57 research outputs found
INVESTIGATION ON ENERGY UTILIZATION IN CLOUD DATA CENTERS
Abstract-Cloud computing has revolutioned the ICT industry by enabling on-demand provisioning of computing resources. An organization can either outsource its computational needs to the cloud avoiding high up-front investments in a private computing infrastructure and consequent maintenance costs, or implement a private cloud data center to improve the resource management and provisioning processes. The global energy consumption of IT equipment is steadily rising and produces an increasing portion of global energy production. Currently, data centers consume about 1.5% of global electricity production, whereby their total energy usage has almost tripled between 2000 and 2010.The increasing demand of computational power, especially in current cloud computing environments, is an important reason for the rising number of running computers as well as increasing energy consumption
Patia: Adaptive distributed webserver (A position paper)
This paper introduces the Patia Adaptive Webserver architecture, which is distributed and consists of semi-autonomous agents called FLYs. The FLY carries with it the set of rules and adaptivity policies required to deliver the data to the requesting client. Where a change in the FLY’s external environment could affect performance, it is the FLY’s responsibility to change the method of delivery (or the actual object being delivered). It is our conjecture that the success of today’s multimedia websites in terms of performance lies in the architecture of the underlying servers and their ability to adapt to changes in demand and resource availability, as well as their ability to scale. We believe that the distributed and autonomous nature of this system are key factors in achieving this.
Dynamic content delivery infrastructure deployment using network cloud resources
Millionen von Menschen schätzen die Inhalte und Anwendungen, die das Internet zur Verfügung stellt. Um der steigenden Nachfrage an populären Inhalten wie z.B. High-Definition Video oder Online Social Networks nachzukommen, wurden weit verteilte Content Delivery Infrastructures (CDIs) aufgebaut. Damit CDIs im harten Wettbewerbs bestehen können, suchen sie ständig neue Möglichkeiten um laufende Kosten zu senken und Ihre Leistungsfähigkeit zu steigern. Jedoch machen den CDIs eine geringe Agilität bei der Allokation von Servern zu schaffen. Informationen zur Steigerung von Effizienz und Leistungsfähigkeit wie z.B. aktuelle Netzwerkbedingungen und präzise User-Positionen sind den CDIs unbekannt. Obwohl Internet Service Provider (ISPs) diese Informationen besitzen, lassen auch neuere CDI-Architekturen eine mögliche Kollaboration außer Acht. Diese Dissertation untersucht den Einfluss von Kollaboration auf Content Delivery. Zunächst wird das heutige Design- und Betriebsfeld untersucht. Eine Analyse der operativen Daten eines Europäischen Tier-1 ISPs erörtert mögliche Verbesserungen. Erste Ergebnisse zeigen, dass Kollaboration bei der Zuordnung von Usern zu CDI Servern den Netzwerkverkehr lokal begrenzt und die Geschwindigkeit erhöht. Vorhandene Netzwerkpfade eröffnen neue Möglichkeiten der Verkehrssteuerung. Um die Kollaboration zwischen CDIs und ISPs zu ermöglichen, beschreibt diese Arbeit die beiden Key Enabler In-Network Server Allocation und Informed User-Server Assignment. Sie stellt außerdem ein Systemdesign vor, das diese realisiert: NetPaaS (Network Platform as a Service). In-Network Server Allocation nutzt im ISP verteilte Resourcen und aktuelle Virtualisierungstechnologien um eine agile Serverallokation zu ermöglichen. Informed User-Server Assignment erlaubt es ISPs, mögliche Netzwerkengpässe und präzise User-Positionen einzukalkulieren und so CDIs den besten Server für individuelle Nutzer zu empfehlen. Damit bietet NetPaaS einen zusätzlichen Freiheitsgrad zur dynamischen Skalierung von Serverinfrastrukturen. Um das Kollaborationspotential von NetPaaS aufzuzeigen, wird erstmals eine Studie mit operativen Daten des größten kommerziellen CDI und einem Europäischen Tier-1 ISP durchgeführt. Die Ergebniss zeigen, dass eine auf präzisen User-Positionen und aktuellen Netzwerkbedingungen basierende dynamische Serverallokation es dem CDI ermöglicht, besser mit der stark schwankenden Nachfrage nach Inhalten zurecht zu kommen und die Geschwindigkeit der Nutzer zu verbessern. Darüber hinaus führt die Nutzung von NetPaaS zu einer besseren Auslastung vorhandener Serverinfrastrukturen und ermöglicht ein verbessertes Verkehrsmanagement im Netz des ISP. Diese Ergebnisse lassen den Schluss zu, dass NetPaaS die Leistungsfähigkeit und Effizienz von CDIs stark verbessert und unter Umständen laufende Kosten und Investitionen reduziert. NetPaaS verbessert weiterhin das Verkehrsmanagement des ISP und bietet somit eine echte "win-win" Situation fur CDIs und ISPs.Millions of people value the Internet for the content and the applications it makes available. To cope with the increasing end-user demand for popular and often high volume content, e.g., high-definition video or online social networks, massively distributed Content Delivery Infrastructures (CDIs) have been deployed.
