Least-recently-used caching with dependent requests

Jelenković, Predrag R.; Radovanović, Ana

doi:10.1016/j.tcs.2004.07.029

Cited by 68 publications

(122 citation statements)

References 19 publications

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“…The theorem presented in this subsection complements the results of Jelenkovic and Radovanovic who showed in [13,12] that for dependent request processes, the hit probability is asymptotically, for large cache sizes, the same as in the corresponding LRU system with i.i.d. requests.…”

Section: Lru Insensitivitysupporting

confidence: 80%

TTL approximations of the cache replacement algorithms LRU(m) and h-LRU

Gast

Houdt

2017

Performance Evaluation

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Computer system and network performance can be significantly improved by caching frequently used information. When the cache size is limited, the cache replacement algorithm has an important impact on the effectiveness of caching. In this paper we introduce time-to-live (TTL) approximations to determine the cache hit probability of two classes of cache replacement algorithms: h-LRU and LRU(m). These approximations only require the requests to be generated according to a general Markovian arrival process (MAP). This includes phase-type renewal processes and the IRM model as special cases. We provide both numerical and theoretical support for the claim that the proposed TTL approximations are asymptotically exact. In particular, we show that the transient hit probability converges to the solution of a set of ODEs (under the IRM model), where the fixed point of the set of ODEs corresponds to the TTL approximation.We use this approximation and trace-based simulation to compare the performance of h-LRU and LRU(m). First, we show that they perform alike, while the latter requires less work when a hit/miss occurs. Second, we show that as opposed to LRU, h-LRU and LRU(m) are sensitive to the correlation between consecutive inter-request times. Last, we study cache partitioning. In all tested cases, the hit probability improved by partitioning the cache into different parts -each being dedicated to a particular content provider. However, the gain is limited and the optimal partition sizes are very sensitive to the problem's parameters.

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Section: Lru Insensitivitysupporting

confidence: 80%

TTL approximations of the cache replacement algorithms LRU(m) and h-LRU

Gast

Houdt

2017

Performance Evaluation

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“…Our method of proof uses probabilistic and sample path arguments introduced in [12] for the case of the ordinary LRU (PAC(β, 1)) algorithm. The starting point of our analysis is given by the representation formula in (7) from Section 2.…”

Section: Resultsmentioning

confidence: 99%

“…Note that the performance of the PAC algorithm drastically improves even for the small values of parameter k and, thus, it is nearly optimal; (ii) For the ordinary MTF (k = 1) searching, the convergence of C (N) /N in distribution as N → ∞ and the Laplace transform of the limiting function are obtained in Lemma 4.5 of [6]. The result in its presented form, for the ordinary LRU, was derived in [11]; (iii) It is possible to relax the assumption q i = h N /i α , 1 ≤ i ≤ N, e.g., by assuming that for any > 0, there exists i 0 , such that for all i 0 ≤ i ≤ N, inequality…”

Section: Theorem 2 Assume That Q Imentioning

confidence: 98%

The persistent‐access‐caching algorithm

Jelenković

Radovanović

2008

Random Struct Algorithms

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ABSTRACT:Caching is widely recognized as an effective mechanism for improving the performance of the World Wide Web. One of the key components in engineering the Web caching systems is designing document placement/replacement algorithms for updating the collection of cached documents. The main design objectives of such a policy are the high cache hit ratio, ease of implementation, low complexity and adaptability to the fluctuations in access patterns. These objectives are essentially satisfied by the widely used heuristic called the least-recently-used (LRU) cache replacement rule. However, in the context of the independent reference model, the LRU policy can significantly underperform the optimal least-frequently-used (LFU) algorithm that, on the other hand, has higher implementation complexity and lower adaptability to changes in access frequencies.To alleviate this problem, we introduce a new LRU-based rule, termed the persistent-accesscaching (PAC), which essentially preserves all of the desirable attributes of the LRU scheme. For this new heuristic, under the independent reference model and generalized Zipf's law request probabilities, we prove that, for large cache sizes, its performance is arbitrarily close to the optimal LFU algorithm. Furthermore, this near-optimality of the PAC algorithm is achieved at the expense of a negligible additional complexity for large cache sizes when compared to the ordinary LRU policy, since the PAC algorithm makes the replacement decisions based on the references collected during the preceding interval of fixed length.

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“…Though this model does not take into consideration the correlation between accesses, studies [10] show that the behavior modeled assuming independent reference gives results that are very close to those obtained using models that do indeed incorporate such correlation. We will also show this with empirical results which reconfirm that IRM is indeed able to accurately predict SPM and cache performance for data-structures such as trees where the access-pattern is clearly data-dependent and correlated.…”

Section: Model Descriptionmentioning

confidence: 72%

Analysis of scratch-pad and data-cache performance using statistical methods

Absar

Catthoor

2006

Proceedings of the 2006 Conference on Asia South Pacific Design Automation - ASP-DAC '06

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Abstract-An effectively designed and efficiently used memory hierarchy, composed of scratch-pads or cache, is seen today as the key to obtaining energy and performance gains in data-dominated embedded applications. However, an unsolved problem is -how to make the right choice between the scratchpad and the data-cache for different class of applications? Recent studies show that applications with regular and manifest data access patterns (e.g. matrix multiplication) perform better on the scratch-pad compared to the cache. In the case of dynamic applications with irregular and non-manifest access patterns, it is however commonly and intuitively believed that the cache would perform better. In this paper, we show by theoretical analysis and empirical results that this intuition can sometimes be misleading. When access-probabilities remain fixed, we prove that the scratch-pad, with an optimal mapping, will always outperform the cache. We also demonstrate how to map dynamic applications efficiently to scratch-pad or cache and additionally, how to accurately predict the performance.

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Least-recently-used caching with dependent requests

Cited by 68 publications

References 19 publications

TTL approximations of the cache replacement algorithms LRU(m) and h-LRU

TTL approximations of the cache replacement algorithms LRU(m) and h-LRU

The persistent‐access‐caching algorithm

Analysis of scratch-pad and data-cache performance using statistical methods

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