Scheduling multiple divisible loads in homogeneous star systems

In this paper we analyze scheduling multiple divisible loads on a star-connected system of identical processors. It is shown that this problem is computationally hard. Some special cases appear to be particularly difficult, so it is not even known if they belong to the class NP. Exponential algorithms and special cases solvable in polynomial time are presented. M. Drozdowski’s research partially supported by Polish Ministry of Science and Higher Education.     

An incentive-based distributed mechanism for scheduling divisible loads in tree networks

The underlying assumption of Divisible Load Scheduling (DLS) theory is that the processors composing the network are obedient, i.e., they do not “cheat” the scheduling algorithm. This assumption is unrealistic if the processors are owned by autonomous, self-interested organizations that have no a priori motivation for cooperation and they will manipulate the algorithm if it is beneficial to do so. In this paper, we address this issue by designing a distributed mechanism for scheduling divisible loads in tree networks, called DLS-T, which provides incentives to processors for reporting their true processing capacity and executing their assigned load at full processing capacity. We prove that the DLS-T mechanism computes the optimal allocation in an ex post Nash equilibrium. Finally, we simulate and study the mechanism under various network structures and processor parameters.     

Scheduling divisible loads on heterogeneous linear daisy chain networks with arbitrary processor release times

The problem of distributing and processing a divisible load in a heterogeneous linear network of processors with arbitrary processors release times is considered. A divisible load is very large in size and has computationally intensive CPU requirements. Further, it has the property that the load can be partitioned arbitrarily into any number of portions and can be scheduled onto processors independently for computation. The load is assumed to arrive at one of the farthest end processors, referred to as boundary processors, for processing. The processors in the network are assumed to have nonzero release times, i.e., the time instants from which the processors are available for processing the divisible load. Our objective is to design a load distribution strategy by taking into account the release times of the processors in such a way that the entire processing time of the load is a minimum. We consider two generic cases in which all processors have identical release times and when all processors have arbitrary release times. We adopt both the single and multiinstallment strategies proposed in the divisible load scheduling literature in our design of load distribution strategies, wherever necessary, to achieve a minimum processing time. Finally, when optimal strategies cannot be realized, we propose two heuristic strategies, one for the identical case, and the other for nonidentical release times case, respectively. Several conditions are derived to determine whether or not optimal load distribution exists and illustrative examples are provided for the ease of understanding.     

Scheduling real-time divisible loads with advance reservations

Providing QoS and performance guarantee to arbitrarily divisible loads has become a significant problem for many cluster-based research computing facilities. While progress is being made in scheduling arbitrarily divisible loads, previous approaches have no support for advance reservations. However, with the emergence of Grid applications that require simultaneous access to multi-site resources, supporting advance reservations in a cluster has become increasingly important. In this paper we propose a new real-time divisible load scheduling algorithm that supports advance reservations in a cluster. The impact of advance reservations on system performance is systematically studied. Simulation results show that, with the proposed algorithm and appropriate advance reservations, the system performance could be maintained at the same level as the no reservation case. Thus, Our approach enforces the real-time agreement vis-a-vis addresses the under-utilization concerns.     

Scheduling divisible loads with time and cost constraints

In distributed computing, divisible load theory provides an important system model for allocation of data-intensive computations to processing units working in parallel. The main task is to define how a computation job should be split into parts, to which processors those parts should be allocated and in which sequence. The model is characterized by multiple parameters describing processor availability in time, transfer times of job parts to processors, their computation times and processor usage costs. The main criteria are usually the schedule length and cost minimization. In this paper, we provide the generalized formulation of the problem, combining key features of divisible load models studied in the literature, and prove its NP-hardness even for unrestricted processor availability windows. We formulate a linear program for the version of the problem with a fixed number of processors. For the case with an arbitrary number of processors, we close the gaps in the study of special cases, developing efficient algorithms for single criterion and bicriteria versions of the problem, when transfer times are negligible.

     

Scheduling divisible jobs on hypercubes

In this work a problem of finding an optimal distribution of a divisible computational job among a set of processors is considered. In the model of parallel computer systems two important factors must be taken into account: speeds of processors and speeds of communications links. With regard to this, we propose a deterministic approach finding an optimal distribution of the job's load on a hypercube of processors. The method used allows also the determination of performance bounds on the hypercube architecture.     