However, a highly competitive market requires CDIs to constantly investigate new ways to reduce operational costs and improve delivery performance. Today, CDIs mainly suffer from limited agility in server deployment and are largely unaware of network conditions and precise end-user locations, information that improves the efficiency and performance of content delivery. While newly emerging architectures try to address these challenges, none so far considered collaboration, although ISPs have the information readily at hand.
In this thesis, we assess the impact of collaboration on content delivery. We first evaluate the design and operating space of todays content delivery landscape and quantify possible benefits of collaboration by analyzing operational traces from an European Tier-1 ISP. We find that collaboration when assigning end-users to servers highly localizes CDI traffic and improves end-user performance. Moreover, we find significant path diversity which enables new mechanisms for traffic management.
We propose two key enablers, namely in-network server allocation and informed user-server assignment, to facilitate CDI-ISP collaboration and present our system design, called NetPaaS (Network Platform as a Service), that realizes them. In- network server allocation offers agile server allocation close to the ISPs end-users leveraging virtualization technology and cloud style resources in the network. In- formed user-server assignment enables ISPs to take network bottlenecks and precise end-user locations into account and to recommend the best possible candidate server for individual end-users to CDIs. Therefore, NetPaaS provides an additional degree of freedom to scale-up or shrink the CDI footprint on demand.
To quantify the potential of collaboration with NetPaaS, we perform a first-of-its- kind evaluation based on operational traces from the largest commercial CDI and an European Tier-1 ISP. Our findings reveal that dynamic server allocation based on accurate end-user locations and network conditions enables the CDI to better cope with increasing and highly volatile demand for content and improves the end-users performance. Moreover, recommendations from NetPaaS result in better utilization of existing server infrastructure and enables the ISP to better manage traffic flows inside its network.
We conclude, that NetPaaS improves the performance and efficiency of content delivery architectures while potentially reducing the required capital investment and operational costs. Moreover, NetPaaS enables the ISP to achieve traffic engineering goals and therefore offers a true win-win situation to both CDIs and ISPs
Scalable hosting of web applications
Modern Web sites have evolved from simple monolithic systems to complex multitiered systems. In contrast to traditional Web sites, these sites do not simply deliver pre-written content but dynamically generate content using (one or more) multi-tiered Web applications. In this thesis, we addressed the question: How to host multi-tiered Web applications in a scalable manner? Scaling up a Web application requires scaling its individual tiers. To this end, various research works have proposed techniques that employ replication or caching solutions at different tiers. However, most of these techniques aim to optimize the performance of individual tiers and not the entire application. A key observation made in our research is that there exists no elixir technique that performs the best for allWeb applications. Effective hosting of a Web application requires careful selection and deployment of several techniques at different tiers. To this end, we present several caching and replication strategies, such as GlobeCBC, GlobeDB and GlobeTP, to improve the scalability of different tiers of a Web application. While these techniques and systems improve the performance of the individual tiers (and eventually the application), an application's administrator is not only interested in the performance of its individual tiers but also in its endto- end performance. To this end, we propose a resource provisioning approach that allows us to choose the best resource configuration for hosting a Web application such that its end-to-end response time can be optimized with minimum usage of resources. The proposed approach is based on an analytical model for multi-tier systems, which allows us to derive expressions for estimating the mean end-to-end response time and its variance.Steen, M.R. van [Promotor]Pierre, G.E.O. [Copromotor
Distributed Dynamic Replica Placement and Request Redirection in Content Delivery Networks
Chiara Petrioli, Giancarlo Bongiovanni, Francesco Lo Prest
Analyzing the costs/tradeoffs involved between layer 2, layer 3, layer 4 and layer 5 switching
The switching function was primarily entrusted to Layer 2 of the OSI model, i.e. the Data Link Layer. A Layer 2 switch performs forwarding decisions by analyzing the MAC (Media Access Control) address of the destination segment in the frame. The Layer 2 switch checks for the destination address and transmits the packet to the appropriate segment if the address is present in its table of known destinations. If the entry for that address is not present, the switch then forwards the packet to all segments except the one on which it came from. This is known as flooding. When it gets a reply from the destination segment, it learns the location of the new address and adds it to its table of known destinations. As number of users are increasing on the network, the speed and the bandwidth of the network is being stretched to its limits. Earlier, switching was primarily entrusted to Layer 2 (Data Link Layer) of the OSI model, but now there are switches that operate at Layer 3 (Network Layer), Layer 4 (Transport Layer) and Layer 5 (Session Layer) of the OSI model. Going from one layer to the other layer does involve some costs/tradeoffs. My thesis explores the costs and tradeoffs involved with switching based on layers 2, 3, 4 and 5 of the OSI reference model
