Global internet content delivery

Microservices architecture has emerged as a transformative paradigm in modern software development, enabling organizations to build resilient and scalable distributed systems. This comprehensive exploration delves into the fundamental principles, implementation strategies, and real-world applications of microservices architecture. The architectural framework facilitates independent service deployment, enhanced fault isolation, and streamlined maintenance processes while promoting technology stack flexibility. Through the implementation of sophisticated monitoring patterns, testing strategies, and data consistency mechanisms, organizations can effectively address common challenges in distributed systems. The integration of enterprise architecture principles with microservices has demonstrated significant improvements in resource utilization, system reliability, and operational efficiency. The adoption of API gateway patterns, security frameworks, and containerization technologies further enhances system performance and scalability. Real-world applications, particularly in e-commerce platforms, showcase the practical benefits of microservices architecture in managing complex business operations while maintaining high availability and performance standards.

Cloud providers give storage access and efficient content placement and delivery services to content providers by optimizing cloud-based content delivery. The cost-efficient model should not only consider the content delivery cost but also the storage cost associated with the cloud network. In this article, a novel cloud-based content delivery model is proposed that uses shared storage models for cost optimization in content delivery. Shared storages are placed in different areas of the content delivery network and an efficient replica placement strategy is employed using optimization techniques. Different content delivery schemes are used in proposed model for different situations and overall content delivery cost is optimized. Experimental results show better performance and lesser cost in terms of storage, traffic and latency and also satisfy Quality-of-Service (QoS) and Quality-of-Experience (QoE) in content delivery using PSO when compared to ACO and GA.

It is a well known fact that managed care and new treatment technologies are revolutionizing the health care provider world. Community Health Information Network and Computer-based Patient Record projects are underway throughout the United States. More and more hospitals are installing digital, `filmless' radiology (and other imagery) systems. They generate a staggering amount of information around the clock. For example, a typical 500-bed hospital might accumulate more than 5 terabytes of image data in a period of 30 years for conventional x-ray images and digital images such as Magnetic Resonance Imaging and Computer Tomography images. With several hospitals contributing to the archive, the storage required will be in the hundreds of terabytes. Systems for reliable, secure, and inexpensive storage and retrieval of digital medical information do not exist today. In this paper, we present a Medical Image Archive and Distribution Service (MIADS) concept. MIADS is a system shared by individual and community hospitals, laboratories, and doctors' offices that need to store and retrieve medical images. Due to the large volume and complexity of the data, as well as the diversified user access requirement, implementation of the MIADS will be a complex procedure. One of the key challenges to implementing a MIADS is to select a cost-effective, scalable system architecture to meet the ingest/retrieval performance requirements. We have performed an in-depth system engineering study, and developed a sophisticated simulation model to address this key challenge. This paper describes the overall system architecture based on our system engineering study and simulation results. In particular, we will emphasize system scalability and upgradability issues. Furthermore, we will discuss our simulation results in detail. The simulations study the ingest/retrieval performance requirements based on different system configurations and architectures for variables such as workload, tape access time, number of drives, number of exams per patient, number of Central Processing Units, patient grouping, and priority impacts. The MIADS, which could be a key component of a broader data repository system, will be able to communicate with and obtain data from existing hospital information systems. We will discuss the external interfaces enabling MIADS to communicate with and obtain data from existing Radiology Information Systems such as the Picture Archiving and Communication System (PACS). Our system design encompasses the broader aspects of the archive node, which could include multimedia data such as image, audio, video, and free text data. This system is designed to be integrated with current hospital PACS through a Digital Imaging and Communications in Medicine interface. However, the system can also be accessed through the Internet using Hypertext Transport Protocol or Simple File Transport Protocol. Our design and simulation work will be key to implementing a successful, scalable medical image archive and distribution system.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A distributed multiserver Web site can provide the scalability necessary to keep up with growing client demand at popular sites. Load balancing of these distributed Web-server systems, consisting of multiple, homogeneous Web servers for document retrieval and a Domain Name Server (DNS) for address resolution, opens interesting new problems. In this paper, we investigate the effects of using a more active DNS which, as an atypical centralized scheduler, applies some scheduling strategy in routing the requests to the most suitable Web server. Unlike traditional parallel/distributed systems in which a centralized scheduler has full control of the system, the DNS controls only a very small fraction of the requests reaching the multiserver Web site. This peculiarity, especially in the presence of highly skewed load, makes it very difficult to achieve acceptable load balancing and avoid overloading some Web servers. This paper adapts traditional scheduling algorithms to the DNS, proposes new policies, and examines their impact under different scenarios. Extensive simulation results show the advantage of strategies that make scheduling decisions on the basis of the domain that originates the client requests and limited server state information (e.g., whether a server is overloaded or not). An initially unexpected result is that using detailed server information, especially based on history, does not seem useful in predicting the future load and can often lead to degraded performance.

