Autonomic management of software defined networks : DAIM can provide the environment for building autonomy in distributed electronic environments - using OpenFlow networks as the case study

University of Technology Sydney. Faculty of Engineering and Information Technology.Next generation networks need to support a broad range of services and functionalities with capabilities such as autonomy, scalability, and adaptability for managing networks complexity. In present days, network infrastructures are becoming increasingly complex and challenging to administer due to scale and heterogeneous nature of the infrastructures. Furthermore, among various vendors, services, and platforms, managing networks require expert operators who have expertise in all different fields. This research relied on distributed active information model (DAIM) to establish a foundation which will meet future network management requirements. The DAIM is an information model for network solutions which considers challenges of autonomic functionalities, where the network devices can make local and overall network decisions by collected information. The DAIM model can facilitate networks management by introducing autonomic behaviours. The autonomic behaviours for communication networks lead networks to be self-managed and emerge as promising solutions to manage networks complexity. Autonomic networks management aims at reducing the workload on network operators from low-level tasks. Over the years, researchers have proposed a number of models for developing self-managed network solutions. One such example is the common information model (CIM), which is described as the managed environment that attempts to merge and extend the existing conventional management and also uses object-oriented constructs for overall network representation. However, the CIM has limitations coping in complex distributed electronic environments with multiple disciplines. The goal of this research is defined as development of a network architecture or a solution based on the DAIM model, which is effectively distribute and automate network’s functions to various network devices. The research first looks into the possibilities of local decision-making and programmability of network elements for distributed electronic environments with an intention to simplify network management by providing abstracted network infrastructures. After investigating and implementing different elements of the DAIM model in network forwarding devices by utilising virtual network switches, it discovers that a common high-level interface and framework for network devices are essential for the development of network solutions which will meet future network requirements. The outcome of this research is the development of (DAIM OS) specification. The DAIM OS is a network forwarding device operating system which is compliant with the DAIM model when it comes to network infrastructure management and provides a high-level abstracted application programming interface (DAIM OS API) for creating network service applications. Through the DAIM OS, network elements will be able to adapt to ever changing environments to meet the goals of service providers, vendors, and end users. Furthermore, the DAIM OS API aims to reduce complexity and time of network service applications development. If the developed DAIM OS specification is implemented and if it functions as predicted in the design analyses; that will result in a significant milestone in the development of distributed network management. This dissertation has an introduction in chapter 1 followed by five parts in order to draw a blueprint for information model as a distributed independent computing environment for autonomic network management. The five parts include lending weight to the proposition, gaining confidence in the proposition, drawing conclusions, supporting work and lastly is appendices. The introduction in chapter 1 includes motivations for the research, main challenges of the research, overall objectives, and review of research contributions. After that, to lend weight to the proposition as the first part of the dissertation, there is chapter 2 which presents the background and literature review, and chapter 3 which has a theoretical foundation for the proposed model. The foundation consists of a generic architecture for complex network management and agents to aggregate distributed network information. Moreover, chapter 3 is probably more about a state of the art in software engineering than about real implementation to engineer autonomic network management. The second part of the dissertation is to gain confidence in the proposition which includes attempting to implement the DAIM model in chapter 4 with some tests to report good performance regarding convergence and robustness for the service configuration process of network management. Also, the second part has a specification of true abstraction layers in chapter 5. The specification of true abstraction layers proposes a high-level abstraction for forwarding networking devices and provides an application program interface for network service applications developed by network operators and service providers. The implementation in chapter 4 is supported by the fourth part of the dissertation in chapter 10 which supports the theoretical foundation, designing, modelling, and developing the distributed active information model via simulation, emulation and real environments. The third part of this dissertation provides the way to draw conclusions as shown in chapter 7 which has the overall research summary, validation of the propositions, contributions and discussion, limitations and finally recommendations for future works. Finally are the appendices in Appendix A, Appendix B, Appendix C and Appendix D which provide a developing code of the core DAIM model and show different setting up for testbed environments

Autonomic care platform for optimizing query performance

Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

Dynamic Model-based Management of Service-Oriented Infrastructure.

Models are an effective tool for systems and software design. They allow software architects to abstract from the non-relevant details. Those qualities are also useful for the technical management of networks, systems and software, such as those that compose service oriented architectures. Models can provide a set of well-defined abstractions over the distributed heterogeneous service infrastructure that enable its automated management. We propose to use the managed system as a source of dynamically generated runtime models, and decompose management processes into a composition of model transformations. We have created an autonomic service deployment and configuration architecture that obtains, analyzes, and transforms system models to apply the required actions, while being oblivious to the low-level details. An instrumentation layer automatically builds these models and interprets the planned management actions to the system. We illustrate these concepts with a distributed service update operation

A peer-to-peer infrastructure for resilient web services

This work is funded by GR/M78403 “Supporting Internet Computation in Arbitrary Geographical Locations” and GR/R51872 “Reflective Application Framework for Distributed Architectures”, and by Nuffield Grant URB/01597/G “Peer-to-Peer Infrastructure for Autonomic Storage Architectures”This paper describes an infrastructure for the deployment and use of Web Services that are resilient to the failure of the nodes that host those services. The infrastructure presents a single interface that provides mechanisms for users to publish services and to find hosted services. The infrastructure supports the autonomic deployment of services and the brokerage of hosts on which services may be deployed. Once deployed, services are autonomically managed in a number of aspects including load balancing, availability, failure detection and recovery, and lifetime management. Services are published and deployed with associated metadata describing the service type. This same metadata may be used subsequently by interested parties to discover services. The infrastructure uses peer-to-peer (P2P) overlay technologies to abstract over the underlying network to deploy and locate instances of those services. It takes advantage of the P2P network to replicate directory services used to locate service instances (for using a service), Service Hosts (for deployment of services) and Autonomic Managers which manage the deployed services. The P2P overlay network is itself constructed using novel Web Services-based middleware and a variation of the Chord P2P protocol, which is self-managing.Postprin

An event service supporting autonomic management of ubiquitous systems for e-health

An event system suitable for very simple devices corresponding to a body area network for monitoring patients is presented. Event systems can be used both for self-management of the components as well as indicating alarms relating to patient health state. Traditional event systems emphasise scalability and complex event dissemination for internet based systems, whereas we are considering ubiquitous systems with wireless communication and mobile nodes which may join or leave the system over time intervals of minutes. Issues such as persistent delivery are also important. We describe the design, prototype implementation, and performance characteristics of an event system architecture targeted at this application domain

An Autonomous Engine for Services Configuration and Deployment.

The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this propos

DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling

The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimum resource utilization. The need for auto-scaling is particularly important during workload peaks, in which applications may need to scale up to extremely large-scale systems. Both the research community and the main cloud providers have already developed auto-scaling solutions. However, most research solutions are centralized and not suitable for managing large-scale systems, moreover cloud providers' solutions are bound to the limitations of a specific provider in terms of resource prices, availability, reliability, and connectivity. In this paper we propose DEPAS, a decentralized probabilistic auto-scaling algorithm integrated into a P2P architecture that is cloud provider independent, thus allowing the auto-scaling of services over multiple cloud infrastructures at the same time. Our simulations, which are based on real service traces, show that our approach is capable of: (i) keeping the overall utilization of all the instantiated cloud resources in a target range, (ii) maintaining service response times close to the ones obtained using optimal centralized auto-scaling approaches.Comment: Submitted to Springer Computin