We show that the Internet topology at the Autonomous System (AS) level has a rich-club phenomenon. The rich nodes, which are a small number of nodes with large numbers of links, are very well connected to each other. The rich-club is a core tier that we measured using the rich-club connectivity and the node-node link distribution. We obtained this core tier without any heuristic assumption between the ASes. The rich-club phenomenon is a simple qualitative way to differentiate between power law topologies and provides a criterion for new network models. To show this, we compared the measured rich-club of the AS graph with networks obtained using the Barabási-Albert (BA) scale-free network model, the Fitness BA model and the Inet-3.0 model.

Based on measurements of the internet topology data, we found that there are two mechanisms which are necessary for the correct modeling of the internet topology at the autonomous systems (AS) level: the interactive growth of new nodes and new internal links, and a nonlinear preferential attachment, where the preference probability is described by a positive-feedback mechanism. Based on the above mechanisms, we introduce the positive-feedback preference (PFP) model which accurately reproduces many topological properties of the AS-level internet, including degree distribution, rich-club connectivity, the maximum degree, shortest path length, short cycles, disassortative mixing, and betweenness centrality. The PFP model is a phenomenological model which provides an insight into the evolutionary dynamics of real complex networks.

Process migration is the act of transferring a process between two machines. It enables dynamic load distribution, fault resilience, eased system administration, and data access locality. Despite these goals and ongoing research efforts, migration has not achieved widespread use. With the increasing deployment of distributed systems in general, and distributed operating systems in particular, process migration is again receiving more attention in both research and product development. As high-performance facilities shift from supercomputers to networks of workstations, and with the ever-increasing role of the World Wide Web, we expect migration to play a more important role and eventually to be widely adopted. This survey reviews the field of process migration by summarizing the key concepts and giving an overview of the most important implementations. Design and implementation issues of process migration are analyzed in general, and then revisited for each of the case studies described: MOSIX, Sprite, Mach, and Load Sharing Facility. The benefits and drawbacks of process migration depend on the details of implementation and, therefore, this paper focuses on practical matters. This survey will help in understanding the potentials of process migration and why it has not caught on.

Load sharing in large, heterogeneous distributed systems allows users to access vast amounts of computing resources scattered around the system and may provide substantial performance improvements to applications. We discuss the design and implementation issues in Utopia, a load sharing facility specifically built for large and heterogeneous systems. The system has no restriction on the types of tasks that can be remotely executed, involves few application changes and no operating system change, supports a high degree of transparency for remote task execution, and incurs low overhead. The algorithms for managing resource load information and task placement take advantage of the clustering nature of large‐scale distributed systems; centralized algorithms are used within host clusters, and directed graph algorithms are used among the clusters to make Utopia scalable to thousands of hosts. Task placements in Utopia exploit the heterogeneous hosts and consider varying resource demands of the tasks. A range of mechanisms for remote execution is available in Utopia that provides varying degrees of transparency and efficiency. A number of applications have been developed for Utopia, ranging from a load sharing command interpreter, to parallel and distributed applications, to a distributed batch facility. For example, an enhanced Unix command interpreter allows arbitrary commands and user jobs to be executed remotely, and a parallel make facility achieves speed‐ups of 15 or more by processing a collection of tasks in parallel on a number of hosts.

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. A trace-driven simulation study of dynamic load balancing in homogeneous distributed systems supporting broadcasting is presented. We use information about job CPU and I/O demands collected from a production system as input to a simulation model that includes a representative CPU scheduling policy and considers the message exchange and job transfer costs explicitly. Seven load balancing algorithms are simulated and their performances compared. We find that load balancing is capable of significantly reducing the mean and standard deviation of job response times, especially under heavy system load, and for jobs with high resource demands. The performances of all hosts, even those originally with light loads, are generally improved by load balancing. The reduction of the mean response time increases with the number of hosts, but levels off at around 30 hosts. Algorithms based on periodic or non-periodic load information exchange provide similar performance, and, among the periodic policies, the algorithms that use a distinguished agent to collect and distribute load information cut down the overhead and scale better. They are also the most appropriate algorithms for adaptive load balancing, which has the potential of offering near-optimal performance under a wide spectrum of system configurations and load conditions. System instability in the form of host overloading is possible when the load information is not up-to-date and the system is under heavy load; however, this undesirable phenomenon can be alleviated by simple measures. Load balancing is still very effective even when up to half of the eligible jobs have to be executed locally. The trace-driven simulation approach to the study of load balancing is found to be critical and effective, an d is recommended for use before implementation efforts. A trace-driven simulation study of dynamic load balancing in homogeneous distributed systems supporting broadcasting is presented. We use information about job CPU and 1/0 demands collected from a production system as input to a simulation model that includes a representative CPU scheduling policy and considers the message exchange and job transfer costs explicitly. Seven load balancing algorithms are simulated...