Decentralized Resource Scheduling in Grid/Cloud Computing

In the Grid/Cloud environment, applications or services and resources belong to different organizations with different objectives. Entities in the Grid/Cloud are autonomous and self-interested; however, they are willing to share their resources and services to achieve their individual and collective goals. In such open environment, the scheduling decision is a challenge given the decentralized nature of the environment. Each entity has specific requirements and objectives that need to achieve. In this thesis, we review the Grid/Cloud computing technologies, environment characteristics and structure and indicate the challenges within the resource scheduling. We capture the Grid/Cloud scheduling model based on the complete requirement of the environment. We further create a mapping between the Grid/Cloud scheduling problem and the combinatorial allocation problem and propose an adequate economic-based optimization model based on the characteristic and the structure nature of the Grid/Cloud. By adequacy, we mean that a comprehensive view of required properties of the Grid/Cloud is captured. We utilize the captured properties and propose a bidding language that is expressive where entities have the ability to specify any set of preferences in the Grid/Cloud and simple as entities have the ability to express structured preferences directly. We propose a winner determination model and mechanism that utilizes the proposed bidding language and finds a scheduling solution. Our proposed approach integrates concepts and principles of mechanism design and classical scheduling theory. Furthermore, we argue that in such open environment privacy concerns by nature is part of the requirement in the Grid/Cloud. Hence, any scheduling decision within the Grid/Cloud computing environment is to incorporate the feasibility of privacy protection of an entity. Each entity has specific requirements in terms of scheduling and privacy preferences. We analyze the privacy problem in the Grid/Cloud computing environment and propose an economic based model and solution architecture that provides a scheduling solution given privacy concerns in the Grid/Cloud. Finally, as a demonstration of the applicability of the approach, we apply our solution by integrating with Globus toolkit (a well adopted tool to enable Grid/Cloud computing environment). We also, created simulation experimental results to capture the economic and time efficiency of the proposed solution

Client-side resource management on the cloud: survey and future directions

Cloud computing and how to bridge the gap between various providers is getting increasing attention. In this context, efficiently scheduling tasks on heterogeneous resources is of extreme importance. The state-of-the-art for this field has been continuously growing during the last years and has reached a point in which a comprehensive overview indicating current solutions and ongoing challenges is of extreme importance for researchers. This paper aims to offer this analysis from a client-side scheduling perspective in which emphasis is not put on physical resource selection but on task to virtual machine mappings and virtual machine allocation. It provides a taxonomy for the current state-of-the-art and a unified model concerning the various metrics and goals used throughout literature. This model is designed to be sufficiently generic, extensible, and comprehensive to support most of the future work in the field. Several promising research directions and existing challenges are described

SLA Violation Detection Model and SLA Assured Service Brokering (SLaB) in Multi-Cloud Architecture

Cloud brokering facilitates CSUs to find cloud services according to their requirements. In the current practice, CSUs or Cloud Service Brokers (CSBs) select cloud services according to SLA committed by CSPs in their website. In our observation, it is found that most of the CSPs do not fulfill the service commitment mentioned in the SLA agreement. Verified cloud service performances against their SLA commitment of CSPs provide an additional trust on CSBs to recommend services to the CSUs. In this thesis work, we propose a SLA assured service-brokering framework, which considers both committed and delivered SLA by CSPs in cloud service recommendation to the users. For the evaluation of the performance of CSPs, two evaluation techniques: Heat Map and IFL are proposed, which include both directly measurable and non-measurable parameters in the performance evaluation CSPs. These two techniques are implemented using real data measured from CSPs. The result shows that Heat Map technique is more transparent and consistent in CSP performance evaluation than IFL technique. In this work, regulatory compliance of the CSPs is also analyzed and visualized in performance heat map table to provide legal status of CSPs. Moreover, missing points in their terms of service and SLA document are analyzed and recommended to add in the contract document. In the revised European GPDR, DPIA is going to be mandatory for all organizations/tools. The decision recommendation tool developed using above mentioned evaluation techniques may cause potential harm to individuals in assessing data from multiple CSPs. So, DPIA is carried out to assess the potential harm/risks to individuals due to our tool and necessary precaution to be taken in the tool to minimize possible data privacy risks. It also analyzes the service pattern and future performance behavior of CSPs to help CSUs in decision making to select appropriate CSP