A Hybrid Web Caching Design Model for Internet-Content Delivery

The need for online contents (or resources) to be shared and distributed in a large and sophisticated networks of users, geographical dispersed location of servers and their clients, time taken to fulfil clients requests pose major challenge. Therefore the choice of suitable architecture forInternet-based content delivery (ICD) technologies readily comes to mind. To achieve this, Akamai and Gnutella Web technologies are extensively reviewed to identify their strengths and weakness because of their popularity across the world for delivering contents. This new design for Internet-based content distribution is called AkaGnu because of the extra layer (Gnutella network)inserted into Akamai architecture, which provides greater Internet edge over each technology deployed independently. The paper presents a new ICD technology that performs better than Akamai system as a result of new features and behaviours introduced that reduce network traffic, more clients Internet connectivity, increase file sharing, improved speed of contents deliveries, andenhanced network security.Keywords/Index Terms- ICD, Akamai, Gnutella, peer-to-peer, AkaGnu, network traffic, security, architecture, technolog

Development of a system compliant with the Application-Layer Traffic Optimization Protocol

Dissertação de mestrado integrado em Engenharia InformáticaWith the ever-increasing Internet usage that is following the start of the new decade, the need to optimize this world-scale network of computers becomes a big priority in the technological sphere that has the number of users rising, as are the Quality of Service (QoS) demands by applications in domains such as media streaming or virtual reality. In the face of rising traffic and stricter application demands, a better understand ing of how Internet Service Providers (ISPs) should manage their assets is needed. An important concern regards to how applications utilize the underlying network infras tructure over which they reside. Most of these applications act with little regard for ISP preferences, as exemplified by their lack of care in achieving traffic locality during their operation, which would be a preferable feature for network administrators, and that could also improve application performance. However, even a best-effort attempt by applications to cooperate will hardly succeed if ISP policies aren’t clearly commu nicated to them. Therefore, a system to bridge layer interests has much potential in helping achieve a mutually beneficial scenario. The main focus of this thesis is the Application-Layer Traffic Optimization (ALTO) work ing group, which was formed by the Internet Engineering Task Force (IETF) to explore standardizations for network information retrieval. This group specified a request response protocol where authoritative entities provide resources containing network status information and administrative preferences. Sharing of infrastructural insight is done with the intent of enabling a cooperative environment, between the network overlay and underlay, during application operations, to obtain better infrastructural re sourcefulness and the consequential minimization of the associated operational costs. This work gives an overview of the historical network tussle between applications and service providers, presents the ALTO working group’s project as a solution, im plements an extended system built upon their ideas, and finally verifies the developed system’s efficiency, in a simulation, when compared to classical alternatives.Com o acrescido uso da Internet que acompanha o início da nova década, a necessidade de otimizar esta rede global de computadores passa a ser uma grande prioridade na esfera tecnológica que vê o seu número de utilizadores a aumentar, assim como a exigência, por parte das aplicações, de novos padrões de Qualidade de Serviço (QoS), como visto em domínios de transmissão de conteúdo multimédia em tempo real e em experiências de realidade virtual. Face ao aumento de tráfego e aos padrões de exigência aplicacional mais restritos, é necessário melhor compreender como os fornecedores de serviços Internet (ISPs) devem gerir os seus recursos. Um ponto fulcral é como aplicações utilizam os seus recursos da rede, onde muitas destas não têm consideração pelas preferências dos ISPs, como exemplificado pela sua falta de esforço em localizar tráfego, onde o contrário seria preferível por administradores de rede e teria potencial para melhorar o desempenho aplicacional. Uma tentativa de melhor esforço, por parte das aplicações, em resolver este problema, não será bem-sucedida se as preferências administrativas não forem claramente comunicadas. Portanto, um sistema que sirva de ponte de comunicação entre camadas pode potenciar um cenário mutuamente benéfico. O foco principal desta tese é o grupo de trabalho Application-Layer Traffic Optimization (ALTO), que foi formado pelo Internet Engineering Task Force (IETF) para explorar estandardizações para recolha de informação da rede. Este grupo especificou um protocolo onde entidades autoritárias disponibilizam recursos com informação de estado de rede, e preferências administrativas. A partilha de conhecimento infraestrutural é feita para possibilitar um ambiente cooperativo entre redes overlay e underlay, para uma mais eficiente utilização de recursos e a consequente minimização de custos operacionais. É pretendido dar uma visão da histórica disputa entre aplicações e ISPs, assim como apresentar o projeto do grupo de trabalho ALTO como solução, implementar e melhorar sobre as suas ideias, e finalmente verificar a eficiência do sistema numa simulação, quando comparado com alternativas clássicas

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

Reducing the Download Time in Stochastic P2P Content Delivery Networks by Improving Peer Selection

