A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Implementation and Evaluation of Mobile-Edge Computing Cooperative Caching

Recent expanding rise of mobile device users for cloud services leads to resource challenges in Mobile Network Operator's (MNO) network. This poses significant additional costs to MNOs and also results in poor user experience. Studies illustrate that large amount of traffic consumption in MNO's network is originated from the similar requests of users for the same popular contents over Internet. Therefore such networks suffer from delivering the same content multiple times through their connected gateways to the Internet backhaul. On the other hand, in content delivery networks (CDN), the delay caused by network latency is one of the biggest issues which impedes the efficient delivery and desirable user experience. Cooperative caching is one of the ways to handle the extra posed traffic by requesting popular contents repeatedly in MNO's network. Furthermore Mobile-Edge Computing (MEC) offers a resource rich environment and data locality to cloud applications. This helps to reduce the network latency time in CDN services. Thus in this Thesis an aggregation between Cooperative Caching and MEC concept has been considered. This Thesis demonstrates a design, implementation and evaluation for a Mobile-Edge computing Cooperative Caching system to deliver content to mobile users. A design is presented in a failure resilient and scalable practice using a light-weight synchronizing method. The system is implemented and deployed on Nokia Networks Radio Application Cloud Servers(Nokia Networks RACS) as intelligent MEC base-stations and finally the outcome of the system and the effect on bandwidth saving, CDN delay and user experience are evaluated

Ontwerp en evaluatie van content distributie netwerken voor multimediale streaming diensten.

Traditionele Internetgebaseerde diensten voor het verspreiden van bestanden, zoals Web browsen en het versturen van e-mails, worden aangeboden via één centrale server. Meer recente netwerkdiensten zoals interactieve digitale televisie of video-op-aanvraag vereisen echter hoge kwaliteitsgaranties (QoS), zoals een lage en constante netwerkvertraging, en verbruiken een aanzienlijke hoeveelheid bandbreedte op het netwerk. Architecturen met één centrale server kunnen deze garanties moeilijk bieden en voldoen daarom niet meer aan de hoge eisen van de volgende generatie multimediatoepassingen. In dit onderzoek worden daarom nieuwe netwerkarchitecturen bestudeerd, die een dergelijke dienstkwaliteit kunnen ondersteunen. Zowel peer-to-peer mechanismes, zoals bij het uitwisselen van muziekbestanden tussen eindgebruikers, als servergebaseerde oplossingen, zoals gedistribueerde caches en content distributie netwerken (CDN's), komen aan bod. Afhankelijk van de bestudeerde dienst en de gebruikte netwerktechnologieën en -architectuur, worden gecentraliseerde algoritmen voor netwerkontwerp voorgesteld. Deze algoritmen optimaliseren de plaatsing van de servers of netwerkcaches en bepalen de nodige capaciteit van de servers en netwerklinks. De dynamische plaatsing van de aangeboden bestanden in de verschillende netwerkelementen wordt aangepast aan de heersende staat van het netwerk en aan de variërende aanvraagpatronen van de eindgebruikers. Serverselectie, herroutering van aanvragen en het verspreiden van de belasting over het hele netwerk komen hierbij ook aan bod

Value Creation in a QoE Environment

User behavior of multimedia services currently undergoes strong changes. This is reflected in several recent trends, e.g. the increase of rich media content consumption, preferences for more individual and personalized services and the higher sensitivity of end users for quality issues. These changes will eventually lead to strong changes in network traffic characteristics: rising congestion in peak times and less availability of bandwidth for the individual user. As a result, the quality as perceived by the end-user will decrease if network operators and service providers do not anticipate the required changes for the network. Measurable network requirements such as available video and speech quality, security and reliability are addressed by technologies that are commonly summed up in the Quality of Service (QoS) concept. However, the end-users' perception of quality is only reflected in the wider concept of Quality of Experience (QoE). This takes the measurable network requirements into account as well as customer needs, wants and preferences. For the implementation of QoE technologies several network components need to be added or changed resulting in high capital expenditures. Yet, it is not clear if these costs can be compensated with efficiency increases. Thus, new revenue streams for the network operator are necessary to incentivize investments in QoE technologies. In this paper we address four new value creation models that can serve as basis for more elaborated business models for network operators and other actors. We show how interest in QoE of the user, the content provider, the service provider and the advertiser induces new revenue streams. These models are embedded in five possible future QoE scenarios that reveal regulation, end user quality sensibility and end-to-end support as major issues for the future. --Business Models,Quality of Experience (QoE),Quality of Service (QoS),Value Creation