We measure the distribution of lifetimes for UNIX processes and propose a functional form that fits this distribution well. We use this functional form to derive a policy for preemptive migration, and then use a trace-driven simulator to compare our proposed policy with other preemptive migration policies, and with a non-preemptive load balancing strategy. We find that, contrary to previous reports, the performance benefits of preemptive migration are significantly greater than those of non-preemptive migration, even when the memorytransfer cost is high. Using a model of migration costs representative of current systems, we find that preemptive migration reduces the mean delay (queueing and migration) by 35 -- 50%, compared to non-preemptive migration. 1 Introduction Most systems that perform load balancing use remote execution (i.e. non-preemptive migration) based on a priori knowledge of process behavior, often in the form of a list of process names eligible for migration. Althoug...

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This paper presents a new strategy for increasing the availability of data in multi-processor, shared-nothing database machines. This technique, termed chained declustering, is demonstrated to provide superior performance in the event of failures while maintaining a very high degree of data availability. Furthermore, unlike most earlier replication strategies, the implementation of chained declustering requires no special hardware and only minimal modifications to existing software.

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This paper presents a method for qualitative and quantitative analysis of load sharing algorithms, using a number of well known examples as illustration. Algorithm design choices are considered with respect to the main activities of information dissemination and allocation decision making. We argue that nodes must be capable of making local decisions, and for this efficient state dissemination techniques are necessary. Activities related to remote execution should be bounded and restricted to a small proportion of the activity in the system. The quantitative analysis provides both performance and efficiency measures, including consideration of the load and delay characteristics of the environment. To assess stability, which is also a precondition for scalability,we introduce and measure load sharing hit-ratio, the ratio of remote execution requests concluded successfully. Using our analysis method, we are able to suggest improvements to some published algorithms.

A process is an operating system abstraction representing an instance of a running computer program. Process migration is the act of transferring a process between two machines during its execution. Several implementations

Efficient allocation of communication channels is crit-ical for the performance of wireless mobile computing systems. The centralized channel allocation algorithms proposed in literature are neither robust, nor scalable. Distributed channel allocation schemes proposed in the past are complicated and require active participation of the mobile nodes. These algorithms are unable to dy-namically adjust to spatial and temporal fluctuations in channel demand. We present a dynamic distributed channel allocation algorithm that can quickly adapt to changes in load distribution. The algorithm described in this paper requires minimal involvement of the mo-bile nodes, thus conserving their limited energy supply. The algorithm is proved to be deadlock free, starvation free and fair. It prevents co-channel interference and is scalable.

Multi-agent systems (MAS) are subject to performance bottlenecks in cases where agents cannot perform tasks by themselves due to insu cient resources. Solutions to such problems include passing tasks to others or agent migration to remote hosts. We propose agent cloning as a more comprehensive approach to the problem of local agent overloads. Agent cloning subsumes task transfer and agent mobility. According to our paradigm, agents may clone, pass tasks to others, die or merge. We discuss the requirements of implementing a cloning mechanism and its bene ts in a Multi-Agent System, and support our claims with simulation results.

In a distributed real-time system, uneven task arrivals temporarily overload some nodes while leaving others idle or underloaded. Consequently, some tasks may miss their deadlines even if the overall system has the capacity to meet the deadlines of all tasks. An effective load sharing (LS) scheme is proposed as a solution to this problem. Upon arrival of a task at a node, the node determines whether or not the node can complete the task in time under the minimum--laxity--first--served policy. If the task cannot be guaranteed or if guarantees of some other tasks are to be violated due to the addition of this task to the existing schedule, the node looks up the list of loss--minimizing decisions , and determines the best node among a set of nodes in its physical proximity, called its buddy set , to which the task(s) may be transferred. This list of decisions is periodically updated using Bayesian decision analysis and prior/posterior state distributions. These probability distributions a...