Researchers and practitioners in the area of parallel and distributed computing have been lacking a portable, flexible and robust distributed instrumentation system. This paper presents the reference implementation of Baseline Reduced Instrumentation System Kernel (BRISK). BRISK was developed as a part of a realtime system instrumentation and performance visualization project. The design is based on a simple distributed instrumentation system model for flexibility and extensibility. The basic implementation poses minimalistic system requirements and achieves high performance. The paper also shows evaluations of BRISK on both basic and advanced configurations. The first evaluation emphasizes local, simple performance metrics; and the second highlights aggregate performance, built-in clock synchronization and dynamic on-line sorting. Copyright © 2000 John Wiley & Sons, Ltd.

This paper investigates an architecture and implementation for the use of a TCP-friendly protocol in a scalable video distribution system for hierarchically encoded layered video. The design supports a variety of heterogeneous clients, because recent developments have shown that access network and client capabilities differ widely in today's Internet. The distribution system presented here consists of videos servers, proxy caches and clients that make use of a TCP-friendly rate control (TFRC) to perform congestion controlled streaming of layer encoded video. The data transfer protocol of the system is RTP compliant, yet it integrates protocol elements for congestion control with protocols elements for retransmission that is necessary for lossless transfer of contents into proxy caches. The control protocol RTSP is used to negotiate capabilities, such as support for congestion control or retransmission. By tests performed with our experimental platform in a lab test and over the Internet, we show that congestion controlled streaming of layer encoded video through proxy caches is a valid means of supporting heterogeneous clients. We show that filtering of layers depending on a TFRC-controlled permissible bandwidth allows the preferred delivery of the most relevant layers to end-systems while additional layers can be delivered to the cache server. We experiment with uncontrolled delivery from the proxy cache to the client as well, which may result in random loss and bandwidth waste but also a higher goodput, and compare these two approaches.

In this paper, we have described a non-intrusive, scalable administration and monitoring system for high performance grid environment. It is a fundamental building block for achieving and analyzing the performance of the storage virtualization system in a huge and heterogeneous grid storage environment. It offers a very flexible and simple model that collects nodes state information and requirements needed by the other services of our virtualization storage system improving storage distributed data performance. It is based on a multi-tiered hierarchical architecture the start-up of the monitoring and administration system.

This work is part of the ViSaGe project. This project concerns the storage virtualization applied in the grid environment. Its goal is to create and manage virtual storage resources by aggregating geographically distributed physical storage resources shared on a Grid. To these shared resources, a quality of service will be associated and related to the data storage performance. In a Grid environment, sharing resources may improve performances if these resources are well managed and if the management software obtains sufficient knowledge about the grid resources workload (computing nodes, storage nodes and links). The grid resources workload is mainly perceived by a monitoring system. Several existing monitoring systems are available for monitoring the grid resources and applications. Each one provides informations according to its aim. For example, Network Weather Service [6] is designed to monitor grid computing nodes and links. On the other hand, Netlogger [8] monitors grid resources and applications in order to detect application's bottleneck. These systems are useful for a post mortem analysis. However, in ViSaGe, we need a system that analyzes the necessary nodes state during execution time. This system is represented by the ViSaGe Administration and monitoring service "Admon". In this paper, we present our scalable distributed system: Admon. Admon traces applications, and calculates the system resources consumption (CPU, Disks, Links). Its originality consists in providing a new opportunity to improve virtual data storage performance by using workload's constraints (e.g., maximum CPU usage percentage). Many constraints will be discussed (such as time's constraint). These constraints allow performance improvement by assigning nodes to the ViSaGe's jobs in an effective manner.

Researchers and practitioners in the area of parallel and distributed computing have been lacking a portable, flexible and robust distributed instrumentation system. We present the Baseline Reduced Instrumentation System Kernel (BRISK) that we have developed as a part of a realtime system instrumentation and performance visualization project. The design is based on a simple distributed instrumentation system model for flexibility and extensibility. The basic implementation poses minimalistic system requirements and achieves high performance. We show evaluations of BRISK using two distinct configurations: one emphasizes isolated simple performance metrics; and the other, BRISK’s operation on distributed applications, its built-in clock synchronization and dynamic on-line sorting algorithms.

