Orchestrating Bulk Data Movement in Grid Environments

Data Grids provide a convenient environment for researchers to manage and access massively distributed bulk data by addressing several system and transfer challenges inherent to these environments. This work addresses issues involved in the efficient selection and access of replicated data in Grid environments in the context of the Globus Toolkit{trademark}, building middleware that (1) selects datasets in highly replicated environments, enabling efficient scheduling of data transfer requests; (2) predicts transfer times of bulk wide-area data transfers using extensive statistical analysis; and (3) co-allocates bulk data transfer requests, enabling parallel downloads from mirrored sites. These efforts have demonstrated a decentralized data scheduling architecture, a set of forecasting tools that predict bandwidth availability within 15% error and co-allocation architecture, and heuristics that expedites data downloads by up to 2 times

Replication for Web Hosting Systems

Replication is a well-known technique to improve the accessibility of Web sites. It generally offers reduced client latencies and increases a site’s availability. However, applying replication techniques is not trivial, and various Content Delivery Networks (CDNs) have been created to facilitate replication for digital content providers. Th

Digital Currencies and 5G

Στη παρούσα διπλωματική εργασία με τίτλο “Digital Currencies and 5G” μελετάται η τεχνολογία blockchain, ο τρόπος με τον οποίο γίνεται η τιμολόγηση της υπηρεσίας που εξαρτάται από τον τύπο, το πλήθος, το είδος της υπηρεσίας που επιθυμεί ο εκάστοτε χρήστης αλλά και πως επηρεάζεται το QoE από την υφιστάμενη πολιτική τιμολόγησης.In this work entitled "Digital Currencies and 5G" the blockchain technology is studied, the way in which the service is priced depending on the type, number, type of service desired by each user and how the QoE from the existing pricing policy

Scalable approaches for DiffServ multicasting

Over the last several years, there has been an explosion in the introduction of new Internet technologies. Whereas the Internet in its original form was a medium primarily for academia and research interests, the Internet has been redefined as business and consumer interests have dominated the focal points of Internet technology. The dominant question facing the Internet today is, how can the network meet the needs of the users and their applications while trying to keep such implementations scalable to the billions of users present on the Internet? Two of the emerging technologies for answering the question are Differentiated Services (DiffServ) and multicasting. Although the two technologies share complementary goals, the integration of the two technologies is a non-trivial issue due to three fundamental conflicts. The three fundamental conflicts are the scalability of per-group state information, sender versus receiver-driven QoS, and resource management. The issues surrounding how to solve these conflicts provide the basis for this dissertation.;In this dissertation, two architectures (DiffServ Multicasting (DSMCast) and Edge-Based Multicasting (EBM)) are proposed to satisfy the requirements for scalable DiffServ multicasting architectures. In addition to the two architectures, this dissertation also presents the first in-depth study regarding single tree support for heterogeneous QoS multicasting. Furthermore, the dissertation proposes a novel application of DSMCast for fault tolerance and management of the DiffServ network. Finally, the dissertation comments on future applications of the architectures and proposes several areas for future research

Scalable download protocols

Scalable on-demand content delivery systems, designed to effectively handle increasing request rates, typically use service aggregation or content replication techniques. Service aggregation relies on one-to-many communication techniques, such as multicast, to efficiently deliver content from a single sender to multiple receivers. With replication, multiple geographically distributed replicas of the service or content share the load of processing client requests and enable delivery from a nearby server.Previous scalable protocols for downloading large, popular files from a single server include batching and cyclic multicast. Analytic lower bounds developed in this thesis show that neither of these protocols consistently yields performance close to optimal. New hybrid protocols are proposed that achieve within 20% of the optimal delay in homogeneous systems, as well as within 25% of the optimal maximum client delay in all heterogeneous scenarios considered.In systems utilizing both service aggregation and replication, well-designed policies determining which replica serves each request must balance the objectives of achieving high locality of service, and high efficiency of service aggregation. By comparing classes of policies, using both analysis and simulations, this thesis shows that there are significant performance advantages in using current system state information (rather than only proximities and average loads) and in deferring selection decisions when possible. Most of these performance gains can be achieved using only “local” (rather than global) request information.Finally, this thesis proposes adaptations of already proposed peer-assisted download techniques to support a streaming (rather than download) service, enabling playback to begin well before the entire media file is received. These protocols split each file into pieces, which can be downloaded from multiple sources, including other clients downloading the same file. Using simulations, a candidate protocol is presented and evaluated. The protocol includes both a piece selection technique that effectively mediates the conflict between achieving high piece diversity and the in-order requirements of media file playback, as well as a simple on-line rule for deciding when playback can safely commence

Latency-driven replication for globally distributed systems

Steen, M.R. van [Promotor]Pierre, G.E.O. [Copromotor