Showing papers by "Petra Berenbrink published in 2001"

The natural work-stealing algorithm is stable

Abstract: In this paper we analyse a very simple dynamic work-stealing algorithm. In the work-generation model, there are n generators which are arbitrarily distributed among a set of n processors. During each time-step, with probability /spl lambda/, each generator generates a unit-time task which it inserts into the queue of its host processor. After the new tasks are generated, each processor removes one task from its queue and services it. Clearly, the work-generation model allows the load to grow more and more imbalanced, so, even when /spl lambda/<1, the system load can be unbounded. The natural work-stealing algorithm that we analyse works as follows. During each time step, each empty processor sends a request to a randomly selected other processor. Any non-empty processor having received at least one such request in turn decides (again randomly) in favour of one of the requests. The number of tasks which are transferred from the non-empty processor to the empty one is determined by the so-called work-stealing function f. We analyse the long-term behaviour of the system as a function of /spl lambda/ and f. We show that the system is stable for any constant generation rate /spl lambda/<1 and for a wide class of functions f. We give a quantitative description of the functions f which lead to stable systems. Furthermore, we give upper bounds on the average system load (as a function of f and n).

Simple routing strategies for adversarial systems

Abstract: In this paper we consider the problem of delivering dynamically changing input streams in dynamically changing networks where both the topology and the input streams can change in an unpredictable way. In particular, we present two simple distributed balancing algorithms (one for packet injections and one for flow injections) and show that for the case of a single receiver these algorithms will always ensure that the number of packets or flow in the system is bounded at any time step, even for an injection process that completely saturates the capacities of the available edges and even if the network topology changes in a completely unpredictable way. We also show that the maximum number of packets or flow that can be in the system at any time is essentially best possible by providing a lower bound that holds for any online algorithm, whether distributed or not. Interestingly, our balancing algorithms do not behave well in a completely adversarial setting. We show that also in the other extreme of a static network and a static injection pattern the algorithms will converge to a point in which they achieve an average routing time that is close to the best possible average routing time that can be achieved by any strategy. This demonstrates that there are simple algorithms that can be efficient for very different scenarios.

The Natural Work-Stealing Algorithm is Stable

Abstract: In this paper we analyse a very simple dynamic workstealing algorithm. In the work-generation model, there are n generators which are arbitrarily distributed among a set of n processors. During each time-step, with probability \lambda, each generator generates a unit-time task which it inserts into the queue of its host processor. After the new tasks are generated, each processor removes one task from its queue and services it. Clearly, the work-generation model allows the load to grow more and more imbalanced, so, even when \lambda < 1, the system load can be unbounded.The natural work-stealing algorithm that we analyse works as follows. During each time step, each empty processor sends a request to a randomly selected other processor. Any non-empty processor having received at least one such request in turn decides (again randomly) in favour of one of the requests. The number of tasks which are transferred from the non-empty processor to the empty one is determined by the so-called work-stealing function f.We analyse the long-term behaviour of the system as a function of \lambda and f. We show that the system is stable for any constant generation rate \lambda < 1 and for a wide class of functions f. We give a quantitative description of the functions f which lead to stable systems. Furthermore, we give upper bounds on the average system load (as a function of f and n).

SIMLAB-a simulation environment for storage area networks

Abstract: In this paper we present a simulation environment for storage area networks called SIMLAB. SIMLAB is a part of the PRESTO project, which is a joint project of the Electrical Engineering Department and the Computer Science Department of the Paderborn University. The aim of the PRESTO project is to construct a scalable and resource-efficient storage network that can support the real-time delivery of data. SIMLAB has been implemented to aid the development and verification of distributed algorithms for this storage network. However, it has been designed in such a way that it can also be used for the simulation of many other types of networking problems. SIMLAB is based on C++ and common libraries and input/output formats, which ensures that SIMLAB can be used on many different platforms. We therefore expect SIMLAB to be useful also for other people working on similar problems.