Abstract: Future Grid Networks should be able to provide Quality
of Service (QoS) guarantees to their users. In this work
we propose a framework for Grid Networks that provides
deterministic delay guarantees to its Guaranteed Service
(GS) users and best effort service to its Best Effort (BE)
users. The proposed framework is theoretically and experimentally
analyzed. We also define four types of computational
resources based on the type of users (GS, BE) these
resources serve and the priority they give them. We implement
the proposed QoS framework for Grids and verify that
it not only satisfies the delay guarantees given to GS users,
but also improves performance in terms of deadlines missed
and resource use. In our simulations, data from a real Grid
Network are used, validating in this way the appropriateness
and usefulness of the proposed framework.
Abstract: Grid Infrastructures have been used to solve large scale scientific problems that do not have special requirements on QoS. However, the introduction and success of the Grids in commercial applications as well, entails the provision of QoS mechanisms which will allow for meeting the special requirements of the users-customers. In this paper we present an advanced Grid Architecture which incorporates appropriate mechanisms so as to allow guarantees of the diverse and contradictory usersrsquo QoS requirements. We present a runtime estimation model, which is the heart of any scheduling and resource allocation algorithm, and we propose a scheme able to predict the runtime of submitted jobs for any given application on any computer by introducing a general prediction model. Experimental results are presented which indicate the robustness and reliability of the proposed architecture. The scheme has been implemented in the framework of GRIA IST project (Grid Resources for Industrial Applications).
Abstract: An ad-hoc mobile network is a collection of mobile hosts, with wireless communication capability, forming a temporary network without the aid of any established fixed infrastructure. In such a (dynamically changing) network it is not at all easy to avoid broadcasting (and flooding).
In this paper we propose, theoretically analyse and experimentally validate a new and efficient protocol for pairwise communication. The protocol exploits the co-ordinated motion of a small part of the network (i.e. it is a semi-compulsory protocol) in order to provide to various senders and receivers an efficient support for message passing. Our implementation platform is the LEDA system and we have tested the protocol for three classes of graphs (grids, random graphs and bipartite multi-stage graphs) each ing a different ?motion topology?.
Our theoretical analysis (based on properties of random walks) and our experimental measurements indicate that only a small fraction of the mobile stations are enough to be exploited by the support in order to achieve very fast communication between any pair of mobile stations.
Abstract: In this work we examine a task scheduling and data migration problem for Grid Networks, which we refer to as the Data Consolidation (DC) problem. DC arises when a task needs for its execution two or more pieces of data, possibly scattered throughout the Grid Network. In such a case, the scheduler and the data manager must select the data replicas to be used and the site where these will accumulate for the task to be executed. The policies for selecting the data replicas and the data consolidating site comprise the Data Consolidation problem. We propose and experimentally evaluate a number of DC techniques. Our simulation results brace our belief that DC is an important technique for Data Grids since it can substantially improve task delay, network load and other performance related parameters.
Abstract: We examine a task scheduling and data migration problem for grid networks, which we refer to as the Data Consolidation (DC) problem. DC arises when a task concurrently requests multiple pieces of data, possibly scattered throughout the grid network, that have to be present at a selected site before the task¢s execution starts. In such a case, the scheduler and the data manager must select (i) the data replicas to be used, (ii) the site where these data will be gathered for the task to be executed, and (iii) the routing paths to be followed; this is assuming that the selected datasets are transferred concurrently to the execution site. The algorithms or policies for selecting the data replicas, the data consolidating site and the corresponding paths comprise a Data Consolidation scheme. We propose and experimentally evaluate several DC schemes of polynomial number of operations that attempt to estimate the cost of the concurrent data transfers, to avoid congestion that may appear due to these transfers and to provide fault tolerance. Our simulation results strengthen our belief that DC is an important problem that needs to be addressed in the design of data grids, and can lead, if performed efficiently, to significant benefits in terms of task delay, network load and other performance parameters.
Abstract: We propose a fair scheduling algorithm for Computational Grids, called Fair Execution Time Estimation (FETE) algorithm. FETE assigns a task to the computation resource that minimizes what we call its fair execution time estimation. The fair execution time of a task on a certain resource is an estimation of the time by which a task will be executed on the resource, assuming it gets a fair share of the resource’s computational power. Though space-shared scheduling is used in practice, the estimates of the fair execution times are obtained assuming that a time-sharing discipline is used. We experimentally evaluate the proposed algorithm and observe that it outperforms other known scheduling algorithms. We also propose a version of FETE, called Simple FETE (SFETE), which requires no a-priori knowledge of the tasks workload and in most cases has similar performance to that of FETE.
Abstract: This paper presents results from the IST Phosphorus project that studies and implements an optical Grid test-bed. A significant part of this project addresses scheduling and routing algorithms and dimensioning problems of optical grids. Given the high costs involved in setting up actual hardware implementations, simulations are a viable alternative. In this paper we present an initial study which proposes models that reflect real-world grid application traffic characteristics, appropriate for simulation purposes. We detail several such models and the corresponding process to extract the model parameters from real grid log traces, and verify that synthetically generated jobs provide a realistic approximation of the real-world grid job submission process.
