21 research outputs found
Stochastic Dynamic Cache Partitioning for Encrypted Content Delivery
In-network caching is an appealing solution to cope with the increasing
bandwidth demand of video, audio and data transfer over the Internet.
Nonetheless, an increasing share of content delivery services adopt encryption
through HTTPS, which is not compatible with traditional ISP-managed approaches
like transparent and proxy caching. This raises the need for solutions
involving both Internet Service Providers (ISP) and Content Providers (CP): by
design, the solution should preserve business-critical CP information (e.g.,
content popularity, user preferences) on the one hand, while allowing for a
deeper integration of caches in the ISP architecture (e.g., in 5G femto-cells)
on the other hand.
In this paper we address this issue by considering a content-oblivious
ISP-operated cache. The ISP allocates the cache storage to various content
providers so as to maximize the bandwidth savings provided by the cache: the
main novelty lies in the fact that, to protect business-critical information,
ISPs only need to measure the aggregated miss rates of the individual CPs and
do not need to be aware of the objects that are requested, as in classic
caching. We propose a cache allocation algorithm based on a perturbed
stochastic subgradient method, and prove that the algorithm converges close to
the allocation that maximizes the overall cache hit rate. We use extensive
simulations to validate the algorithm and to assess its convergence rate under
stationary and non-stationary content popularity. Our results (i) testify the
feasibility of content-oblivious caches and (ii) show that the proposed
algorithm can achieve within 10\% from the global optimum in our evaluation
Interference control by best-effort process duty-cycling in chip multi-processor systems for real-time medical image processing
Systems with chip multi-processors are currently used for several applications that have real-time requirements. In chip multi-processor architectures, many hardware resources such as parts of the cache hierarchy are shared between cores and by using such resources, applications can significantly interfere with each other. In previous work, we showed that a single X-ray imaging streaming applications can be executed with low jitter on such systems. However, it was assumed that only one application would be running on the system, which prevents system integration where multiple real-time and best- effort applications are executing on a single chip multi-processor. In this paper, we address the limited bandwidth in the cache hierarchy, which can cause threads to interfere with each other significantly. We propose a technique that implements cache bandwidth reservation in software, by dynamically duty-cycling best-effort applications, based on their cache bandwidth usages using processor performance counters in order to control the influence of best-effort applications on real-time applications. With this technique we can control the latency increase of real- time applications that is caused by best-effort application in order to satisfy real-time requirements with a minimal reduction in best-effort performance. The results of the experiments with real- life applications indicate that we can control the increase of the latency to such an extent that we can almost completely eliminate the influence of bandwidth sharing in the cache at the cost of best-effort performance
Divided disk cache and SSD FTL for improving performance in storage
Although there are many efficient techniques to minimize the speed gap between processor and the memory, it remains a bottleneck for various commercial implementations. Since secondary memory technologies are much slower than main memory, it is challenging to match memory speed to the processor. Usually, hard disk drives include semiconductor caches to improve their performance. A hit in the disk cache eliminates the mechanical seek time and rotational latency. To further improve performance a divided disk cache, subdivided between metadata and data, has been proposed previously. We propose a new algorithm to apply the SSD that is flash memory-based solid state drive by applying FTL. First, this paper evaluates the performance of such a disk cache via simulations using DiskSim. Then, we perform an experiment to evaluate the performance of the proposed algorithm.clos
Efficient caching with reserves via marking
Online caching is among the most fundamental and well-studied problems in the area of online algorithms. Innovative algorithmic ideas and analysis – including potential functions and primal-dual techniques – give insight into this still-growing area. Here, we introduce a new analysis technique that first uses a potential function to upper bound the cost of an online algorithm and then pairs that with a new dual-fitting strategy to lower bound the cost of an offline optimal algorithm. We apply these techniques to the Caching with Reserves problem recently introduced by Ibrahimpur et al. [10] and give an O(log k)-competitive fractional online algorithm via a marking strategy, where k denotes the size of the cache. We also design a new online rounding algorithm that runs in polynomial time to obtain an O(log k)-competitive randomized integral algorithm. Additionally, we provide a new, simple proof for randomized marking for the classical unweighted paging problem
Optimal Eviction Policies for Stochastic Address Traces
The eviction problem for memory hierarchies is studied for the Hidden Markov
Reference Model (HMRM) of the memory trace, showing how miss minimization can
be naturally formulated in the optimal control setting. In addition to the
traditional version assuming a buffer of fixed capacity, a relaxed version is
also considered, in which buffer occupancy can vary and its average is
constrained. Resorting to multiobjective optimization, viewing occupancy as a
cost rather than as a constraint, the optimal eviction policy is obtained by
composing solutions for the individual addressable items.
This approach is then specialized to the Least Recently Used Stack Model
(LRUSM), a type of HMRM often considered for traces, which includes V-1
parameters, where V is the size of the virtual space. A gain optimal policy for
any target average occupancy is obtained which (i) is computable in time O(V)
from the model parameters, (ii) is optimal also for the fixed capacity case,
and (iii) is characterized in terms of priorities, with the name of Least
Profit Rate (LPR) policy. An O(log C) upper bound (being C the buffer capacity)
is derived for the ratio between the expected miss rate of LPR and that of OPT,
the optimal off-line policy; the upper bound is tightened to O(1), under
reasonable constraints on the LRUSM parameters. Using the stack-distance
framework, an algorithm is developed to compute the number of misses incurred
by LPR on a given input trace, simultaneously for all buffer capacities, in
time O(log V) per access.
Finally, some results are provided for miss minimization over a finite
horizon and over an infinite horizon under bias optimality, a criterion more
stringent than gain optimality.Comment: 37 pages, 3 figure