Suboptimal solutions using integer approximation techniques forscheduling divisible loads on distributed bus networks

The problem of optimal divisible load distribution in distributed bus networks employing a heterogeneous cluster of processors is addressed. The objective is to minimize the total processing time of the entire load subject to the communication and computation delays. In the mathematical model we adopt, both the granularity of the load fractions and all the associated overheads (also referred to as start-up costs) in the process of communication and computation, are considered explicitly in the problem formulation. We introduce a directed flow graph model for representing the load distribution process. This representation is novel to this literature. With this model, we first derive a closed-form solution for an optimal processing time. We propose an integer approximation algorithm and derive ultimate performance bounds for the class of homogeneous networks. We then extend the problem to a special class of application problems in which the data partitioning is restricted to a finite number of partitions. For this case, we present a recursive procedure to obtain optimal processing time. We then present two different integer approximation algorithms-PIA and IIA that could generate integer load fractions and yield suboptimal solutions. The choice of these algorithms are also analyzed. All the results are extended to a class of homogeneous networks to obtain ultimate performance bounds. Several illustrative examples are provided for ease of explanation     

On the influence of start-up costs in scheduling divisible loads onbus networks

Optimal distribution of divisible loads in bus networks is considered in this paper. The problem of minimizing the processing time is investigated by including all the overhead components that could penalize the performance of the system, in addition to the inherent communication and computation delays. These overheads are considered to be constant additive factors to the respective communication and computation components. Closed-form solution for the processing time is derived and the influence of overheads on the optimal processing time is analyzed. We derive a necessary and sufficient condition for the existence of the optimal processing time. We then study the effect of changing the load distribution sequence on the time performance. Through rigorous analysis, an optimal sequence to distribute the load among the processors is identified, whenever it exists. In case such an optimal sequence fails to exist, we present a greedy algorithm to obtain a suboptimal sequence based on some important properties of the overhead factors. Then, the effect of granularity of the data that is divisible is considered in the analysis for the case of homogeneous networks. An integer approximation algorithm capable of generating integer values of the load fractions in time O(m), where m is the number of processors in the network, is proposed. We then show that the upper bound on the suboptimal solution generated by our algorithm lies within a radius given by the sum of the computation and communication delays. Several numerical examples are presented to illustrate the concepts     

Scheduling in or-parallel Prolog systems: Survey and open problems

Implementation of or-parallel Prolog systems offers a number of interesting scheduling problems. The main issues are the interaction between memory models and scheduling, ordering of multiple solutions, and scheduling of speculative work. The problems occur partly because of the design choices (e.g. the choice of a memory model), and partly because of the desire to maintain observational equivalence between parallel and sequential implementations of Prolog, while achieving high efficiency. In the first part of this paper a common framework for discussing scheduling in or-parallel systems is introduced, and also a collection of issues that must be addressed in such systems is presented. In the second part of the paper we survey a number of solutions to these problems comparing their efficiency whenever possible. We close the survey with a short discussion of open problems.Current association: Carlstedt Elektronik AB     

Approximating the traffic grooming problem in tree and star networks

We consider the problem of grooming paths in all-optical networks with tree topology so as to minimize the switching cost, measured by the total number of used ADMs. We first present efficient approximation algorithms with approximation factor of 2ln(δ⋅g)+o(ln(δ⋅g))$2ln(\delta \cdot g)+o(ln(\delta \cdot g))$ for any fixed node degree bound δ$\delta$ and grooming factor g$g$, and 2lng+o(lng)$2lng+o(lng)$ in unbounded degree directed trees, respectively. In the attempt to extend our results to general undirected trees, we completely characterize the complexity of the problem in star networks by providing polynomial time optimal algorithms for g≤2$g\le 2$ and proving the intractability of the problem for any fixed g>2$g>2$. While for general topologies, the problem was known to be NP-hard g$g$ not constant, the complexity for fixed values of g$g$ was still an open question.     

Scheduling time-constrained multicast messages in circuit-switched tree networks

In this paper, we consider a kind of multicast scheduling problem in a tree network. Each multicast message is transmitted through a directed subtree within the tree network. The transmission time of each multicast message is assumed to be one unit. Two messages can be transmitted at the same time if their subtrees are edge-disjoint. Each message is constrained by a ready time and a deadline, and has a weight we can gain if it is scheduled within its deadline. The optimality criterion is the total weight we gain. We assume that the degree of each subtree is bounded by a constant d and present an approximation algorithm of which the approximation ratio is at most 4d+15.     

