396 research outputs found

    Self-management for large-scale distributed systems

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    Autonomic computing aims at making computing systems self-managing by using autonomic managers in order to reduce obstacles caused by management complexity. This thesis presents results of research on self-management for large-scale distributed systems. This research was motivated by the increasing complexity of computing systems and their management. In the first part, we present our platform, called Niche, for programming self-managing component-based distributed applications. In our work on Niche, we have faced and addressed the following four challenges in achieving self-management in a dynamic environment characterized by volatile resources and high churn: resource discovery, robust and efficient sensing and actuation, management bottleneck, and scale. We present results of our research on addressing the above challenges. Niche implements the autonomic computing architecture, proposed by IBM, in a fully decentralized way. Niche supports a network-transparent view of the system architecture simplifying the design of distributed self-management. Niche provides a concise and expressive API for self-management. The implementation of the platform relies on the scalability and robustness of structured overlay networks. We proceed by presenting a methodology for designing the management part of a distributed self-managing application. We define design steps that include partitioning of management functions and orchestration of multiple autonomic managers. In the second part, we discuss robustness of management and data consistency, which are necessary in a distributed system. Dealing with the effect of churn on management increases the complexity of the management logic and thus makes its development time consuming and error prone. We propose the abstraction of Robust Management Elements, which are able to heal themselves under continuous churn. Our approach is based on replicating a management element using finite state machine replication with a reconfigurable replica set. Our algorithm automates the reconfiguration (migration) of the replica set in order to tolerate continuous churn. For data consistency, we propose a majority-based distributed key-value store supporting multiple consistency levels that is based on a peer-to-peer network. The store enables the tradeoff between high availability and data consistency. Using majority allows avoiding potential drawbacks of a master-based consistency control, namely, a single-point of failure and a potential performance bottleneck. In the third part, we investigate self-management for Cloud-based storage systems with the focus on elasticity control using elements of control theory and machine learning. We have conducted research on a number of different designs of an elasticity controller, including a State-Space feedback controller and a controller that combines feedback and feedforward control. We describe our experience in designing an elasticity controller for a Cloud-based key-value store using state-space model that enables to trade-off performance for cost. We describe the steps in designing an elasticity controller. We continue by presenting the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores that combines feedforward and feedback control