Latency-driven replication for globally distributed systems
Steen, M.R. van [Promotor]Pierre, G.E.O. [Copromotor
A survey of online data-driven proactive 5G network optimisation using machine learning
In the fifth-generation (5G) mobile networks, proactive network optimisation plays an important role in meeting the exponential traffic growth, more stringent service requirements, and to reduce capitaland operational expenditure. Proactive network optimisation is widely acknowledged as on e of the most promising ways to transform the 5G network based on big data analysis and cloud-fog-edge computing, but there are many challenges. Proactive algorithms will require accurate forecasting of highly contextualised traffic demand and quantifying the uncertainty to drive decision making with performance guarantees. Context in Cyber-Physical-Social Systems (CPSS) is often challenging to uncover, unfolds over time, and even more difficult to quantify and integrate into decision making. The first part of the review focuses on mining and inferring CPSS context from heterogeneous data sources, such as online user-generated-content. It will examine the state-of-the-art methods currently employed to infer location, social behaviour, and traffic demand through a cloud-edge computing framework; combining them to form the input to proactive algorithms. The second part of the review focuses on exploiting and integrating the demand knowledge for a range of proactive optimisation techniques, including the key aspects of load balancing, mobile edge caching, and interference management. In both parts, appropriate state-of-the-art machine learning techniques (including probabilistic uncertainty cascades in proactive optimisation), complexity-performance trade-offs, and demonstrative examples are presented to inspire readers. This survey couples the potential of online big data analytics, cloud-edge computing, statistical machine learning, and proactive network optimisation in a common cross-layer wireless framework. The wider impact of this survey includes better cross-fertilising the academic fields of data analytics, mobile edge computing, AI, CPSS, and wireless communications, as well as informing the industry of the promising potentials in this area
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Content Placement as a Key to a Content-Dominated, Highly mobile Internet
Most of the Internet traffic is content, and most of the Internet connected hosts are mobile. Our work focuses on the design of infrastructure services needed to support such a content-dominated, highly mobile Internet. In the design of these services, three sets of decisions arise frequently: (1) Content placment for selecting the locations where a content is placed, (2) request redirection for selecting the location where a particular request is served from and (3) network routing for selecting the physical path between clients and the services they are accessing. Our central thesis is that content placement is a powerful factor, and is often more powerful than redirection and routing, in determining the cost, performance and energy-related metrics for these services. In support of this thesis, we consider three types of infrastructure.
Internet service provider (ISP): In an ISP carrying content-dominated traffic, we show that combinations of simple placement and routing schemes are effective in optimizing an ISP\u27s performance and cost objectives. Further, we show that effective content placement contributes more than optimizing network routing to achieve an ISP\u27s objectives. Our findings question the value of traditional ISP traffic engineering schemes that optimize routing alone, while simplifying the task of traffic engineering for the operators.
Global name service (GNS): We design and implement a GNS, \auspice, that resolves names to network addresses for highly mobile entities, thereby providing a key building block for establishing communication between mobile entities in the Internet. A key distinction between \auspice\ and other name services is a {\em demand-aware} replica {placement engine} that intelligently replicates name records to provide low lookup latency, low update cost, and high availability. In our experiments, Auspice\u27s placement scheme enables it to significantly outperform commercial managed DNS providers, DHT-based replication as well as static placement schemes that use the same redirection scheme as Auspice.
Content datacenter (CDC): Content datacenters cache and serve content to improve user-perceived performance for content accesses. In a CDC, we quantify the tradeoff between energy savings via consolidation and the user-perceived performance impact based on a real CDC workload. A key insight, supported via experiments, is that despite server consolidation, a simple caching scheme is able to achieve cache hit rates close to an unconsolidated datacenter, which helps mitigate the impact of consolidation on user-perceived latencies. Further, our work is the first to propose a network-aware server consolidation approach that enables additional network energy savings over network-unaware server consolidation schemes for common datacenter topologies
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