Peer-to-peer (P2P) applications have become a popular method for obtaining digital content. Recent research has shown that the amount of time spent downloading from a poor performing peer effects the total download duration. Current peer selection strategies attempt to limit the amount of time spent downloading from a poor performing peer, but they do not use both advanced knowledge and service capacity after the connection has been made to aid in peer selection. Advanced knowledge has traditionally been obtained from methods that add additional overhead to the P2P network, such as polling peers for service capacity information, using round trip time techniques to calculate the distance between peers, and by using tracker peers. This work investigated the creation of a new download strategy that replaced the random selection of peers with a method that selects server peers based on historic service capacity and ISP in order to further reduce the amount of time needed to complete a download session. Peer-to-peer (P2P) applications have become a popular method for obtaining digital content. Recent research has shown that the amount of time spent downloading from a poor performing peer effects the total download duration. Current peer selection strategies attempt to limit the amount of time spent downloading from a poor performing peer, but they do not use both advanced knowledge and service capacity after the connection has been made to aid in peer selection. Advanced knowledge has traditionally been obtained from methods that add additional overhead to the P2P network, such as polling peers for service capacity information, using round trip time techniques to calculate the distance between peers, and by using tracker peers. This work investigated the creation of a new download strategy that replaced the random selection of peers with a method that selects server peers based on historic service capacity and ISP in order to further reduce the amount of time needed to complete a download session. The results of this new historic based peer selection strategy have shown that there are benefits in using advanced knowledge to select peers and only replacing the worst performing peers. This new approach showed an average download duration improvement of 16.6% in the single client simulation and an average cross ISP traffic reduction of 55.17% when ISPs were participating in cross ISP throttling. In the multiple clients simulation the new approach showed an average download duration improvement of 53.31% and an average cross ISP traffic reduction of 88.83% when ISPs were participating in cross ISP throttling. This new approach also significantly improved the consistency of the download duration between download sessions allowing for the more accurate prediction of download times

Exploring the Memory-Bandwidth Tradeoff in an Information-Centric Network

An information-centric network should realize significant economies by exploiting a favourable memory-bandwidth tradeoff: it is cheaper to store copies of popular content close to users than to fetch them repeatedly over the Internet. We evaluate this tradeoff for some simple cache network structures under realistic assumptions concerning the size of the content catalogue and its popularity distribution. Derived cost formulas reveal the relative impact of various cost, traffic and capacity parameters, allowing an appraisal of possible future network architectures. Our results suggest it probably makes more sense to envisage the future Internet as a loosely interconnected set of local data centers than a network like today's with routers augmented by limited capacity content stores.Comment: Proceedings of ITC 25 (International Teletraffic Congress), Shanghai, September, 201

AngelCast: cloud-based peer-assisted live streaming using optimized multi-tree construction

Increasingly, commercial content providers (CPs) offer streaming solutions using peer-to-peer (P2P) architectures, which promises significant scalabil- ity by leveraging clients’ upstream capacity. A major limitation of P2P live streaming is that playout rates are constrained by clients’ upstream capac- ities – typically much lower than downstream capacities – which limit the quality of the delivered stream. To leverage P2P architectures without sacri- ficing quality, CPs must commit additional resources to complement clients’ resources. In this work, we propose a cloud-based service AngelCast that enables CPs to complement P2P streaming. By subscribing to AngelCast, a CP is able to deploy extra resources (angel), on-demand from the cloud, to maintain a desirable stream quality. Angels do not download the whole stream, nor are they in possession of it. Rather, angels only relay the minimal fraction of the stream necessary to achieve the desired quality. We provide a lower bound on the minimum angel capacity needed to maintain a desired client bit-rate, and develop a fluid model construction to achieve it. Realizing the limitations of the fluid model construction, we design a practical multi- tree construction that captures the spirit of the optimal construction, and avoids its limitations. We present a prototype implementation of AngelCast, along with experimental results confirming the feasibility of our service.Supported in part by NSF awards #0720604, #0735974, #0820138, #0952145, #1012798 #1012798 #1430145 #1414119. (0720604 - NSF; 0735974 - NSF; 0820138 - NSF; 0952145 - NSF; 1012798 - NSF; 1430145 - NSF; 1414119 - NSF

An Efficient Holistic Data Distribution and Storage Solution for Online Social Networks

