Cloudbus Toolkit for Market-Oriented Cloud Computing

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape

Towards an MPI-like Framework for Azure Cloud Platform

Message passing interface (MPI) has been widely used for implementing parallel and distributed applications. The emergence of cloud computing offers a scalable, fault-tolerant, on-demand al-ternative to traditional on-premise clusters. In this thesis, we investigate the possibility of adopt-ing the cloud platform as an alternative to conventional MPI-based solutions. We show that cloud platform can exhibit competitive performance and benefit the users of this platform with its fault-tolerant architecture and on-demand access for a robust solution. Extensive research is done to identify the difficulties of designing and implementing an MPI-like framework for Azure cloud platform. We present the details of the key components required for implementing such a framework along with our experimental results for benchmarking multiple basic operations of MPI standard implemented in the cloud and its practical application in solving well-known large-scale algorithmic problems

Survey and Analysis of Production Distributed Computing Infrastructures

This report has two objectives. First, we describe a set of the production distributed infrastructures currently available, so that the reader has a basic understanding of them. This includes explaining why each infrastructure was created and made available and how it has succeeded and failed. The set is not complete, but we believe it is representative. Second, we describe the infrastructures in terms of their use, which is a combination of how they were designed to be used and how users have found ways to use them. Applications are often designed and created with specific infrastructures in mind, with both an appreciation of the existing capabilities provided by those infrastructures and an anticipation of their future capabilities. Here, the infrastructures we discuss were often designed and created with specific applications in mind, or at least specific types of applications. The reader should understand how the interplay between the infrastructure providers and the users leads to such usages, which we call usage modalities. These usage modalities are really abstractions that exist between the infrastructures and the applications; they influence the infrastructures by representing the applications, and they influence the ap- plications by representing the infrastructures

Designing Human-Centered Collective Intelligence

Human-Centered Collective Intelligence (HCCI) is an emergent research area that seeks to bring together major research areas like machine learning, statistical modeling, information retrieval, market research, and software engineering to address challenges pertaining to deriving intelligent insights and solutions through the collaboration of several intelligent sensors, devices and data sources. An archetypal contextual CI scenario might be concerned with deriving affect-driven intelligence through multimodal emotion detection sources in a bid to determine the likability of one movie trailer over another. On the other hand, the key tenets to designing robust and evolutionary software and infrastructure architecture models to address cross-cutting quality concerns is of keen interest in the “Cloud” age of today. Some of the key quality concerns of interest in CI scenarios span the gamut of security and privacy, scalability, performance, fault-tolerance, and reliability. I present recent advances in CI system design with a focus on highlighting optimal solutions for the aforementioned cross-cutting concerns. I also describe a number of design challenges and a framework that I have determined to be critical to designing CI systems. With inspiration from machine learning, computational advertising, ubiquitous computing, and sociable robotics, this literature incorporates theories and concepts from various viewpoints to empower the collective intelligence engine, ZOEI, to discover affective state and emotional intent across multiple mediums. The discerned affective state is used in recommender systems among others to support content personalization. I dive into the design of optimal architectures that allow humans and intelligent systems to work collectively to solve complex problems. I present an evaluation of various studies that leverage the ZOEI framework to design collective intelligence

Ontology-Based Resolution of Cloud Data Lock-in Problem

Cloud computing is nowadays becoming a popular paradigm for the provision of computing infrastructure that enables organizations to achieve financial savings. On the other hand, there are some known obstacles, among which vendor lock-in stands out. Furthermore, due to missing standards and heterogeneities of cloud storage systems, the migration of data to alternative cloud providers is expensive and time-consuming. We propose an approach based on Semantic Web services and AI planning to tackle cloud vendor data lock-in problem. To complete the mentioned task, data structures and data type mapping rules between different types of cloud storage systems are defined. The migration of data among different providers of platform as a service is presented in order to prove the practical applicability of the proposed approach. Additionally, this concept was also applied to software as a service model of cloud computing to perform one-shot data migration from Zoho CRM to Salesforce CRM

A service composition platform in cloud computing using mobile devices for smart shopping

The development of the Next Generation Networks (NGN) such as LTE, WiMax and 5G networks has resulted in the development of more diverse mobile services. Many voice and video services have been developed (e.g. Viber, Skype and WhatsApp). Social networking sites have also been developed (e.g. Facebook, Instagram and Twitter). Users of these services are increasingly expecting and demanding more complex services which have more capabilities that can improve their day to day business. Users want services that are reliable, fast and easy to use. To effectively design and implement services, Service Oriented Architecture (SOA) principles are useful and some of the advantages of designing services using SOA principles are: • Improved interoperability; • Cross platform and cross application integration; • Reusability; • Service composition. Service composition has the advantage that customized services with more features can be developed by combining two or more basic services. In this research, SOA principles are used to design a cloud based Mobile Smart Shopping Service Platform. Canal Walk Shopping Mall, which is located in Cape Town, South Africa is used as a case study. Various mobile services are composed in order to solve the problem of getting information about the services provided by the shopping mall and also to show the available parking bays, which has become a major concern due to the rapid growth of the surrounding residential and business areas. Performance measurements for the Smart Shopping service are then conducted to test its power consumption, memory usage, bandwidth usage and application timeline. Conclusions are drawn and recommendations for possible future development are then provided

Intelligent business processes composition based on mas, semantic and cloud integration (IPCASCI)

[EN]Component reuse is one of the techniques that most clearly contributes to the evolution of the software industry by providing efficient mechanisms to create quality software. Reuse increases both software reliability, due to the fact that it uses previously tested software components, and development productivity, and leads to a clear reduction in cost. Web services have become are an standard for application development on cloud computing environments and are essential in business process development. These services facilitate a software construction that is relatively fast and efficient, two aspects which can be improved by defining suitable models of reuse. This research work is intended to define a model which contains the construction requirements of new services from service composition. To this end, the composition is based on tested Web services and artificial intelligent tools at our disposal. It is believed that a multi-agent architecture based on virtual organizations is a suitable tool to facilitate the construction of cloud computing environments for business processes from other existing environments, and with help from ontological models as well as tools providing the standard BPEL (Business Process Execution Language). In the context of this proposal, we must generate a new business process from the available services in the platform, starting with the requirement specifications that the process should meet. These specifications will be composed of a semi-free description of requirements to describe the new service. The virtual organizations based on a multi-agent system will manage the tasks requiring intelligent behaviour. This system will analyse the input (textual description of the proposal) in order to deconstruct it into computable functionalities, which will be subsequently treated. Web services (or business processes) stored to be reused have been created from the perspective of SOA architectures and associated with an ontological component, which allows the multi-agent system (based on virtual organizations) to identify the services to complete the reuse process. The proposed model develops a service composition by applying a standard BPEL once the services that will compose the solution business process have been identified. This standard allows us to compose Web services in an easy way and provides the advantage of a direct mapping from Business Process Management Notation diagrams

Adapting Microservices in the Cloud with FaaS

This project involves benchmarking, microservices and Function-as-a-service (FaaS) across the dimensions of performance and cost. In order to do a comparison this paper proposes a benchmark framework