IT Security and Governance Compliant Service Oriented Computing in Cloud Computing Environments

The authors present the key security challenges and solutions on the Cloud with the help of literature reviews and an experimental model created on OPNET that is simulated to produce useful statistics to establish the approach that the Cloud computing service providers should take to provide optimal security and compliance. The literature recommends the concept of unified threat management for ensuring secured services on the Cloud. Through the simulation results, the authors demonstrate that UTM may not be a feasible approach to security implementation as it may become a bottleneck for the application Clouds. The fundamental benefits of Cloud computing (resources on demand and high elasticity) may be diluted if UTMs do not scale up effectively as per the traffic loads on the application Clouds. Moreover, it is not feasible for application Clouds to absorb the performance degradation for security and compliance because UTM will not be a total solution for security and compliance. Applications also share the vulnerabilities just like the systems, which will be out of UTM Cloud’s control.

Cloud Computing for Scientific Simulation and High Performance Computing

This chapter describes experiences using Cloud infrastructures for scientific computing, both for serial and parallel computing. Amazon’s High Performance Computing (HPC) Cloud computing resources were compared to traditional HPC resources to quantify performance as well as assessing the complexity and cost of using the Cloud. Furthermore, a shared Cloud infrastructure is compared to standard desktop resources for scientific simulations. Whilst this is only a small scale evaluation these Cloud offerings, it does allow some conclusions to be drawn, particularly that the Cloud can currently not match the parallel performance of dedicated HPC machines for large scale parallel programs but can match the serial performance of standard computing resources for serial and small scale parallel programs. Also, the shared Cloud infrastructure cannot match dedicated computing resources for low level benchmarks, although for an actual scientific code, performance is comparable.

Internet-Based Virtual Computing Infrastructure for Cloud Computing

Virtualisation is massively important in computing and continues to develop. This chapter discusses and evaluates the virtualisation technologies and in particular, a state-of-art system called iVIC (the Internet-based Virtual Computing) developed by Beihang University, China as it provides an all-in-one example of many of the major headline Cloud Computing titles of SaaS, IaaS, and HaaS. The chapter considers several virtualization packages which are either commercial, community, or experimental, before focusing on iVIC, a virtual machine cloning system that may be beneficial in a learning or office environment. The chapter introduces a test environment which is used to assess the performance of the iVIC process and the virtual machines created. Power requirements of virtual, as opposed to physical machines, are compared and evaluated. The chapter closes with conclusions regarding virtualisation and iVIC.

An Infrastructure-as-a-Service Cloud

Cloud computing allows business customers to elastically scale up and down their resource usage based on needs. This feature eliminates the dilemma of planning IT infrastructures for Cloud users, where under-provisioning compromises service quality while over-provisioning wastes investment as well as electricity. It offers virtually infinite resource. It also made the desirable “pay as you go” accounting model possible. The above touted gains in the Cloud model come from on-demand resource provisioning technology. In this chapter, the authors elaborate on such technologies incorporated in a real IaaS system to exemplify how Cloud elasticity is implemented. It involves the resource provisioning technologies in hypervisor, Virtual Machine (VM) migration scheduler and VM replication. The authors also investigate the load prediction algorithm for its significant impacts on resource allocation.

An Efficient, Robust, and Secure SSO Architecture for Cloud Computing Implemented in a Service Oriented Architecture

Implementing Single Sign-On (SSO) in a Cloud space for a spectrum of services and applications is an interesting research avenue for scientific communities in the field of secure identity and access management for Cloud Computing. Using an SSO implementation, in the backend, users can navigate any or all of the supported applications or resources without the need to repeatedly provide credentials. In this chapter, the authors present an efficient and robust Cloud Single Sign-On Architecture (CSSOA) model based on a token security mechanism. Service Oriented Architectures (SOAs) are one of the enabling technologies for solving complex service oriented real world challenges, and hence, CSSOA has been implemented using SOAs. In the authors’ CSSOA model, a CSSO SOAP authentication service is distributed among the Cloud servers while the CSSO database service is centralized.

Cloud Computing

Defining Cloud Computing can be difficult, as each organization often has its own spin on the definition. Despite being hard to define, Gartner Research named Cloud Computing as one of the top technologies to watch in 2010, 2011, and 2012. At its core, Cloud Computing is a technical architecture that meets a specific business need. This chapter traces the roots of Cloud Computing from its origins in mainframe distributed computing, discusses the basics of the Cloud Computing model today, and offers insights for future directions that are likely to be pursued in the Cloud Computing arena. A number of challenges to Cloud Computing are identified, including concerns of security and how to deal with the rise of mobile computing. The chapter ends with recommendations on how to choose which Cloud model is most appropriate to meet your organization’s needs and how to establish a successful Cloud strategy.

