Notes on Cloud computing principles

This letter provides a review of fundamental distributed systems and economic Cloud computing principles. These principles are frequently deployed in their respective fields, but their inter-dependencies are often neglected. Given that Cloud Computing first and foremost is a new business model, a new model to sell computational resources, the understanding of these concepts is facilitated by treating them in unison. Here, we review some of the most important concepts and how they relate to each other

Pricing the Cloud: An Auction Approach

Cloud computing has changed the processing and service modes of information communication technology and has affected the transformation, upgrading and innovation of the IT-related industry systems. The rapid development of cloud computing in business practice has spawned a whole new field of interdisciplinary, providing opportunities and challenges for business management research. One of the critical factors impacting cloud computing is how to price cloud services. An appropriate pricing strategy has important practical means to stakeholders, especially to providers and customers. This study addressed and discussed research findings on cloud computing pricing strategies, such as fixed pricing, bidding pricing, and dynamic pricing. Another key factor for cloud computing is Quality of Service (QoS), such as availability, reliability, latency, security, throughput, capacity, scalability, elasticity, etc. Cloud providers seek to improve QoS to attract more potential customers; while, customers intend to find QoS matching services that do not exceed their budget constraints. Based on the existing study, a hybrid QoS-based pricing mechanism, which consists of subscription and dynamic auction design, is proposed and illustrated to cloud services. The results indicate that our hybrid pricing mechanism has potential to better allocate available cloud resources, aiming at increasing revenues for providers and reducing expenses for customers in practice

Optimal Posted Prices for Online Cloud Resource Allocation

We study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either takes the current prices, renting resources to execute its job, or refuses the prices without running its job there. We design pricing functions based on the current resource utilization ratios, in a wide array of demand-supply relationships and resource occupation durations, and prove worst-case competitive ratios of the pricing functions in terms of social welfare. In the basic case of a single-type, non-recycled resource (i.e., allocated resources are not later released for reuse), we prove that our pricing function design is optimal, in that any other pricing function can only lead to a worse competitive ratio. Insights obtained from the basic cases are then used to generalize the pricing functions to more realistic cloud systems with multiple types of resources, where a job occupies allocated resources for a number of time slots till completion, upon which time the resources are returned back to the cloud resource pool

Modeling of Utility Distribution Feeder in OpenDSS with Steady State Impact Analysis of Distributed Generation

With the deregulation of the electric power industry and the advancement of new technologies, the attention of the utilities has been drawn towards adopting Distributed Generation (DG) into their existing infrastructure. The deployment of DG brings ample technological and environmental benefits to the traditional distribution networks. The appropriate sizing and placement of DGs which generate power locally to fulfill consumer demands, helps to reduce power losses and avoid transmission and distribution system expansion.;The primary objective of this thesis is to model a utility distribution feeder in OpenDSS. Studies are conducted on the data obtained from American Electric Power utility. This thesis develops models for 12.47 kV (medium voltage) distribution feeders in OpenDSS by utilizing the existing models in CYMDIST. The model conversion is achieved by a detailed one-to-one component matching approach for multi phased lines, conductors, underground cables, loads, regulators and capacitor banks. The power flow results of OpenDSS and CYMDIST are compared to derive important conclusions.;The second major objective is to analyze the impacts of DG on distribution systems and two focus areas are chosen, namely: effect on voltage profiles and losses of the system and the effects on power market operation. To analyze the impacts of DG on the distribution systems, Photovoltaic (PV) system with varying penetration levels are integrated at different locations along the developed feeder model. PV systems are one of the fastest growing DG technologies, with a lot of utilities in North America expressing interest in its implementation. Many utilities either receive incentives or are mandated by green-generation portfolio regulations to install solar PV systems on their feeders. The large number of PV interconnection requests to the utilities has led to typical studies in the areas of power quality, protection and operation of distribution feeders. The high penetration of PV into the system throws up some interesting implications for the utilities. Bidirectional power flow into a distribution system, (which is designed for one way power flow) may impact system voltage profiles and losses. In this thesis, the effects of voltage unbalance and the losses of the feeder are analyzed for different PV location and penetration scenarios.;Further, this thesis tries to assess the impact of DG on power market operations. In a deregulated competitive market, Generation companies (Genco) sell electricity to the Power exchange (PX) from which large customers such as distribution companies (Disco) and aggregators may purchase electricity to meet their needs through a double sided bidding system. The reliable and efficient operation of this new market structure is ensured by an independent body known as the Independent System Operator (ISO). Under such a market structure, a particular type of unit commitment, called the Price Based Unit Commitment (PBUC) is used by the Genco to determine optimal bids in order to maximize its profit. However, the inclusion of intermittent DG resources such as wind farms by the Gencos causes uncertainty in PBUC schedules. In this research, the effects of intermittency in the DG resource availability on the PBUC schedule of a Genco owning a distribution side wind farm are analyzed

Cloud Market Maker: An automated dynamic pricing marketplace for cloud users

© 2015 Elsevier B.V. Abstract Cloud providers commonly incur heavy upfront set up costs which remain almost constant whether they serve a single or many customers. In order to generate a return on this investment, a suitable pricing strategy is required by providers. Established industries such as the airlines employ dynamic pricing to maximize their revenues. In order to increase their resource utilization rates, cloud providers could also use dynamic pricing for their services. At present however most providers use static schemes for pricing their resources. This work presents a new dynamic pricing mechanism for cloud providers. Furthermore, at present no platform exists that provides a dynamic unified view of the different cloud offerings in real-time. Due to a rapidly changing landscape and a limited knowledge of the cloud marketplace, consumers can often end up choosing a cloud provider that is more expensive or does not give them what they really need. This is because some providers spend significantly on advertising their services online. In order to assist cloud customers in the selection of a suitable resource and cloud providers in implementing dynamic pricing, this work describes an automated dynamic pricing marketplace and a decision support system for cloud users. We present a multi-agent multi-auction based system through which such services are delivered. An evaluation has been carried out to determine how effectively the Cloud Market Maker selects the resource, dynamically adjusts the price for the cloud users and the suitability of dynamic pricing for the cloud environment

Idle block based methods for cloud workflow scheduling with preemptive and non-preemptive tasks

[EN] Complex workflow applications are widely used in scientific computing and economic analysis, which commonly include both preemptive and non-preemptive tasks. Cloud computing provides a convenient way for users to access different resources based on the ¿pay-as-you-go¿ model. However, different resource renting alternatives (reserved, on-demand or spot) are usually provided by the service provider. The spot instances provide a dynamic and cheaper alternative comparing to the on-demand one. However, failures often occur due to the fluctuations of the price of the instance. It is a big challenge to determine the appropriate amount of spot and on-demand resources for workflow applications with both preemptive and non-preemptive tasks. In this paper, the workflow scheduling problem with both spot and on-demand instances is considered. The objective is to minimize the total renting cost under deadline constrains. An idle time block-based method is proposed for the considered problem. Different idle time block-based searing and improving strategies are developed to construct schedules for workflow applications. Schedules are improved by a forward and backward moving mechanism. Experimental and statistical results demonstrate the effectiveness of the proposed algorithm over a lot of tests with different sizes.This work is supported by the National Natural Science Foundation of China (No. 61572127, 61272377), the National Key Research and Development Program of China (No. 2017YFB1400800). Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards" (No. DPI2015-65895-R) financed by FEDER funds.Chen, L.; Li, X.; Ruiz García, R. (2018). Idle block based methods for cloud workflow scheduling with preemptive and non-preemptive tasks. Future Generation Computer Systems. 89:659-669. https://doi.org/10.1016/j.future.2018.07.037S6596698