Elastic Provisioning of Cloud Caches: a Cost-aware TTL Approach

We consider elastic resource provisioning in the cloud, focusing on in-memory key-value stores used as caches. Our goal is to dynamically scale resources to the traffic pattern minimizing the overall cost, which includes not only the storage cost, but also the cost due to misses. In fact, a small variation on the cache miss ratio may have a significant impact on user perceived performance in modern web services, which in turn has an impact on the overall revenues for the content provider that uses those services. We propose and study a dynamic algorithm for TTL caches, which is able to obtain close-to-minimal costs. Since high-throughput caches require low complexity operations, we discuss a practical implementation of such a scheme requiring constant overhead per request independently from the cache size. We evaluate our solution with real-world traces collected from Akamai, and show that we are able to obtain a 17% decrease in the overall cost compared to a baseline static configuration

The RING 2.0 web server for high quality residue interaction networks

open3noopenPiovesan, Damiano; Minervini, Giovanni; Tosatto, Silvio c.E.Piovesan, Damiano; Minervini, Giovanni; Tosatto, Silvi

A\c{C}AI: Ascent Similarity Caching with Approximate Indexes

Similarity search is a key operation in multimedia retrieval systems and recommender systems, and it will play an important role also for future machine learning and augmented reality applications. When these systems need to serve large objects with tight delay constraints, edge servers close to the end-user can operate as similarity caches to speed up the retrieval. In this paper we present A\c{C}AI, a new similarity caching policy which improves on the state of the art by using (i) an (approximate) index for the whole catalog to decide which objects to serve locally and which to retrieve from the remote server, and (ii) a mirror ascent algorithm to update the set of local objects with strong guarantees even when the request process does not exhibit any statistical regularity

Studies of the Site and Distribution of CD34+ Cells in Idiopathic Myelofibrosis

n/

Grass-FedMilk Perception: Profiling Italian Consumer

This paper aims at analyzing the consumers’ perception of grass-fed milk so as to understand if a production based on a sustainable business model could represent a response to new and emerging needs in consumption. The sample of the study was constituted by a total of 750 Italian members of the International Association Slow Food. A Principal Component Analysis (PCA) was used to summarize the quantitative variables, which, grouped in “dimensions”, were used as input for multivariate statistics (HCA, MCA) in order to define and explain consumer profiles. Our data confirm an in-progress change in milk consumption: Consumers were more oriented towards quality, local supply chains, traceability, and are characterized by an increasing propensity to a higher expense for grass-fed milk. Further research will enlarge the proposed panorama covering a sample of more general consumers. The study was a preliminary market analysis that could be used as the basis for a production, distribution, and consumption chain grass-fed-based model. Grass-fed milk is a product linking individual and societal needs for more sustainable production and entrepreneurship that creates a higher value product aligned with market needs

Cronache della pandemia

Il saggio è costituito da un dialogo immaginario tra due docenti universitari a 10 anni di distanza dallo scoppio della pandemia di COVID19. In forma di dialogo vengono discussi alcuni problemi filosofico-giuridici generati dall'evento pandemico, quali l'uso della didattica a distanza nell'università, il ricorso a misure giuridiche emergenziali, il bilanciamento tra i diritti fondamentali coinvolti

Taking two Birds with one k-NN Cache

International audiencek-Nearest Neighbors aims at efficiently finding items close to a query in a large collection of objects, and it is used in different applications, from image retrieval to recommendation. These applications achieve high throughput combining two different elements: 1) approximate nearest neighbours searches that reduce the complexity at the cost of providing inexact answers and 2) caches that store the most popular items. In this paper we propose to combine the approximate index for the whole catalog with a more precise index for the items stored in the cache. Our experiments on realistic traces show that this approach is doubly advantageous as it 1) improves the quality of the final answer provided to a query, 2) additionally reduces the service latency