Cloud Computing Diagnosis

Cloud Computing is emerging as a promising cost efficient computing paradigm which professionals believe is an absolutely new trend and will represent next level of internet evolution. Though the presence of Cloud computing is ubiquitous, it still lacks consensus on a proper definition and classification of the major Clouds in effect today. It also suffers from major criticism of being a hype/fad and some researchers claim that it is just an extension of already established computing paradigms. This chapter attempts to deal with such criticisms by comprehensively analyzing the Cloud definitions and diagnose the components of the same. It performs a comprehensive study of more than 30 definitions given by Cloud computing professionals and published in research papers. These definitions are then analyzed under more than fifteen components, each of which is discussed in the chapter. This study is backed by empirical work, to understand Cloud computing from different angles and come up with a comprehensive definition. It also analyses the present Cloud service providers and the level of services they provide to bring about a clear picture of Cloud computing. Based on the comparison, the pending issues in Cloud computing are discussed.

Survivable Mapping of Virtual Networks onto a Shared Substrate Network

The virtualization of both servers and substrate networks will enable the future Internet architecture to support a variety of Cloud computing services and architectures, and prevent its ossification. Since multiple virtual networks (VN) or virtual infrastructure (VI) and services now share the resources of the same underlying network in a network virtualization environment, it is important that efficient techniques are developed for the mapping of the VNs onto the substrate network. Furthermore, due to the sharing of resources, the survivable design of VNs is also very important, since now even small failures in the substrate network will cause the disruption of a large number of VNs that may be mapped on to the substrate network. In this work, the author studies the problem of survivable virtual network mapping (SVNM) and first formulates the problem using mixed integer linear programming (MILP). The author then devises two kinds of algorithms for solving the SVNM problem efficiently: (1) Lagrangian relaxation-based algorithms including LR-SVNM-M and LR-SVNM-D and (2) Heuristic algorithms including H-SVNM-D and H-SVNM-M. The author then compares the performance of the algorithms with other VI mapping algorithms under various performance metrics using simulation. The simulation results and analysis show that the algorithms can be used to balance the tradeoff between time efficiency and mapping cost.

CloudRank

In this chapter, the authors propose a Cloud service ranking system, named CloudRank, based on both the user feedback and service testing. In CloudRank, we design a new ranking-oriented collaborative filtering (CF) approach named WSRank, in which user preferences are modeled as personal rankings derived from user QoS ratings on services to address service quality predication problem. Different from the existing similar approaches, WSRank firstly presents a QoS model which allows users to express their preferences flexibly while providing combination of multiple QoS properties to give an overall rating to a service. Secondly, it measures the similarity among users based on the correlation of their rankings of services rather than the rating values. Nevertheless, it is neither accurate nor sufficient to rank Cloud services merely based on users’ feedbacks, as there are many problems such as cold-start problem, absence of user feedback, even some service faults occurred in a service workflow, so to get an accurate ranking, an active service QoS testing and fault location approach is required together with WSRank. Therefore, in CloudRank, the authors also designed an automated testing prototype named WSTester to collect real QoS information of services. WSTester integrates distributed computers to construct a virtual testing environment for Web service testing and deploys test tasks onto distributed computers efficiently.

An Approach to Evolving Legacy Software System into Cloud Computing Environment

Cloud computing is a new paradigm for the intent of distributed resources sharing and coordinated problem solution. Affected by the Cloud trend and Service-Oriented need, many existing software systems will become legacy systems. These legacy software systems will need Cloud Oriented reengineering, which can facilitate the legacy systems reusable in Cloud Oriented architecture and allow the integration of legacy resources with Cloud features. This research focuses on establishing a general framework to assist with the evolution of legacy systems into Cloud environments. The methodology includes various phases, which use reverse engineering techniques to comprehend and decompose legacy systems, represent legacy resources by XML as Cloud component and integrate these Cloud components into Cloud environment. In this research, a legacy banking system has been chosen as a case study to prove the feasibility of the proposed approach. The legacy banking system can be transformed to run as a Service-Oriented Cloud application, which illustrates the proposed approach is powerful for utilising reusable legacy resources into Cloud environment.