The explosive growth of the Internet demands higher reliability and performance than what the current networking infrastructure can provide. This dissertation explores novel architectures and protocols that provide a methodology for grouping together multiple networking elements, such as routers, gateways, and switches, to create a more reliable and performant distributed networking system. Clustering of networking elements is a novel concept that requires the invention of distributed computing protocols that facilitate efficient and robust support of networking protocols. We introduce the Raincore protocol architecture that achieves these goals by bridging the fields of computer networks and distributed systems. In designing Raincore, we paid special attention to the unique requirements from the networking environment. First, networking clusters need to scale up the networking throughput in addition to the scaling up of computing power. Second, task switching between the different services supported by a networking element has a major negative impact on performance. Third, fast fail-over time is critical for maintaining network connections in the event of failures. We discuss in depth the design of Raincore Group Communication Manager that addresses the forgoing requirements and provides group membership management and reliable multicast transport. It is based on a novel token-ring protocol. We prove that this protocol is formally correct, namely, it satisfies the set of formal specifications that defines the Group Membership problem. The creation of Raincore has already made a substantial impact both at Caltech and the academic community as well as in the industry. The first application is SNOW, a scalable web server cluster that is part of RAIN, a collaborative project between Caltech and JPL/NASA. The second application is RainWall, a commercial solution created by Rainfinity, a Caltech spin-off company, that provides the first fault-tolerant and scalable firewall cluster. These applications exhibit the fast fail-over response, low overhead, and near-linear scalability of the Raincore protocols. In addition, we studied fault-tolerant networking architectures. In particular, we considered efficient constructions of extra-stage fault-tolerant Multistage Interconnection Networks. Multistage Interconnection Networks provide a way to construct a larger switching network using smaller switching elements. We discovered an optimal family of constructions, in the sense that it requires the least number of extra components to tolerate multiple switching element failures. We prove that this is the only family of constructions that has this optimal fault-tolerance property.

Hypermedia retrieval in combination with querying is a very powerful document access metaphor for digital library systems. Conventional distributed hypermedia systems, however, suffer from some well-known problems that make effective, goal-directed document retrieval and maintenance impossible. On the one hand, relationships between documents are modeled on a very low level of abstraction, preventing knowledge re-use and user-adapted navigation through the document space. On the other hand, huge static web structures are prone to redundancies, inconsistencies and costly to maintain. We present an approach of a scalable distributed resource discovery and delivery system that offers access to information through querying and knowledge-based hypermedia browsing. Relationship knowledge is partitioned into handy, independent structures, modeled on a high level of abstraction apart from documents. Navigation paths are computed by the system, combining semantic networks with information retrieval.

After Google published their first paper on their software infrastruc-ture in October 2003, the open-source community quickly began working on similar free solutions. Yahoo! is now able to process terabytes of data daily using Hadoop, which is a scalable distributed file system and an open-source implementation of Google's MapReduce. HBase, a distributed database that uses Hadoop, enables the reliable storage of structured data, just like Google's Bigtable which powers applications like Google Maps and Google Analytics, to name only two. Many companies are tempted to use these technologies, but it is currently difficult to compare today's systems with systems built on top of HBase. This paper presents this new technology and, a list of proposed comparison elements to existing database technology as well as proposed comparison assessment criteria.

Distributed file systems often exhibit high tail latencies, especially in large-scale datacenters and in the presence of competing (and possibly higher priority) workloads. This paper introduces techniques for managing tail latencies in these systems, while addressing the practical challenges inherent in production datacenters (e.g., hardware heterogeneity, interference from other workloads, the need to maximize simplicity and maintainability). We implement our techniques in a scalable distributed file system (an extension of HDFS) used in production at Microsoft. Our evaluation uses 70k servers in 3 datacenters, and shows that our techniques reduce tail latency significantly for production workloads.

The tile assembly model has allowed the study of the nature's process of self-assembly and the development of self-assembling systems for solving complex computational problems. Research into this model has led to progress in two distinct classes of computational systems: Internet-sized distributed computation, such as software architectures for computational grids, and molecular computation, such as DNA computing. The design of large complex tile systems that emulate Turing machines has shown that the tile assembly model is Turing universal, while the design of small tile systems that implement simple algorithms has shown that tile assembly can be used to build private, fault-tolerant, and scalable distributed software systems and robust molecular machines. However, in order for these types of systems to compete with traditional computing devices, we must demonstrate that fairly simple tile systems can implement complex and intricate algorithms for important problems. The state of the art, however, requires vastly complex tile systems with large tile sets to implement such algorithms. In this paper, I present SFS, a tile system that decides 3-SAT by creating O*(1.8393n) nondeterministic assemblies in parallel, while the previous best known solution requires Θ(2n) such assemblies. In some sense, this tile system follows the most complex algorithm implemented using tiles to date. I analyze that the number of required parallel assemblies is O*(1.8393n), that the size of the system's tileset is 147 = Θ(1), and that the assembly time is nondeterministic linear in the size of the input. This work directly improves the time and space complexities of tile-inspired computational-grid architectures and bridges theory and today's experimental limitations of DNA computing.

Developers of distributed multimedia applications face a diversity of multimedia formats, streaming platforms and streaming protocols. Furthermore, support for end-to-end quality-of-service (QoS) is a crucial factor for the development of future distributed multimedia systems. This paper discusses the architecture, design and implementation of a QoS-aware middleware platform for content delivery. The platform supports the development of distributed multimedia applications and can deliver content with QoS guarantees. QoS support is offered by means of an agent infrastructure for QoS negotiation and enforcement. Properties of content are represented using a generic content representation model described using the OMG Meta Object Facility (MOF) model. A content delivery framework manages stream paths for content delivery despite differences in streaming protocols and content encoding. The integration of the QoS support, content representation and content delivery framework results in a QoS-aware middleware that enables representation transparent and location transparent delivery of content.