Preliminary specification and design documentation for software components to achieve catallaxy in computational systems

This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing

Context-aware collaborative storage and programming for mobile users

Since people generate and access most digital content from mobile devices, novel innovative mobile apps and services are possible. Most people are interested in sharing this content with communities defined by friendship, similar interests, or geography in exchange for valuable services from these innovative apps. At the same time, they want to own and control their content. Collaborative mobile computing is an ideal choice for this situation. However, due to the distributed nature of this computing environment and the limited resources on mobile devices, maintaining content availability and storage fairness as well as providing efficient programming frameworks are challenging. This dissertation explores several techniques to improve these shortcomings of collaborative mobile computing platforms. First, it proposes a medley of three techniques into one system, MobiStore, that offers content availability in mobile peer-to-peer networks: topology maintenance with robust connectivity, structural reorientation based on the current state of the network, and gossip-based hierarchical updates. Experimental results showed that MobiStore outperforms a state-of-the-art comparison system in terms of content availability and resource usage fairness. Next, the dissertation explores the usage of social relationship properties (i.e., network centrality) to improve the fairness of resource allocation for collaborative computing in peer-to-peer online social networks. The challenge is how to provide fairness in content replication for P2P-OSN, given that the peers in these networks exchange information only with one-hop neighbors. The proposed solution provides fairness by selecting the peers to replicate content based on their potential to introduce the storage skewness, which is determined from their structural properties in the network. The proposed solution, Philia, achieves higher content availability and storage fairness than several comparison systems. The dissertation concludes with a high-level distributed programming model, which efficiently uses computing resources on a cloud-assisted, collaborative mobile computing platform. This platform pairs mobile devices with virtual machines (VMs) in the cloud for increased execution performance and availability. On such a platform, two important challenges arise: first, pairing the two computing entities into a seamless computation, communication, and storage unit; and second, using the computing resources in a cost-effective way. This dissertation proposes Moitree, a distributed programming model and middleware that translates high-level programming constructs into events and provides the illusion of a single computing entity over the mobile-VM pairs. From programmers’ viewpoint, the Moitree API models user collaborations into dynamic groups formed over location, time, or social hierarchies. Experimental results from a prototype implementation show that Moitree is scalable, suitable for real-time apps, and can improve the performance of collaborating apps regarding latency and energy consumption

Application networking for pervasive content delivery

Ph.DDOCTOR OF PHILOSOPH

A Light-weight Content Distribution Scheme for Cooperative Caching in Telco-CDNs

A key technique to reduce the rapid growing of video-on-demand’s traffic is a cooperative caching strategy aggregating multiple cache storages. Many internet service providers have considered the use of cache servers on their networks as a solution to reduce the traffic. Existing schemes often periodically calculate a sub-optimal allocation of the content caches in the network. However, such approaches require a large computational overhead that cannot be amortized in a presence of frequent changes of the contents’ popularities. This paper proposes a light-weight scheme for a cooperative caching that obtains a sub-optimal distribution of the contents by focusing on their popularities. This was made possible by adding color tags to both cache servers and contents. In addition, we propose a hybrid caching strategy based on Least Frequently Used (LFU) and Least Recently Used (LRU) schemes, which efficiently manages the contents even with a frequent change in the popularity. Evaluation results showed that our light-weight scheme could considerably reduce the traffic, reaching a sub-optimal result. In addition, the performance gain is obtained with a computation overhead of just a few seconds. The evaluation results also showed that the hybrid caching strategy could follow the rapid variation of the popularity. While a single LFU strategy drops the hit ratio by 13.9%, affected by rapid popularity changes, our proposed hybrid strategy could limit the degradation to only 2.3%

Content Replication and Placement Schemes for Wireless Mesh Networks

Recently, Wireless Mesh Networks (WMNs) have attracted much of interest from both academia and industry, due to their potential to provide an alternative broadband wireless Internet connectivity. However, due to different reasons such as multi-hop forwarding and the dynamic wireless link characteristics, the performance of current WMNs is rather low when clients are soliciting Web contents. Due to the evolution of advanced mobile computing devices; it is anticipated that the demand for bandwidth-onerous popular content (especially multimedia content) in WMNs will dramatically increase in the coming future. Content replication is a popular approach for outsourcing content on behalf of the origin content provider. This area has been well explored in the context of the wired Internet, but has received comparatively less attention from the research community when it comes to WMNs. There are a number of replica placement algorithms that are specifically designed for the Internet. But they do not consider the special features of wireless networks such as insufficient bandwidth, low server capacity, contention to access the wireless medium, etc. This thesis studies the technical challenges encountered when transforming the traditional model of multi-hop WMNs from an access network into a content network. We advance the thesis that support from packet relaying mesh routers to act as replica servers for popular content such as media streaming, results in significant performance improvement. Such support from infrastructure mesh routers benefits from knowledge of the underlying network topology (i.e., information about the physical connections between network nodes is available at mesh routers). The utilization of cross-layer information from lower layers opens the door to developing efficient replication schemes that account for the specific features of WMNs (e.g., contention between the nodes to access the wireless medium and traffic interference). Moreover, this can benefit from the underutilized resources (e.g., storage and bandwidth) at mesh routers. This utilization enables those infrastructure nodes to participate in content distribution and play the role of replica servers. In this thesis, our main contribution is the design of two lightweight, distributed, and scalable object replication schemes for WMNs. The first scheme follows a hierarchical approach, while the second scheme follows a flat one. The challenge is to replicate content as close as possible to the requesting clients and thus, reduce the access latency per object, while minimizing the number of replicas. The two schemes aim to address the questions of where and how many replicas should be placed in the WMN. In our schemes, we consider the underlying topology joint with link-quality metrics to improve the quality of experience. We show using simulation tests that the schemes significantly enhance the performance of a WMN in terms of reducing the access cost, bandwidth consumption and computation/communication cost

Replica placement in peer-to-peer systems

In today’s distributed applications, replica placement is essential since moving the data in the vicinity of an application will provide many benefits. The increasing requirements of data for scientific applications and collaborative access to these data make data placement even more important. Until now, replication is one of the main mechanisms used in distributed data whereby identical copies of data are generated and stored at various distributed sites to improve data access performance and data availability. Most work considers file’s popularity as one of the important parameters taken into consideration when designing replica placement strategies. However, this thesis argues that a combination of popularity and affinity files are the most important parameters which can be used in decision making whilst improving data access performance and data availability in distributed environments. A replica placement mechanism called Affinity Replica Placement Mechanism (ARPM) is proposed focusing on popular files and affinity files. The idea of ARPM is to improve data availability and accessibility in peer-to-peer (P2P) replica placement strategy. A P2P simulator, PeerSim, was used to evaluate the performance of this dynamic replica placement strategy. The simulation results demonstrated the effectiveness of ARPM hence provided a proof that ARPM has contributed towards a new dimension of replica placement strategy that incorporates the affinity and popularity of files replicas in P2P systems

Self-management for large-scale distributed systems

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