{"id":917,"date":"2011-02-18T12:39:22","date_gmt":"2011-02-18T17:39:22","guid":{"rendered":"https:\/\/www.bu.edu\/riscs\/?page_id=917"},"modified":"2020-03-09T15:43:01","modified_gmt":"2020-03-09T19:43:01","slug":"projects","status":"publish","type":"page","link":"https:\/\/www.bu.edu\/riscs\/research\/cloud\/boston-university\/projects\/","title":{"rendered":"Projects"},"content":{"rendered":"<h2>Angels in The Cloud<\/h2>\n<h3>An on Demand Peer-Assisted Content Distribution Cloud Service<\/h3>\n<p>Students: Raymond Sweha, Vatche Ishakian<br \/>\nPIs: Azer Bestavros, John Byers<\/p>\n<p>This project develops a Cloud Service for Internet content  distribution. Our system assists Seeders (content originators) with the  dissemination of content (a file) to a set of nodes using Peer-to-Peer (P2P)  concepts so that this dissemination is completed in the minimum time possible.  Prior results of ours suggest that minimizing content distribution time may be  achieved by adding nodes that are not themselves interested in downloading the  content, but rather in assisting other nodes with their download in a prescribed  (provably optimal) fashion. We call such nodes Angels. The emerging cloud  computing architecture offers the best mechanism to allow such Angels to be  created on-the-fly. As seeders request assistance with their file distribution,  our service responds by spawning virtual machines that act as Angels. In this  work, we describe the design and implementation of our &#8220;Angels-on-Demand&#8221; cloud  service as well as the API for invoking this service.<\/p>\n<h2>Colocation as a Service (CaaS)<\/h2>\n<h3>Strategic and Operational Services for Cloud Colocation<\/h3>\n<p>Students: Vatche Ishakian, Raymond Sweha, Jorge Londo\u00f1o<br \/>\nPIs: Azer Bestavros<\/p>\n<p>By colocating with other tenants of an Infrastructure as a  Service (IaaS) offering, IaaS users could reap significant cost savings by  judiciously sharing their use of the fixed-size instances offered by IaaS  providers. This work presents the blueprints of a Colocation as a Service (CaaS)  framework. CaaS strategic services identify coalitions of selfinterested users  that would benefit from colocation on shared instances. CaaS operational  services provide the information necessary for, and carry out the  reconfigurations mandated by strategic services. CaaS could be incorporated into  an IaaS offering by providers; it could be implemented as a valueadded  proposition by IaaS resellers; or it could be directly leveraged in a  peer-to-peer fashion by IaaS users. To establish the practicality of such  offerings, this paper presents XCS \u2013 a prototype implementation of CaaS on top  of the Xen hypervisor. XCS makes specific choices with respect to the various  elements of the CaaS framework: it implements strategic services based on a  game-theoretic formulation of colocation; it features novel concurrent migration  heuristics which are shown to be efficient; and it offers monitoring and  accounting services at both the hypervisor and VM layers. Extensive experimental  results obtained by running PlanetLab trace-driven workloads on the XCS  prototype confirm the premise of CaaS \u2013 by demonstrating the efficiency and  scalability of XCS, and by quantifying the potential cost savings accrued  through the use of XCS.<\/p>\n<h2>Colocation of  Real-Time Systems<\/h2>\n<p>Students: Vatche Ishakian<br \/>\nPIs: Azer Bestavros, Assaf Kfoury<\/p>\n<p>Desirable application performance is typically guaranteed  through the use of Service Level Agreements (SLAs) that specify \ufb01xed fractions  of resource capacities that must be allocated for unencumbered use by the  application. The mapping between what constitutes desirable performance and SLAs  is not unique: multiple SLA expressions might be functionally equivalent. Having  the \ufb02exibility to transform SLAs from one form to another in a manner that is  provably safe would enable hosting solutions to achieve signi\ufb01cant ef\ufb01ciencies.  This work tries to demonstrate the promise of such an approach by proposing a  type-theoretic framework for the representation and safe transformation of SLAs.<\/p>\n<h2>Embedding Games<\/h2>\n<p>Students: Jorge Londo\u00f1o<br \/>\nPIs: Azer Bestavros, Shang-Hua Teng<\/p>\n<p>Distributed computing infrastructures are ubiquitous:  applications running on the web rely on Cloud infrastructures, scientists run  resource intensive applications on Grid systems, and network architects develop  next generation protocols and services on testbeds such as PlanetLab, Emulab\/Netbed,  and GENI. A common challenge facing all these as well as other systems is  finding and allocating the resources needed in support of such applications and  services. This problem is generally known as the network <em>embedding problem<\/em>\/<\/p>\n<p><em>Embedding Games<\/em> arise when multiple competing agents  engage in solving the network embedding problem, with each agent trying to  maximize its own benefit. From a modeling and analysis perspective, important  questions that arise in this context include determining whether and under what  conditions do equilibria governing agent interactions exist, whether convergence  to such equilibria is assured, and the extent of the inefficiencies associated  with these equilibria. From a system design perspective, the main challenge is  that of designing mechanisms that provide incentives that ensure that the  choices of the non-cooperating, selfish agents engaged in an embedding game lead  to an efficient allocation of resources from a system-wide perspective.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Angels in The Cloud An on Demand Peer-Assisted Content Distribution Cloud Service Students: Raymond Sweha, Vatche Ishakian PIs: Azer Bestavros, John Byers This project develops a Cloud Service for Internet content distribution. Our system assists Seeders (content originators) with the dissemination of content (a file) to a set of nodes using Peer-to-Peer (P2P) concepts so [&hellip;]<\/p>\n","protected":false},"author":3458,"featured_media":0,"parent":908,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/pages\/917"}],"collection":[{"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/users\/3458"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/comments?post=917"}],"version-history":[{"count":16,"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/pages\/917\/revisions"}],"predecessor-version":[{"id":1508,"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/pages\/917\/revisions\/1508"}],"up":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/pages\/908"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/riscs\/wp-json\/wp\/v2\/media?parent=917"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}