Giacomo Carito - Appunti per una storia dell'alimentazione e della gastronomia in Terra di Brindisi, in Sapori della Terra di Brindisi, Brindisi: Inner Wheel Italia, 2012, pp. 7-25.
Pubblicazione negli atti del convegno “Mi ricordo il mulino” tenutosi al centro espositivo del Chiapparino di Cicagna (GE) nel 1998, esito di una approfondita ricerca di "Archeologia industriale" nel territorio di Moneglia e Varese... more
Pubblicazione negli atti del convegno “Mi ricordo il mulino” tenutosi al centro espositivo del Chiapparino di Cicagna (GE) nel 1998, esito di una approfondita ricerca di "Archeologia industriale" nel territorio di Moneglia e Varese Ligure, confronto fra mulini e frantoi
Application performance has been and remains one of top five concerns since the inception of cloud computing. A primary determinant of application performance is multitenancy or sharing of hardware resources in clouds. While some hardware... more
Application performance has been and remains one of top five concerns since the inception of cloud computing. A primary determinant of application performance is multitenancy or sharing of hardware resources in clouds. While some hardware resources can be partitioned well among VMs (such as CPUs), many others cannot (such as memory bandwidth). In this paper, we focus on understanding the variability in application performance on a cloud and explore ways for an end customer to deal with it. Based on rigorous experiments using CloudSuite, a popular Web2.0 benchmark, running on EC2, we found that interference-induced performance degradation is a reality. On a private cloud testbed, we also observed that interference impacts the choice of best configuration values for applications and middleware. We posit that intelligent reconfiguration of application parameters presents a way for an end customer to reduce the impact of interference. However, tuning the application to deal with interference is challenging because of two fundamental reasons — the configuration depends on the nature and degree of interference and there are inter-parameter dependencies. We design and implement the IC2 system (Interference-aware Cloud application Configuration) to address the challenges of detection and mitigation of performance interference in clouds. Compared to an interference-agnostic configuration, the proposed solution provides up to 29% and 40% improvement in average response time on EC2 and a private cloud testbed respectively.
Performance degradation due to imperfect isola- tion of hardware resources such as cache, network, and I/O has been a frequent occurrence in public cloud platforms. A web server that is suffering from performance interference degrades... more
Performance degradation due to imperfect isola-
tion of hardware resources such as cache, network, and I/O has
been a frequent occurrence in public cloud platforms. A web
server that is suffering from performance interference degrades interactive user experience and results in lost revenues. Existing work on interference mitigation tries to address this problem by intrusive changes to the hypervisor, e.g., using intelligent schedulers or live migration, many of which are available only to infrastructure providers and not end consumers. In this paper, we present a framework for administering webserver clusters where effects of interference can be reduced by intelligent reconfiguration. Our controller, ICE, improves webserver performance during interference by performing two-fold autonomous reconfigurations. First, it reconfigures the load balancer at the ingress point of the server cluster and thus reduces load on the impacted server. ICE then reconfigures the middleware at the impacted server to reduce its load even further. We implement and evaluate ICE on CloudSuite, a popular web application benchmark, and with two popular load balancers - HAProxy and LVS. Our experiments in a private cloud testbed show that ICE can improve median response time of web servers by upto 94% compared to a statically configured server cluster. ICE also outperforms an adaptive load balancer (using least connection scheduling) by upto 39%.
