Energy Efficient Resource Allocation for Virtual Network Services with Dynamic Workload in Cloud Data Centers

Title from PDF of title page, viewed on March 21, 2016Dissertation advisor: Baek-Young ChoiVitaIncludes bibliographical references (pages 126-143)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2016With the rapid proliferation of cloud computing, more and more network services and applications are deployed on cloud data centers. Their energy consumption and green house gas emissions have significantly increased. Some efforts have been made to control and lower energy consumption of data centers such as, proportional energy consuming hardware, dynamic provisioning, and virtualization machine techniques. However, it is still common that many servers and network resources are often underutilized, and idle servers spend a large portion of their peak power consumption. Network virtualization and resource sharing have been employed to improve energy efficiency of data centers by aggregating workload to a few physical nodes and switch the idle nodes to sleep mode. Especially, with the advent of live migration, a virtual node can be moved from one physical node to another physical node without service disrup tion. It is possible to save more energy by shrinking virtual nodes to a small set of physical nodes and turning the idle nodes to sleep mode when the service workload is low, and expanding virtual nodes to a large set of physical nodes to satisfy QoS requirements when the service workload is high. When the service provider explicates the desired virtual network including a specific topology, and a set of virtual nodes with certain resource demands, the infrastructure provider computes how the given virtual network is embedded to its operated data centers with minimum energy consumption. When the service provider only gives some description about the network service and the desired QoS requirements, the infrastructure provider has more freedom on how to allocate resources for the network service. For the first problem, we consider the evolving workload of the virtual networks or virtual applications and residual resources in data centers, and build a novel model of energy efficient virtual network embedding (EE-VNE) in order to minimize energy usage in the physical network consists of multiple data centers. In this model, both operation cost for executing network services’ task and migration cost for the live migrations of virtual nodes are counted toward the total energy consumption. In addition, rather than random generated physical network topology, we use practical assumption about physical network topology in our model. Due to the NP-hardness of the proposed model, we develop a heuristic algorithm for virtual network scheduling and mapping. In doing so, we specifically take the expected energy consumption at different times, virtual network operation and future migration costs, and a data center architecture into consideration. Our extensive evaluation results showthatouralgorithmcouldreduceenergyconsumptionupto40%andtakeuptoa57% higher number of virtual network requests over other existing virtual mapping schemes. However, through comparison with CPLEX based exact algorithm, we identify that there is still a gap between the heuristic solution and the optimal solution. Therefore, after investigation other solutions, we convert the origin EE-VNE problem to an Ant Colony Optimization (ACO) problem by building the construction model and presenting the transition probability formula. Then, ACO based algorithm has been adapted to solve the ACO-EE-VNE problem. In addition, we reduce the space complexity of ACO-EE VNE by developing a novel way to track and update the pheromone. For the second problem, we design a framework to dynamically allocate resources for a network service by employing container based virtual nodes. In the framework,each network service would have a pallet container and a set of execution containers. The pal let container requests resource based on certain strategy, creates execution containers with assigned resources and manage the life cycle of the containers; while the execution containers execute the assigned job for the network service. Formulations are presented to optimize resource usage efficiency and save energy consumption for network services with dynamic workload, and a heuristic algorithm is proposed to solve the optimization problem. Our numerical results show that container based resource allocation provide more flexible and saves more cost than virtual service deployment with fixed virtual machines and demands. In addition, we study the content distribution problem with joint optimization goal and varied size of contents in cloud storage. Previous research on content distribution mainly focuses on reducing latency experienced by content customers. A few recent studies address the issue of bandwidth usage in CDNs, as the bandwidth consumption is an important issue due to its relevance to the cost of content providers. However, few researches consider both bandwidth consumption and delay performance for the content providers that use cloud storages with limited budgets, which is the focus of this study. We develop an efficient light-weight approximation algorithm toward the joint optimization problem of content placement. We also conduct the analysis of its theoretical complexities. The performance bound of the proposed approximation algorithm exhibits a much better worst case than those in previous studies. We further extend the approximate algorithm into a distributed version that allows it to promptly react to dynamic changes in users’ interests. The extensive results from both simulations and Planetlab experiments exhibit that the performance is near optimal for most of the practical conditions.Introduction -- Related work -- Energy efficient virtual network embedding for green data centers using data center topology and future migration -- Ant colony optimization based energy efficient virtual network embedding -- Energy aware container based resource allocation for virtual services in green data centers -- Achieving optimal content delivery using cloud storage -- Conclusions and future wor

Resource Orchestration in Softwarized Networks

Network softwarization is an emerging research area that is envisioned to revolutionize the way network infrastructure is designed, operated, and managed today. Contemporary telecommunication networks are going through a major transformation, and softwarization is recognized as a crucial enabler of this transformation by both academia and industry. Softwarization promises to overcome the current ossified state of Internet network architecture and evolve towards a more open, agile, flexible, and programmable networking paradigm that will reduce both capital and operational expenditures, cut-down time-to-market of new services, and create new revenue streams. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are two complementary networking technologies that have established themselves as the cornerstones of network softwarization. SDN decouples the control and data planes to provide enhanced programmability and faster innovation of networking technologies. It facilitates simplified network control, scalability, availability, flexibility, security, cost-reduction, autonomic management, and fine-grained control of network traffic. NFV utilizes virtualization technology to reduce dependency on underlying hardware by moving packet processing activities from proprietary hardware middleboxes to virtualized entities that can run on commodity hardware. Together SDN and NFV simplify network infrastructure by utilizing standardized and commodity hardware for both compute and networking; bringing the benefits of agility, economies of scale, and flexibility of data centers to networks. Network softwarization provides the tools required to re-architect the current network infrastructure of the Internet. However, the effective application of these tools requires efficient utilization of networking resources in the softwarized environment. Innovative techniques and mechanisms are required for all aspects of network management and control. The overarching goal of this thesis is to address several key resource orchestration challenges in softwarized networks. The resource allocation and orchestration techniques presented in this thesis utilize the functionality provided by softwarization to reduce operational cost, improve resource utilization, ensure scalability, dynamically scale resource pools according to demand, and optimize energy utilization

Energy Efficient Core Networks with Clouds

The popularity of cloud based applications stemming from the high volume of connected mobile devices has led to a huge increase in Internet traffic. In order to enable easy access to cloud applications, infrastructure providers have invested in geographically distributed databases and servers. However, intelligent and energy efficient high capacity transport networks with near ubiquitous connectivity are needed to adequately and sustainably serve these requirements. In this thesis, network virtualisation has been identified as a potential networking paradigm that can contribute to network agility and energy efficiency improvements in core networks with clouds. The work first introduces a new virtual network embedding core network architecture with clouds and a compute and bandwidth resource provisioning mechanism aimed at reducing power consumption in core networks and data centres. Further, quality of service measures in compute and bandwidth resource provisioning such as delay and customer location have been investigated and their impact on energy efficiency established. Data centre location optimisation for energy efficiency in virtual network embedding infrastructure has been investigated by developing a MILP model that selects optimal data centre locations in the core network. The work also introduces an optical OFDM based physical layer in virtual network embedding to optimise power consumption and optical spectrum utilization. In addition, virtual network embedding schemes aimed at profit maximization for cloud infrastructure providers as well greenhouse gas emission reduction in cloud infrastructure networks have been investigated. GreenTouch, a consortium of industrial and academic experts on energy efficiency in ICTs, has adopted the work in this thesis as one of the measures of improving energy efficiency in core networks