    SoS: self-organizing substrates

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    Large-scale networked systems often, both by design or chance exhibit self-organizing properties. Understanding self-organization using tools from cybernetics, particularly modeling them as Markov processes is a first step towards a formal framework which can be used in (decentralized) systems research and design.Interesting aspects to look for include the time evolution of a system and to investigate if and when a system converges to some absorbing states or stabilizes into a dynamic (and stable) equilibrium and how it performs under such an equilibrium state. Such a formal framework brings in objectivity in systems research, helping discern facts from artefacts as well as providing tools for quantitative evaluation of such systems. This thesis introduces such formalism in analyzing and evaluating peer-to-peer (P2P) systems in order to better understand the dynamics of such systems which in turn helps in better designs. In particular this thesis develops and studies the fundamental building blocks for a P2P storage system. In the process the design and evaluation methodology we pursue illustrate the typical methodological approaches in studying and designing self-organizing systems, and how the analysis methodology influences the design of the algorithms themselves to meet system design goals (preferably with quantifiable guarantees). These goals include efficiency, availability and durability, load-balance, high fault-tolerance and self-maintenance even in adversarial conditions like arbitrarily skewed and dynamic load and high membership dynamics (churn), apart of-course the specific functionalities that the system is supposed to provide. The functionalities we study here are some of the fundamental building blocks for various P2P applications and systems including P2P storage systems, and hence we call them substrates or base infrastructure. These elemental functionalities include: (i) Reliable and efficient discovery of resources distributed over the network in a decentralized manner; (ii) Communication among participants in an address independent manner, i.e., even when peers change their physical addresses; (iii) Availability and persistence of stored objects in the network, irrespective of availability or departure of individual participants from the system at any time; and (iv) Freshness of the objects/resources' (up-to-date replicas). Internet-scale distributed index structures (often termed as structured overlays) are used for discovery and access of resources in a decentralized setting. We propose a rapid construction from scratch and maintenance of the P-Grid overlay network in a self-organized manner so as to provide efficient search of both individual keys as well as a whole range of keys, doing so providing good load-balancing characteristics for diverse kind of arbitrarily skewed loads - storage and replication, query forwarding and query answering loads. For fast overlay construction we employ recursive partitioning of the key-space so that the resulting partitions are balanced with respect to storage load and replication. The proper algorithmic parameters for such partitioning is derived from a transient analysis of the partitioning process which has Markov property. Preservation of ordering information in P-Grid such that queries other than exact queries, like range queries can be efficiently and rather trivially handled makes P-Grid suitable for data-oriented applications. Fast overlay construction is analogous to building an index on a new set of keys making P-Grid suitable as the underlying indexing mechanism for peer-to-peer information retrieval applications among other potential applications which may require frequent indexing of new attributes apart regular updates to an existing index. In order to deal with membership dynamics, in particular changing physical address of peers across sessions, the overlay itself is used as a (self-referential) directory service for maintaining the participating peers' physical addresses across sessions. Exploiting this self-referential directory, a family of overlay maintenance scheme has been designed with lower communication overhead than other overlay maintenance strategies. The notion of dynamic equilibrium study for overlays under continuous churn and repairs, modeled as a Markov process, was introduced in order to evaluate and compare the overlay maintenance schemes. While the self-referential directory was originally invented to realize overlay maintenance schemes with lower overheads than existing overlay maintenance schemes, the self-referential directory is generic in nature and can be used for various other purposes, e.g., as a decentralized public key infrastructure. Persistence of peer identity across sessions, in spite of changes in physical address, provides a logical independence of the overlay network from the underlying physical network. This has many other potential usages, for example, efficient maintenance mechanisms for P2P storage systems and P2P trust and reputation management. We specifically look into the dynamics of maintaining redundancy for storage systems and design a novel lazy maintenance strategy. This strategy is algorithmically a simple variant of existing maintenance strategies which adapts to the system dynamics. This randomized lazy maintenance strategy thus explores the cost-performance trade-offs of the storage maintenance operations in a self-organizing manner. We model the storage system (redundancy), under churn and maintenance, as a Markov process. We perform an equilibrium study to show that the system operates in a more stable dynamic equilibrium with our strategy than for the existing maintenance scheme for comparable overheads. Particularly, we show that our maintenance scheme provides substantial performance gains in terms of maintenance overhead and system's resilience in presence of churn and correlated failures. Finally, we propose a gossip mechanism which works with lower communication overhead than existing approaches for communication among a relatively large set of unreliable peers without assuming any specific structure for their mutual connectivity. We use such a communication primitive for propagating replica updates in P2P systems, facilitating management of mutable content in P2P systems. The peer population affected by a gossip can be modeled as a Markov process. Studying the transient spread of gossips help in choosing proper algorithm parameters to reduce communication overhead while guaranteeing coverage of online peers. Each of these substrates in themselves were developed to find practical solutions for real problems. Put together, these can be used in other applications, including a P2P storage system with support for efficient lookup and inserts, membership dynamics, content mutation and updates, persistence and availability. Many of the ideas have already been implemented in real systems and several others are in the way to be integrated into the implementations. There are two principal contributions of this dissertation. It provides design of the P2P systems which are useful for end-users as well as other application developers who can build upon these existing systems. Secondly, it adapts and introduces the methodology of analysis of a system's time-evolution (tools typically used in diverse domains including physics and cybernetics) to study the long run behavior of P2P systems, and uses this methodology to (re-)design appropriate algorithms and evaluate them. We observed that studying P2P systems from the perspective of complex systems reveals their inner dynamics and hence ways to exploit such dynamics for suitable or better algorithms. In other words, the analysis methodology in itself strongly influences and inspires the way we design such systems. We believe that such an approach of orchestrating self-organization in internet-scale systems, where the algorithms and the analysis methodology have strong mutual influence will significantly change the way future such systems are developed and evaluated. We envision that such an approach will particularly serve as an important tool for the nascent but fast moving P2P systems research and development community

    Smart PIN: performance and cost-oriented context-aware personal information network

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    The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches
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