the collaborative caching and processing. The evaluation results prove that our model and policies give better performance than approaches using conventional replacement policies. This improvement reaches up to 50% in some cases.