In the past few years, Online Social Networks (OSNs) have dramatically spread over the world. Facebook [4], one of the largest worldwide OSNs, has 1.35 billion users, 82.2% of whom are outside the US [36]. The browsing and posting interactions (text content) between OSN users lead to user data reads (visits) and writes (updates) in OSN datacenters, and Facebook now serves a billion reads and tens of millions of writes per second [37]. Besides that, Facebook has become one of the top Internet traffic sources [36] by sharing tremendous number of large multimedia files including photos and videos. The servers in datacenters have limited resources (e.g. bandwidth) to supply latency efficient service for multimedia file sharing among the rapid growing users worldwide. Most online applications operate under soft real-time constraints (e.g., ≤ 300 ms latency) for good user experience, and its service latency is negatively proportional to its income. Thus, the service latency is a very important requirement for Quality of Service (QoS) to the OSN as a web service, since it is relevant to the OSN’s revenue and user experience. Also, to increase OSN revenue, OSN service providers need to constrain capital investment, operation costs, and the resource (bandwidth) usage costs. Therefore, it is critical for the OSN to supply a guaranteed QoS for both text and multimedia contents to users while minimizing its costs. To achieve this goal, in this dissertation, we address three problems. i) Data distribution among datacenters: how to allocate data (text contents) among data servers with low service latency and minimized inter-datacenter network load; ii) Efficient multimedia file sharing: how to facilitate the servers in datacenters to efficiently share multimedia files among users; iii) Cost minimized data allocation among cloud storages: how to save the infrastructure (datacenters) capital investment and operation costs by leveraging commercial cloud storage services. Data distribution among datacenters. To serve the text content, the new OSN model, which deploys datacenters globally, helps reduce service latency to worldwide distributed users and release the load of the existing datacenters. However, it causes higher inter-datacenter communica-tion load. In the OSN, each datacenter has a full copy of all data, and the master datacenter updates all other datacenters, generating tremendous load in this new model. The distributed data storage, which only stores a user’s data to his/her geographically closest datacenters, simply mitigates the problem. However, frequent interactions between distant users lead to frequent inter-datacenter com-munication and hence long service latencies. Therefore, the OSNs need a data allocation algorithm among datacenters with minimized network load and low service latency. Efficient multimedia file sharing. To serve multimedia file sharing with rapid growing user population, the file distribution method should be scalable and cost efficient, e.g. minimiza-tion of bandwidth usage of the centralized servers. The P2P networks have been widely used for file sharing among a large amount of users [58, 131], and meet both scalable and cost efficient re-quirements. However, without fully utilizing the altruism and trust among friends in the OSNs, current P2P assisted file sharing systems depend on strangers or anonymous users to distribute files that degrades their performance due to user selfish and malicious behaviors. Therefore, the OSNs need a cost efficient and trustworthy P2P-assisted file sharing system to serve multimedia content distribution. Cost minimized data allocation among cloud storages. The new trend of OSNs needs to build worldwide datacenters, which introduce a large amount of capital investment and maintenance costs. In order to save the capital expenditures to build and maintain the hardware infrastructures, the OSNs can leverage the storage services from multiple Cloud Service Providers (CSPs) with existing worldwide distributed datacenters [30, 125, 126]. These datacenters provide different Get/Put latencies and unit prices for resource utilization and reservation. Thus, when se-lecting different CSPs’ datacenters, an OSN as a cloud customer of a globally distributed application faces two challenges: i) how to allocate data to worldwide datacenters to satisfy application SLA (service level agreement) requirements including both data retrieval latency and availability, and ii) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. Therefore, the OSNs need a data allocation system distributing data among CSPs’ datacenters with cost minimization and SLA guarantee. In all, the OSN needs an efficient holistic data distribution and storage solution to minimize its network load and cost to supply a guaranteed QoS for both text and multimedia contents. In this dissertation, we propose methods to solve each of the aforementioned challenges in OSNs. Firstly, we verify the benefits of the new trend of OSNs and present OSN typical properties that lay the basis of our design. We then propose Selective Data replication mechanism in Distributed Datacenters (SD3) to allocate user data among geographical distributed datacenters. In SD3,a datacenter jointly considers update rate and visit rate to select user data for replication, and further atomizes a user’s different types of data (e.g., status update, friend post) for replication, making sure that a replica always reduces inter-datacenter communication. Secondly, we analyze a BitTorrent file sharing trace, which proves the necessity of proximity-and interest-aware clustering. Based on the trace study and OSN properties, to address the second problem, we propose a SoCial Network integrated P2P file sharing system for enhanced Efficiency and Trustworthiness (SOCNET) to fully and cooperatively leverage the common-interest, geographically-close and trust properties of OSN friends. SOCNET uses a hierarchical distributed hash table (DHT) to cluster common-interest nodes, and then further clusters geographically close nodes into a subcluster, and connects the nodes in a subcluster with social links. Thus, when queries travel along trustable social links, they also gain higher probability of being successfully resolved by proximity-close nodes, simultaneously enhancing efficiency and trustworthiness. Thirdly, to handle the third problem, we model the cost minimization problem under the SLA constraints using integer programming. According to the system model, we propose an Eco-nomical and SLA-guaranteed cloud Storage Service (ES3), which finds a data allocation and resource reservation schedule with cost minimization and SLA guarantee. ES3 incorporates (1) a data al-location and reservation algorithm, which allocates each data item to a datacenter and determines the reservation amount on datacenters by leveraging all the pricing policies; (2) a genetic algorithm based data allocation adjustment approach, which makes data Get/Put rates stable in each data-center to maximize the reservation benefit; and (3) a dynamic request redirection algorithm, which dynamically redirects a data request from an over-utilized datacenter to an under-utilized datacenter with sufficient reserved resource when the request rate varies greatly to further reduce the payment. Finally, we conducted trace driven experiments on a distributed testbed, PlanetLab, and real commercial cloud storage (Amazon S3, Windows Azure Storage and Google Cloud Storage) to demonstrate the efficiency and effectiveness of our proposed systems in comparison with other systems. The results show that our systems outperform others in the network savings and data distribution efficiency