Application of Cloud-based Virtual Reality Integrated Automatic Presentation Script for Understanding Urban Design Concepts

13301甲第4483号博士（学術）金沢大学博士論文本文Full 以下に掲載：International Review for Spatial Planning and Sustainable Development 3(2) pp.53-67 2015. International Community of Spatial Planning and Sustainable Development. 共著者：Yuanyi Zhang, Zhang Ying, Zhenjiang Shen, Tatsuya Nishino, Xiaojuan Che

A Composition-Based View of Organizational Ingenuity: Empirical Evidence from SMEs in India

This thesis explores a relatively new concept of organizational ingenuity (OI) through the composition-based view (CBV) theory lens with SMEs in India. The unique conditions of emerging economy context of India are delineated to be factors that compel SMEs to develop ingenuity. Three conceptual properties of OI -strategy, capabilities, and process are validated as the components that support SMEs thrive despite challenging emerging economy conditions. Findings of this thesis are presented in a theoretical framework

Optimization and Management Techniques for Geo-distributed SDN-enabled Cloud Datacenters\u27 Provisioning

Cloud computing has become a business reality that impacts technology users around the world. It has become a cornerstone for emerging technologies and an enabler of future Internet services as it provides on-demand IT services delivery via geographically distributed data centers. At the core of cloud computing, virtualization technology has played a crucial role by allowing resource sharing, which in turn allows cloud service providers to offer computing services without discrepancies in platform compatibility. At the same time, a trend has emerged in which enterprises are adopting a software-based network infrastructure with paradigms, such as software-defined networking, gaining further attention for large-scale networks. This trend is due to the flexibility and agility offered to networks by such paradigms. Software-defined networks allow for network resource sharing by facilitating network virtualization. Hence, combining cloud computing with a software-defined network architecture promises to enhance the quality of services that are delivered to clients and reduces the operational costs to service providers. However, this combined architecture introduces several challenges to cloud service providers, including resource management, energy efficiency, virtual network provisioning, and controller placement. This thesis tackles these challenges by proposing innovative resource provisioning techniques and developing novel frameworks to improve resource utilization, power efficiency, and quality of service performance. These metrics have a direct impact on the capital and operational expenditure of service providers. In this thesis, the problem of virtual computing and network provisioning in geographically distributed software-defined network-enabled cloud data centers is modeled and formulated. It proposes and evaluates optimal and sub-optimal heuristic solutions to validate their efficiency. To address the energy efficiency of cloud environments that are enabled for software-defined networks, this thesis presents an innovative architecture and develops a comprehensive power consumption model that accurately describes the power consumption behavior of such environments. To address the challenge of the number of software-defined network controllers and locations, a sub-optimal solution is proposed that combines unsupervised hierarchical clustering. Finally, betweenness centrality is proposed as an efficient solution to the controller placement problem

Adaptive monitoring and control framework in Application Service Management environment

The economics of data centres and cloud computing services have pushed hardware and software requirements to the limits, leaving only very small performance overhead before systems get into saturation. For Application Service Management–ASM, this carries the growing risk of impacting the execution times of various processes. In order to deliver a stable service at times of great demand for computational power, enterprise data centres and cloud providers must implement fast and robust control mechanisms that are capable of adapting to changing operating conditions while satisfying service–level agreements. In ASM practice, there are normally two methods for dealing with increased load, namely increasing computational power or releasing load. The first approach typically involves allocating additional machines, which must be available, waiting idle, to deal with high demand situations. The second approach is implemented by terminating incoming actions that are less important to new activity demand patterns, throttling, or rescheduling jobs. Although most modern cloud platforms, or operating systems, do not allow adaptive/automatic termination of processes, tasks or actions, it is administrators’ common practice to manually end, or stop, tasks or actions at any level of the system, such as at the level of a node, function, or process, or kill a long session that is executing on a database server. In this context, adaptive control of actions termination remains a significantly underutilised subject of Application Service Management and deserves further consideration. For example, this approach may be eminently suitable for systems with harsh execution time Service Level Agreements, such as real–time systems, or systems running under conditions of hard pressure on power supplies, systems running under variable priority, or constraints set up by the green computing paradigm. Along this line of work, the thesis investigates the potential of dimension relevance and metrics signals decomposition as methods that would enable more efficient action termination. These methods are integrated in adaptive control emulators and actuators powered by neural networks that are used to adjust the operation of the system to better conditions in environments with established goals seen from both system performance and economics perspectives. The behaviour of the proposed control framework is evaluated using complex load and service agreements scenarios of systems compatible with the requirements of on–premises, elastic compute cloud deployments, server–less computing, and micro–services architectures