Abstract: Grids offer a transparent interface to geographically scattered computation, communication, storage and
other resources. In this chapter we propose and evaluate QoS-aware and fair scheduling algorithms for
Grid Networks, which are capable of optimally or near-optimally assigning tasks to resources, while taking
into consideration the task characteristics and QoS requirements. We categorize Grid tasks according to
whether or not they demand hard performance guarantees. Tasks with one or more hard requirements are
referred to as Guaranteed Service (GS) tasks, while tasks with no hard requirements are referred to as Best
Effort (BE) tasks. For GS tasks, we propose scheduling algorithms that provide deadline or computational
power guarantees, or offer fair degradation in the QoS such tasks receive in case of congestion. Regarding
BE tasks our objective is to allocate resources in a fair way, where fairness is interpreted in the max-min fair
share sense. Though, we mainly address scheduling problems on computation resources, we also look at
the joint scheduling of communication and computation resources and propose routing and scheduling
algorithms aiming at co-allocating both resource type so as to satisfy their respective QoS requirements.
Abstract: This research attempts a first step towards investigating the aspect of radiation awareness in environments with abundant heterogeneous wireless networking. We call radiation at a point of a 3D wireless network the total amount of electromagnetic quantity the point is exposed to, our definition incorporates the effect of topology as well as the time domain, data traffic and environment aspects. Even if the impact of radiation to human health remains largely unexplored and controversial, we believe it is worth trying to understand and control. We first analyze radiation in well known topologies (random and grids), randomness is meant to capture not only node placement but also uncertainty of the wireless propagation model. This initial understanding of how radiation adds (over space and time) can be useful in network design, to reduce health risks. We then focus on the minimum radiation path problem of finding the lowest radiation trajectory of a person moving from a source to a destination point of the network region. We propose three heuristics which provide low radiation paths while keeping path length low, one heuristic gets in fact quite close to the offline solution we compute by a shortest path algorithm. Finally, we investigate the interesting impact on the heuristics' performance of diverse node mobility.
Abstract: Future Grid Networks should be able to provide Quality of Service (QoS) guarantees
to their users. In this work we examine the way Grid resources should be
configured so as to provide deterministic delay guarantees to Guaranteed Service
(GS) users and fairness to Best Effort (BE) users. The resources are partitioned
in groups that serve GS users only, or BE users only, or both types of users with
different priorities. Furthermore, the GS users are registered to the resources
either statically or dynamically, while both single and multi-Cpu resources are
examined. Finally the proposed resource configurations for providing QoS are
implemented in theGridSim environment and a number simulations are executed.
Our results indicate that the allocation of resources to both types of users, with
different priorities, results in fewer deadlines missed and better resources utilization.
Finally benefits can be derived from the dynamic registration of GS users
to the resources
Abstract: We consider information aggregation as a method for reducing the information exchanged in a Grid network and used by the resource manager in order to make scheduling decisions. In this way, information is summarized across nodes and sensitive or detailed information can be kept private, while resources are still publicly available for use. We present a general framework for information aggregation, trying to identify issues that relate to aggregation in Grids. In this context, we describe a number of techniques, including single point and intra-domain aggregation, define appropriate grid-specific domination relations and operators for aggregating static and dynamic resource information, and discuss resource selection optimization functions. The quality of an aggregation scheme is measured both by its effects on the efficiency of the scheduler¢s decisions and also by the reduction it brings on the amount of resource information recorded, a tradeoff that we examine in detail. Simulation experiments demonstrate that the proposed schemes achieve significant information reduction, either in the amount of information exchanged, or in the frequency of the updates, while at the same time maintaining most of the value of the original information as expressed by a stretch factor metric we introduce.
Abstract: Efficient task scheduling is fundamental for the success of the Grids,
since it directly affects the Quality of Service (QoS) offered to the users. Efficient
scheduling policies should be evaluated based not only on performance
metrics that are of interest to the infrastructure side, such as the Grid resources
utilization efficiency, but also on user satisfaction metrics, such as the percentage
of tasks served by the Grid without violating their QoS requirements. In this
paper, we propose a scheduling algorithm for tasks with strict timing requirements,
given in the form of a desired start and finish time. Our algorithm aims
at minimizing the violations of the time constraints, while at the same time
minimizing the number of processors used. The proposed scheduling method
exploits concepts derived from spectral clustering, and groups together for assignment
to a computing resource the tasks so to a) minimize the time overlapping
of the tasks assigned to a given processor and b) maximize the degree of
time overlapping among tasks assigned to different processors. Experimental
results show that our proposed strategy outperforms greedy scheduling algorithms
for different values of the task load submitted.
Abstract: Efficient task scheduling is fundamental for the success of the Grids,
since it directly affects the Quality of Service (QoS) offered to the users. Efficient
scheduling policies should be evaluated based not only on performance
metrics that are of interest to the infrastructure side, such as the Grid resources
utilization efficiency, but also on user satisfaction metrics, such as the percentage
of tasks served by the Grid without violating their QoS requirements. In this
paper, we propose a scheduling algorithm for tasks with strict timing requirements,
given in the form of a desired start and finish time. Our algorithm aims
at minimizing the violations of the time constraints, while at the same time
minimizing the number of processors used. The proposed scheduling method
exploits concepts derived from spectral clustering, and groups together for assignment
to a computing resource the tasks so to a) minimize the time overlapping
of the tasks assigned to a given processor and b) maximize the degree of
time overlapping among tasks assigned to different processors. Experimental
results show that our proposed strategy outperforms greedy scheduling algorithms
for different values of the task load submitted.