Two classes of location problems on tree networks

Cybernetics and Systems Analysis -     

Design and performance evaluation of load distribution strategies for multiple divisible loads on heterogeneous linear daisy chain networks

In this paper, we consider the problem of scheduling multiple divisible loads on heterogeneous linear daisy chain networks. Our objective is to design a load distribution strategy such that the total processing time of a set of loads is minimized. We assume that the set of loads are resident in one of the farthest end processors, which has a scheduler that will distribute the load to the other processors in the network. When distributing a load from the set, the distribution pattern of the previous load has to be taken into consideration to ensure that no processors are left idle and there are no collisions in the communication links. We design single and multi-installments strategies to achieve the above objective. We derive certain important conditions to determine whether an optimum solution exists. We propose two heuristic strategies when an optimum solution is unattainable. Using all the above strategies, we conduct four different simulation experiments to track the performance of strategies under several real-life situations. We conducted four different simulation experiments based on the two heuristic strategies to identify the best combination suitable for our multiple-loads distribution strategy. We also run simulations for a homogeneous system to quantify the performance under 3 different policies, that is, when the loads are (a) unsorted, (b) sorted with smallest load first (SLF) and (c) sorted with largest load first (LLF). A detailed analysis of the simulation results is presented and based on these, recommendations are made for the choice of strategies. Finally, we compare the performance of a single-load distribution strategy against the multiple-loads distribution strategy designed in this paper to quantify the exact performance gain that can be achieved. Illustrative examples are also provided for ease of understanding.     

Distributed scheduling strategy for divisible loads on arbitrarily configured distributed networks using load balancing via virtual routing

In this paper, we consider a scheduling problem for divisible loads originating from single or multiple sites on arbitrary networks. We first propose a generalized mathematical model and formulate the scheduling problem as an optimization problem with an objective to minimize the processing time of the loads. We derive a number of theoretical results on the solution of the optimization problem. On the basis of these first set of results, we propose an efficient algorithm for scheduling divisible loads using the concept of load balancing via virtual routing for an arbitrary network configuration. The proposed algorithm has three major attractive features. Firstly, the algorithm is simple to realize and can be implemented in a distributed fashion. The second one is in its style of working by avoiding the need for generating a timing diagram explicitly for any complex networks having an arbitrary network topology. The last one is its capability of handling divisible loads originating from both single and multiple sites. When divisible loads originate from a single node, we compare the proposed algorithm with a recently proposed RAOLD algorithm which is based on minimum cost spanning tree [J. Yao, V. Bharadwaj, Design and performance analysis of divisible load scheduling strategies on arbitrary graphs, Cluster Computing 7(2) (2004) 191–207]. When divisible loads originate from multiple sites, we test the performance on sparse, medium and densely connected networks. This is the first time in the divisible load theory (DLT) literature that such a generic approach for handling divisible loads originating from multiple sites on arbitrary networks employing load balancing via virtual routing is attempted.     

Requirement-aware strategies for scheduling real-time divisible loads on clusters

This paper investigates the real-time scheduling problem for handling heterogeneous divisible loads on cluster systems. Divisible load applications occur in many fields of science and engineering. Such applications can be easily parallelized in a master–worker fashion, but pose several scheduling challenges. We consider divisible loads associated with deadlines to enhance quality-of-service (QoS) and provide performance guarantees in distributed computing environments. In addition, since the divisible loads to be performed may widely vary in terms of their required hardware and software, we capture the loads’ various processing requirements in our load distribution strategies, a unique feature that is applicable for running proprietary applications only on certain eligible processing nodes. Thus in our problem formulation each load can only be processed by certain processors as both the loads and processors are heterogeneous. We propose scheduling algorithms referred to as Requirements-Aware Real-Time Scheduling (RARTS) algorithms, which consist of a novel scheduling policy, referred to as Minimum Slack Capacity First (MSCF), and two multi-round load distribution strategies, referred to as All Eligible Processors (AEP) and Least Capability First (LCF). We perform rigorous performance evaluation studies to quantify the performance of our strategies on a variety of scenarios.     

Phase-type distributions and representations: Some results and open problems for system theory

In this paper we consider phase-type distributions. These distributions correspond to the random hitting time of an absorbing Markov chain. They are used for modelling various random times, in particular, those which appear in manufacturing systems as processing times, times to failure, repair times, etc. The Markovian nature of these distributions allows the use of very efficient matrix based computer methods for performance evaluation. In this paper we give a system theory oriented introduction to phase-type distributions. We concentrate mainly on the representation problem which consists of finding a Markov chain associated with some phase-type distribution. This is a realization problem in the sense of system theory with a lot of links with the classical linear system theory but also with a number of constraints which make the problem harder but more interesting. Indeed this problem has strong connections with the positive realization problem in control theory. The paper recalls known results, gives some new results, and points out the main remaining problems.     

