Reflections on Active Networking

Interactions among telecommunications networks, computers, and other peripheral devices have been of interest since the earliest distributed computing systems. A key architectural question is the location (and nature) of programmability. One perspective, that examined in this paper, is that network elements should be as programmable as possible, in order to build the most flexible distributed computing systems. This paper presents my personal view of the history of programmable networking over the last two decades, and in the spirit of vox audita perit, littera scripta manet , includes an account of how what is now called Active Networking came into being. It demonstrates the deep roots Active Networking has in the programming languages, networking and operating systems communities, and shows how interdisciplinary approaches can have impacts greater than the sums of their parts. Lessons are drawn both from the broader research agenda, and the specific goals pursued in the SwitchWare project. I close by speculating on possible futures for Active Networking

Multigrain shared memory

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 197-203).by Donald Yeung.Ph.D

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

Doctor of Philosophy

dissertationHigh-performance supercomputers on the Top500 list are commonly designed around commodity CPUs. Most of the codes executed on these machines are message-passing codes using the message-passing toolkit (MPI). Thus it makes sense to look at these machines from a holistic systems architecture perspective and consider optimizations to commodity processors that make them more efficient in message-passing architectures. Described herein is a new User-Level Notification (ULN) architecture that significantly improves message-passing performance. The architecture integrates a simultaneous multithreaded (SMT) processor with a user-level network interface (NI) that can directly control the execution scheduling of threads on the processor. By allowing the network interface to control the execution of message handling code at the user level, the operating system (OS) related overhead for handling interrupts and user code dispatch related to notifications is eliminated. By using an SMT processor, message handling can be performed in one thread concurrent to user computation in other threads, thus most of the overhead of executing message handlers can be hidden. This dissertation presents measurements showing the OS overheads related to message-passing are significant in modern architectures and describes a new architecture that significantly reduces these overheads. On a communication-intensive real-world application, the ULN architecture provides a 50.9% performance improvement over a more traditional OS-based NIC and a 5.29-31.9% improvement over a best-of-class user-level NIC due to the user-level notifications

Distributed Shared Memory based Live VM Migration

Cloud computing is the new trend in computing services and IT industry, this computing paradigm has numerous benefits to utilize IT infrastructure resources and reduce services cost. The key feature of cloud computing depends on mobility and scalability of the computing resources, by managing virtual machines. The virtualization decouples the software from the hardware and manages the software and hardware resources in an easy way without interruption of services. Live virtual machine migration is an essential tool for dynamic resource management in current data centers. Live virtual machine is defined as the process of moving a running virtual machine or application between different physical machines without disconnecting the client or application. Many techniques have been developed to achieve this goal based on several metrics (total migration time, downtime, size of data sent and application performance) that are used to measure the performance of live migration. These metrics measure the quality of the VM services that clients care about, because the main goal of clients is keeping the applications performance with minimum service interruption. The pre-copy live VM migration is done in four phases: preparation, iterative migration, stop and copy, and resume and commitment. During the preparation phase, the source and destination physical servers are selected, the resources in destination physical server are reserved, and the critical VM is selected to be migrated. The cloud manager responsibility is to make all of these decisions. VM state migration takes place and memory state is transferred to the target node during iterative migration phase. Meanwhile, the migrated VM continues to execute and dirties its memory. In the stop and copy phase, VM virtual CPU is stopped and then the processor and network states are transferred to the destination host. Service downtime results from stopping VM execution and moving the VM CPU and network states. Finally in the resume and commitment phase, the migrated VM is resumed running in the destination physical host, the remaining memory pages are pulled by destination machine from the source machine. The source machine resources are released and eliminated. In this thesis, pre-copy live VM migration using Distributed Shared Memory (DSM) computing model is proposed. The setup is built using two identical computation nodes to construct all the proposed environment services architecture namely the virtualization infrastructure (Xenserver6.2 hypervisor), the shared storage server (the network file system), and the DSM and High Performance Computing (HPC) cluster. The custom DSM framework is based on a low latency memory update named Grappa. Moreover, HPC cluster is used to parallelize the work load by using CPUs computation nodes. HPC cluster employs OPENMPI and MPI libraries to support parallelization and auto-parallelization. The DSM allows the cluster CPUs to access the same memory space pages resulting in less memory data updates, which reduces the amount of data transferred through the network. The thesis proposed model achieves a good enhancement of the live VM migration metrics. Downtime is reduced by 50 % in the idle workload of Windows VM and 66.6% in case of Ubuntu Linux idle workload. In general, the proposed model not only reduces the downtime and the total amount of data sent, but also does not degrade other metrics like the total migration time and the applications performance