There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

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A Break in the Clouds: Towards a Cloud Definition

The Internet of Things (IoT) could enable innovations that enhance the quality of life, but it generates unprecedented amounts of data that are difficult for traditional systems, the cloud, and even edge computing to handle. Fog computing is designed to overcome these limitations.

Fog Computing: Helping the Internet of Things Realize Its Potential

All one needs to know about fog computing and related edge computing paradigms: A complete survey

http://faculty.ecnu.edu.cn/picture/article/2443/32/9a/e69148ae413b841a37228a6df5be/4759bd97-b523-4101-83b5-15f52f416943.pdf

A data placement strategy in scientific cloud workflows

A cloud workflow system is a type of platform service which facilitates the automation of distributed applications based on the novel cloud infrastructure. One of the most important aspects which differentiate a cloud workflow system from its other counterparts is the market-oriented business model. This is a significant innovation which brings many challenges to conventional workflow scheduling strategies. To investigate such an issue, this paper proposes a market-oriented hierarchical scheduling strategy in cloud workflow systems. Specifically, the service-level scheduling deals with the Task-to-Service assignment where tasks of individual workflow instances are mapped to cloud services in the global cloud markets based on their functional and non-functional QoS requirements; the task-level scheduling deals with the optimisation of the Task-to-VM (virtual machine) assignment in local cloud data centres where the overall running cost of cloud workflow systems will be minimised given the satisfaction of QoS constraints for individual tasks. Based on our hierarchical scheduling strategy, a package based random scheduling algorithm is presented as the candidate service-level scheduling algorithm and three representative metaheuristic based scheduling algorithms including genetic algorithm (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO) are adapted, implemented and analysed as the candidate task-level scheduling algorithms. The hierarchical scheduling strategy is being implemented in our SwinDeW-C cloud workflow system and demonstrating satisfactory performance. Meanwhile, the experimental results show that the overall performance of ACO based scheduling algorithm is better than others on three basic measurements: the optimisation rate on makespan, the optimisation rate on cost and the CPU time.

http://faculty.ecnu.edu.cn/picture/article/2443/32/9a/e69148ae413b841a37228a6df5be/bd11cc93-7e68-4c46-8d45-e2ac334532d7.pdf

A market-oriented hierarchical scheduling strategy in cloud workflow systems

The concept of cloud computing continues to spread widely, as it has been accepted recently. Cloud computing has many unique advantages which can be utilized to facilitate workflow execution. Instance-intensive cost-constrained cloud workflows are workflows with a large number of workflow instances (i.e. instance intensive) bounded by a certain budget for execution (i.e. cost constrained) on a cloud computing platform (i.e. cloud workflows). However, there are, so far, no dedicated scheduling algorithms for instance-intensive cost-constrained cloud workflows. This paper presents a novel compromised-time-cost scheduling algorithm which considers the characteristics of cloud computing to accommodate instance-intensive cost-constrained workflows by compromising execution time and cost with user input enabled on the fly. The simulation performed demonstrates that the algorithm can cut down the mean execution cost by over 15% whilst meeting the user-designated deadline or shorten the mean execution time by over 20% within the user-designated execution cost.

A Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for Instance-Intensive Cost-Constrained Workflows on a Cloud Computing Platform

http://faculty.ecnu.edu.cn/picture/article/2443/32/9a/e69148ae413b841a37228a6df5be/b46686e6-a142-49b2-8455-3c9c9f9ae43b.pdf

On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

Nowadays, large-scale Cloud-based applications have put forward higher demand for storage ability of data centres. Data in the Cloud need to be stored with high efficiency and cost effectiveness while meeting the requirement of reliability. While in current Cloud systems, typical 3-replicas data replication strategies are applied for data reliability, in this paper we propose a novel cost-effective dynamic data replication strategy which facilitates an incremental replication method to reduce the storage cost and meet the data reliability requirement at the same time. This replication strategy works very well especially for data which are only used temporarily and/or have a relatively low reliability requirement. The simulation shows that our replication strategy for reliability can reduce the data storage cost in data centres substantially.

Dong Yuan

Papers

A data placement strategy in scientific cloud workflows

A market-oriented hierarchical scheduling strategy in cloud workflow systems

A Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for Instance-Intensive Cost-Constrained Workflows on a Cloud Computing Platform

On-demand minimum cost benchmarking for intermediate dataset storage in scientific cloud workflow systems

A Novel Cost-Effective Dynamic Data Replication Strategy for Reliability in Cloud Data Centres