[cs-talks] FW: Ph.D. Thesis Proposal, Maryam Ghasemi, Wed. August 17, 1pm, MCS 148

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Tue Aug 9 12:08:55 EDT 2016

From: <owner-cs-phds-sec at bu.edu<mailto:owner-cs-phds-sec at bu.edu>> on behalf of "Matta, Abraham I" <matta at bu.edu<mailto:matta at bu.edu>>
Date: Friday, August 5, 2016 at 9:57 PM
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Cc: "Streubel, Jennifer" <jenn4 at bu.edu<mailto:jenn4 at bu.edu>>
Subject: Ph.D. Thesis Proposal, Maryam Ghasemi, Wed. August 17, 1pm, MCS 148

Ph.D. Thesis Proposal

Multi-attribute Demand Characterization and Layered Service Pricing

Maryam Ghasemi, Boston University

Wednesday, August 17, 2016 at 1:00pm in MCS 148


As cloud computing gains popularity, understanding the pattern and structure of its workload is increasingly important in order to drive effective resource allocation and pricing decisions. In the cloud model, virtual machines (VMs), each consisting of a bundle of computing resources, e.g., CPU, memory, network, and storage, are presented to users for purchase. Thus, the cloud context requires multi-attribute models of demand. While most of the available studies have focused on one specific attribute of a virtual request (process) such as CPU runtime or memory, to the best of our knowledge there is no work on the joint distribution of resource usage. In this dissertation, we develop a joint distribution model that effectively captures the relationship among multiple resources by carefully fitting both the marginal distribution of each resource type as well as the non-linear structure of their correlation via a copula distribution. We validate several choices for both marginal and joint models using a public data set of Google data center usage.

Constructing the demand model is essential for provisioning revenue-optimal configuration for VMs or quality of service (QoS) offered by a provider. In the second part of the dissertation, we turn to the service pricing problem in a multi-provider setting: given service configurations (qualities) offered by different providers, choose a proper price for each offered service to undercut competitors and attract customers. With the rise of layered service-oriented architectures there is a need for more advanced solutions that manage the interactions among service providers at multiple levels. Brokers, as the intermediaries between customers and lower-level providers, play a key role in improving the efficiency of service-oriented structures by matching the demands of customers to the services of providers. We analyze a layered market in which service brokers and service providers compete at different levels in an oligopoly market to maximize their profit. In our setting, players at each level compete in a Bertrand game while they offer different QoS. We examine the interaction among players and the effect of price competition on their market shares. ​​


Abraham Matta (Advisor)

Steve Homer

Azer Bestavros

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