Scheduling tree dags on parallel architectures

We provide optimal within a constant explicit upper bounds on the makespan of schedules for tree-structured programs on mesh arrays of processors, and provide polynomial-time algorithms to find schedules with makespan matching these bounds. In particular, we show how to find, in polynomial time, a (nonpreemptive) schedule for a binary tree dag withn unit execution time tasks and heighth on ad-dimensional mesh array withm processors and links of unit bandwidth and unit propagation delay whose makespan isO(n/m+n ¹/(d+1)+h), i.e., optimal within a constant factor. Further, we extend these schedules to bounded degree forest dags with arbitrary positive integer execution time tasks and to meshes when the propagation delay of all the links is an arbitrary positive integer. Thus, we provide a polynomial-time approximation algorithm for an NP-hard problem, with a performance ratio that is a constant.We also show how to schedule tree dags on any parallel architecture that satisfies certain natural, not very restrictive, conditions that are satisfied by most parallel architectures used in practice. Let be a fixed positive real number. We provide polynomial time computable schedules for binary tree dags withn unit execution time tasks and heighth (g(n)n ^–,g(n) logn) on any parallel architecture satisfying those conditions, with unit bandwidth and unit propagation delay links, with optimal up to a constant makespanO(g(n)+ft), whereg is a function that depends only on that architecture. The number of processors used is optimal within a constant factor ifh g(n)n ^–, and is optimal within anO(logn) factor ifhg(n)logn. As an example, for hypercube and complete binary tree architectures, we achieve optimal within a constant makespanO(h) whenh=(log² n), using an optimal within anO(logn) factor number of processors. Further, we extend these schedules to the case of bounded-degree forest dags with tasks of arbitrary positive integer execution times and architectures when the propagation delay of all the links is a given arbitrary positive integer.The second author was supported in part by the National Science Foundation under Grant CCR-9106062, and in part by the University of Maryland at College Park, Institute for Advanced Computer Studies.     

异构总线网络中实时可分性负载调度算法

针对异构总线网络提出了一种动态实时可分性负载调度方法.首先,根据可分性负载调度最优性原理,分析了网络中处理器负载分配的最优次序以及参与计算的处理器数目;然后,针对实时任务的截止期限约束提出一种动态负载分配算法,该算法可以利用网络中最少的处理器数目,保证实时任务在其截止期限之前计算完成.理论分析和仿真测试都验证了所提出算法的有效性.     

Co-evolutionary algorithms to solve hierarchized Steiner tree problems in telecommunication networks

This study investigates a hierarchized Steiner tree problem in telecommunication networks. In such networks, users must be connected to capacitated hubs. Additionally, selected hubs must be connected to each other and to extra hubs, if necessary, by considering the latency of the resultant network. A connection between hubs can be considered to be a Steiner tree. This Steiner tree problem is modeled as a bi-level mathematical programming problem that considers two decision levels. In the upper-level, the allocation of users to hubs is performed to minimize the total network connection cost. The lower-level minimizes the user latency concerning the information that flows through the capacitated hubs. Further, two co-evolutionary schemes are developed to solve this bi-level model. The first scheme is an individual–population approach, whereas the second scheme is the traditional population–population approach. The first proposed algorithm exploits the structure of the problem by employing parallel computing in one of the populations. Numerical results depict the effectiveness of the proposed algorithms when the lower-level problem cannot be optimally solved efficiently. Furthermore, the advantages of the proposed schemes over an evolutionary one are exhibited. Finally, the hybridization of both co-evolutionary schemes is implemented to improve the semi-feasible solutions obtained by the second scheme, showing its effectiveness to solve the problem.     

Sensitivity results in open, closed and mixed product form queueing networks

General formulas are proposed to quantify the effects of changing the model parameters in the so-called BCMP network [F. Baskett et al., J. ACM 22 (2) (April 1975) 248–260]. These formulas relate the derivative of the expectation of any function of both the state and the paramaters of the network with respect to any model parameter (i.e., arrival rate, mean service demand, service rate, visit ratio, traffic intensity) to known functions of the state variables. Applications of our results to sensitivity analysis and optimization problems are given.