Message scheduling is shown to be very effective in belief propagation (BP) algorithms. However, most existing scheduling algorithms use fixed heuristics regardless of the structure of the graphs or properties of the distribution. On the other hand, designing different scheduling heuristics for all graph structures are not feasible. In this paper, we propose a reinforcement learning based messa...

Advances in technology giving increasing importance to information service networks and the increasing use of personal workstations are two factors which permit the construction of distributed applications running on a large set of interconnected systems Existing frame works for the development of distributed applications only provide for manual scheduling of application services in particular ...

During the past several years, a large number of studies have been conducted in the area of sharable resource constrained scheduling problems. Intelligent manufacturing planning and scheduling based on meta-heuristic methods, such as the simulated annealing and particle swarm optimization, have become common tools for finding satisfactory solutions within reasonable computational times in real ...

In this paper, we study the performance of opportunistic scheduling for downlink data transmissions with type-II packet-combining hybrid ARQ in a multirate cellular network for a fast fading environment. We develop a Markov model for a two-user scenario with two feasible transmission rates, and derive the throughput distribution. Numerical results suggest that there exists an operating region w...

With the emergence of Cloud computing and Grid Computing, Distributed Scheduling (DS) problems have attracted attention by researchers in recent years. Distributed scheduling requires an uneven distribution of tasks on individual processors. Different heuristic based algorithms to perform the task scheduling have been proposed by the various researchers. This paper offers a new strategy for tas...

In this article we describe a multi-agent dynamic scheduling environment where autonomous agents represent enterprises and manage the capacity of individual macro-resources in a production-distribution context. The agents are linked by client-supplier relationships and inter-agent communication must take place. The model of the environment, the appropriate agent interaction protocol and a coope...

In this paper, we consider task-level scheduling algorithms with respect to budget constraints for a bag of MapReduce jobs on a set of provisioned heterogeneous (virtual) machines in cloud platforms. The heterogeneity is manifested in the popular ”pay-as-you-go” charging model where the service machines with different performance would have different service rates. We organize a bag of jobs as ...

Schedules can be built in a similar way to a human scheduler by using a set of rules that involve domain knowledge. This paper presents an Estimation of Distribution Algorithm (EDA) for the nurse scheduling problem, which involves choosing a suitable scheduling rule from a set for the assignment of each nurse. Unlike previous work that used Genetic Algorithms (GAs) to implement implicit learnin...

This paper introduces an Object-Oriented Model Integration (OOMI) framework and its application in a practice distribution system. The genus graph of Structured Modelling is extended to represent sequence and scheduling models. A heterogeneous integration from one allocation model and one scheduling model is implemented in OOMI.