16,064 research outputs found

    Datacenter Traffic Control: Understanding Techniques and Trade-offs

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    Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

    A Novel Approach to Workload Allocation of QoS-Constrained Workflow-Based Jobs in a Utility Grid

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    Teaching Substantive Environmental Law and Practice Skills Through Interest Group Role-Playing

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    Most law students take their first introductory course in environmental law during their second year of law school. The traditional first-year curriculum does little to prepare students for the complex statutory and regulatory models for most environmental regulation. Law students at the end of their first year often have had little exposure to statutory interpretation. Further, they often have no exposure to administrative law and regulatory implementation. These students may expect statutes to provide clear statements of rules rather than guidelines for administrative rulemaking. They also tend to view the lawmaking and interpretive process through the traditional lens of congressional legislation and common-law-style judicial interpretation in a bipolar scheme of implementation--where the regulatory agencies and the regulated industries are the only players. In fact, environmental regulatory programs constantly evolve through a complex interaction of legislative amendment, administrative rulemaking, and judicial interpretation. Influencing these programs are the multipolar interaction of regulated industries, environmental groups, state agencies, and federal regulators. Law students accustomed to the bipolar model of common-law legal development and who expect statutory law to consist of a simple reading of clear statutory texts can find this interest group pluralist model of law development bewildering. One way to help give context to this complex interaction is to place students in the roles of the various advocates and decision-makers in the environmental law processes. Assigning students to adopt the perspective of various distinct players in the regulatory process, such as agency lawyer, industry lawyer, and environmental NGO lawyer, helps make this complex interaction more accessible to students. This also provides an introduction into the skills of statutory interpretation and regulatory implementation. At Pace Law School, we have had considerable success integrating this approach into an Environmental Law Skills course. This course combines a comprehensive study of the Clean Water Act (CWA) regulatory program with skills-based exercises in administrative rulemaking, judicial review, regulatory permitting, negotiation, and enforcement. The course was added to the curriculum in the 1990s in response to the growing recognition by the legal academy that the traditional case-oriented method of instruction failed to result in law graduates with basic competencies expected of lawyers. The course has been refined over the years to incorporate the Carnegie Report\u27s more recent critiques: the legal education\u27s failure to foster students\u27 development of their professional identities and their understanding of lawyers\u27 role in representing clients. By integrating role-playing, problem solving, and doctrinal instruction, the course seeks to engage students in active learning and professional identity development. The course also seeks to implement recommendations for the improvement of legal instruction contained in Professor Stuckey\u27s influential 2007 report, Best Practices for Legal Education. In particular, the course seeks to “teach doctrine, theory, and practice as part of a unified, coordinated program of instruction” as recommended in that report

    Teamwork protocol

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    This protocol represents an attempt to assist in the instruction of teamwork assessment for first-year students across QUT. We anticipate that teaching staff will view this protocol as a generic resource in teamwork instruction, processes and evaluation. Teamwork has been acknowledged as a problematic practice at QUT while existing predominantly in importance amongst graduate capabilities for all students at this institution. This protocol is not an extensive document on the complexities and dynamics of teamwork processes, but instead presents itself as a set of best practice guidelines and recommendations to assist in team design, development, management, support and assessment. It is recommended that this protocol be progressively implemented across QUT, not only to attain teamwork teaching consistency, but to address and deal with the misconceptions and conflict around the importance of the teamwork experience. The authors acknowledge the extensive input and contributions from a Teamwork Steering Committee selected from academic staff and administrative members across the institution. As well, we welcome feedback and suggestions to both fine tune and make inclusive those strategies that staff believe add to optimal teamwork outcomes

    Increasing allocated tasks with a time minimization algorithm for a search and rescue scenario

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    Rescue missions require both speed to meet strict time constraints and maximum use of resources. This study presents a Task Swap Allocation (TSA) algorithm that increases vehicle allocation with respect to the state-of-the-art consensus-based bundle algorithm and one of its extensions, while meeting time constraints. The novel idea is to enable an online reconfiguration of task allocation among distributed and networked vehicles. The proposed strategy reallocates tasks among vehicles to create feasible spaces for unallocated tasks, thereby optimizing the total number of allocated tasks. The algorithm is shown to be efficient with respect to previous methods because changes are made to a task list only once a suitable space in a schedule has been identified. Furthermore, the proposed TSA can be employed as an extension for other distributed task allocation algorithms with similar constraints to improve performance by escaping local optima and by reacting to dynamic environments

    A novel approach to allocating QoS-constrained workflow-based jobs in a multi-cluster grid

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    Clusters are increasingly interconnected to form multi-cluster systems, which are becoming popular for scientific computation. Grid users often submit their applications in the form of workflows with certain Quality of Service (QoS) requirements imposed on the workflows. These workflows detail the composition of Grid services and the level of service required from the Grid. This paper addresses workload allocation techniques for Grid workflows. We model a resource within a cluster as a G/G/1 queue and minimise failures (QoS requirement violation) of jobs by solving a mixed-integer non-linear program (MINLP). The novel approach is evaluated through an experimental simulation and the results confirm that the proposed workload allocation strategy not only provides QoS guarantee but also performs considerably better in terms of satisfying QoS requirements of Grid workflows than reservation-based scheduling algorithms. © 2006 ACM

    SEAALL Handbook Revision Materials, 1996

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    These materials include correspondence, surveys, and drafts for the 1996 version of the SEAALL Chapter Handbook and Procedures Manual
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