Caesar Wu - Academia.edu (original) (raw)

Papers by Caesar Wu

Cloud Data Centers and Cost Modeling, 2015

The content of this chapter is mainly divided into five topics: data center network (DCN) hardwar... more The content of this chapter is mainly divided into five topics: data center network (DCN) hardware, DCN terms, DCN metrics, DCN topologies, and characteristics of a cloud DCN. In terms of DCN topology, it starts with basic tree topology, which is highly recommended by one of the network equipment vendors, Cisco, and then the chapter discusses the fat tree, DCell, BCube, VL2, butterfly, and dragonfly topologies. Again, the main aim of these discussions is to highlight characteristics of each topology and associated costs for business needs. The section on cloud DCNs in this chapter covers four types of network: management, kernel, virtual machine, and virtualized storage.

Cloud Data Centers and Cost Modeling, 2015

This chapter unfolds the details of a cost model and cost framework. It begins with the concept, ... more This chapter unfolds the details of a cost model and cost framework. It begins with the concept, terms, and definitions related to a cost model and then it gives a functional definition of a cost model. In order to resolve the fundamental issue, namely making the right strategy decision, this chapter highlights many challenges in term of cost modeling.

Cloud Data Centers and Cost Modeling, 2015

This chapter shows how to establish a cost framework based on business revenue projections or for... more This chapter shows how to establish a cost framework based on business revenue projections or forecasting. The case study is about a leading web portal company serving the real estate business. The estimated cost is the static and linear NPV value. This analysis method can be considered a tactical or stack layer-based analysis.

Cloud Data Centers and Cost Modeling, 2015

This chapter discusses the topic of how to measure the usage of a cloud or shared infrastructure.... more This chapter discusses the topic of how to measure the usage of a cloud or shared infrastructure. This is not a new concept, but rather an old idea with a new application: the cloud. It mainly focuses on the issue of cloud operations. The idea in emphasizing chargeback is to understand how the cloud cost should be allocated for different Line of Business (LoB) units. The chargeback exercise makes the cost model assumptions much more rational and objective. The ultimate goal of a chargeback is to make the cloud cost as transparent as possible.

Cloud Data Centers and Cost Modeling, 2015

Chapter 5 mainly deals with data center power. The introduction of this chapter gives a brief int... more Chapter 5 mainly deals with data center power. The introduction of this chapter gives a brief introduction to the basic concepts of data center power. Following the basic concepts, this chapter lays out four major power elements: the circuit breaker, transfer switches (STS and ATS), generators, and UPS. For each power element, this chapter also identifies the characteristics and associated costs.

Cloud Data Centers and Cost Modeling, 2015

However, the word “utility” is very ambiguous and often confusing. One of the primary reasons is ... more However, the word “utility” is very ambiguous and often confusing. One of the primary reasons is that it has many different connotations [16]. The common sense of utility means “the usefulness of something, especially in a practical way.” For example, the utility of database means to implement various processes or functions of the database, such as batch update, rebuild, recovery, backup, etc. Another sense of utility is quite close to the meaning of the usefulness that often refers to the state of being useful, which is to supply the basic infrastructure services to the general public. These services are offered by incumbent service providers, which are called “public utilities” or simply, “utilities.” Buyya et al. [35] defined the infrastructure of “cloud computing” as the 5 utility. Another meaning of utility is the utilization rate, which is to measure effective usage of something.

Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to fac... more Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to facilitate the development of cloud data centers. Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge. The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues. After laying a foundation of cloud concepts and definitions, the book addresses data center creation, infrastructure development, cost modeling, and simulations in decision-making, each part building on the previous. In this way the authors bridge technology, management, and infrastructure as a service, in one complete guide to data centers that facilitates educated decision making. Explains how to balance cloud compu...

Future Generation Computer Systems

ACM Computing Surveys

This article provides a systematic review of cloud pricing in an interdisciplinary approach. It e... more This article provides a systematic review of cloud pricing in an interdisciplinary approach. It examines many historical cases of pricing in practice and tracks down multiple roots of pricing in research. The aim is to help both cloud service provider (CSP) and cloud customers to capture the essence of cloud pricing when they need to make a critical decision either to achieve competitive advantages or to manage cloud resource effectively. Currently, the number of available pricing schemes in the cloud market is overwhelming. It is an intricate issue to understand these schemes and associated pricing models clearly due to involving several domains of knowledge, such as cloud technologies, microeconomics, operations research, and value theory. Some earlier studies have introduced this topic unsystematically. Their approaches inevitably lead to much confusion for many cloud decision-makers. To address their weaknesses, we present a comprehensive taxonomy of cloud pricing, which is driv...

IEEE Transactions on Cloud Computing

Cloud service providers (CSP) and cloud consumers often demand to forecast the cloud price in ord... more Cloud service providers (CSP) and cloud consumers often demand to forecast the cloud price in order to optimize their business strategy. However, pricing of cloud services is a challenging task due to its services complexity and dynamic nature of the ever-changing environment. Moreover, the cloud pricing based on consumers' willingness to pay (W2P) becomes even more challenging due to the subjectiveness of consumers' experiences and implicit values of some non-marketable prices, such as burstable CPU, dedicated server, and cloud data center global footprints. Unfortunately, many existing pricing models often cannot support value-based pricing. In this paper, we propose a novel solution based on value-based pricing, which does not only consider how much does the service cost (or intrinsic values) to a CSP but also how much customer is willing to pay (or extrinsic values) for the service. We demonstrate that the cloud extrinsic values would not only become one of the competitive advantages for CSPs to lead the cloud market but also increase the profit margin. Our approach is often referred to as a hedonic pricing model. We show that our model can capture the value of non-marketable price. This value is about 43.4% on average above the baseline, which is often ignored by many traditional cloud pricing models. We also show that Average Annual Growth Rate (AAGR) of Amazon Web Services' (AWS) is about-20.0% per annum between 2008 and 2017, ceteris paribus. In comparison with Moore's law (-50% per annum), it is at a far slower pace. We argue this value is Moore's law equivalent in the cloud. The primary goal of this research is to provide a less biased pricing model for cloud decision makers to develop their optimizing investment strategy.

Future Generation Computer Systems

Proceedings of the 13th International Conference on Software Technologies

Cloud Data Centers and Cost Modeling, 2015

Future Generation Computer Systems

ACM Computing Surveys

IEEE Transactions on Cloud Computing

Future Generation Computer Systems

Proceedings of the 13th International Conference on Software Technologies

Cloud Data Centers and Cost Modeling, 2015