1,720,956 research outputs found
SQLR: Short-Term Memory Q-Learning for Elastic Provisioning
No full textAs a growing number of service and application providers choose cloud networks to deliver their services on a software-as-a-service (SaaS) basis, cloud providers need to make their provisioning systems agile enough to meet service level agreements (SLAs). At the same time, they should guard against over-provisioning, which limits their capacity to accommodate more tenants. To this end, we propose Shortterm memory Q-Learning pRovisioning (SQLR, pronounced as 'scaler'), a system employing a customized variant of the modelfree reinforcement learning algorithm. It can reuse contextual knowledge learned from one workload to optimize the number of virtual machines (resources) allocated to serve other workload patterns. With minimal overhead, SQLR achieves comparable results to systems where resources are unconstrained. Our experiments show that we can reduce the amount of provisioned resources by about 20% with less than 1% overall service unavailability (due to blocking), while delivering similar response times to those of an over-provisioned system
Driving under influence: Robust controller migration for MEC-enabled platooning
No full textConnected cars are becoming more common. With the development of multi-access edge computing (MEC) for low-latency applications, it will be possible to manage the cooperative adaptive cruise control (CACC, also known as platooning) of such vehicles from the edge of cellular networks. In this paper, we present a controller that manages platooning from the network edge by adapting to varying network conditions. We incorporate a mechanism in the controller that allows vehicles to switch to automated cruise control when delays exceed safety thresholds, and back to platooning when the delays are sufficiently low to support it. We also formulate the problem of maintaining a low-latency connection in the presence of high mobility through migration, and propose a Q-Learning algorithm to solve this problem. We finally propose an Asynchronous Shared Learning scheme that enables multiple migration agents to cooperate, in order to expedite the convergence of migration policies. Compared to state-of-the-art migration techniques, our scheme exhibits better compliance of vehicle speed and spacing values to preset targets, and ameliorates statistical dispersion
Copy-CAV: V2X-enabled wireless towing for emergency transport
Full text linkAs smart connected vehicles become increasingly common and pave the way for the autonomous vehicles of the future, their ability to provide enhanced safety and assistance services has improved. One such service is the emergency transport of drivers in medical distress: as a positive solution of the distress is typically more likely after timely response, an autonomous vehicle could cut on emergency response times, and thus play a key role in saving the life of its driver. In this paper, we show how such an autonomous emergency transport service can be run from a wireless cellular network, and discuss the importance of having a human in the loop in order to expedite driving. We present a Monte-Carlo-based driver assessment system that the network can use when selecting the most suitable candidate to wirelessly tow an autonomous vehicle with an incapacitated driver. We show that this mechanism results in a selection policy that ensures better cohesion between the vehicles, thereby significantly improving service reliability by reducing the chances of disruptions by intervening traffic
When less is more: Core-restricted container provisioning for serverless computing
No full textCloud applications are exposed to workloads whose intensity can change unpredictably over time. Hence, the ability to quickly scale the amount of computing resources provisioned to applications is essential to minimize costs while providing reliable services. In this context, containers are deemed to be a promising technology to enable fast elasticity in resource allocation schemes. In this paper, we propose and experimentally test an efficient container-based cloud computing provisioning system. First, we address the container deployment problem and discuss how to manage container provisioning and scaling. Second, we devise a resource management mechanism leveraging on both admission control and auto-scaling techniques. We propose to drive auto-scaling decisions through a Q-Learning algorithm, which is agnostic to the specific computing environment, and proceeds based only on the load of the physical processors assigned to a container. We evaluate our solution in two experimental setups, and show that it yields significant advantages when compared to popular container managers such as Kubernetes
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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