Scheduling Perfectly Periodic Services Quickly with Aggregation

The problem of scheduling periodic services that have different period lengths seeks to find a schedule in which the workload is nearly the same in every time unit. A time unit’s workload is the sum of the workloads of the services scheduled for that time unit. A level workload minimizes the variability in the resources required and simplifies capacity and production planning. This paper considers the problem in which the schedule for each service must be perfectly periodic, and the schedule length is a multiple of the services’ period lengths. The objective is to minimize the maximum workload. The problem is strongly NP-hard, but there exist heuristics that perform well when the number of services is large. Because many services will have the same period length, we developed a new aggregation approach that separates the problem into subproblems for each period length, uses the subproblem solutions to form aggregate services, schedules these, and then creates a solution to the original instance. We also developed an approach that separates the problem into subproblems based on a partition of the period lengths. Computational experiments show that using aggregation generates high-quality solutions and reduces computational effort. The quality of the partition approach depended upon the partition used

Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems

A cyber-physical system (CPS) employs tight integration of, and coordination between computational, networking, and physical elements. Wireless sensor-actuator networks provide a new communication technology for a broad range of CPS applications such as process control, smart manufacturing, and data center management. Sensing and control in these systems need to meet stringent real-time performance requirements on communication latency in challenging environments. There have been limited results on real-time scheduling theory for wireless sensor-actuator networks. Real-time transmission scheduling and analysis for wireless sensor-actuator networks requires new methodologies to deal with unique characteristics of wireless communication. Furthermore, the performance of a wireless control involves intricate interactions between real-time communication and control. This thesis research tackles these challenges and make a series of contributions to the theory and system for wireless CPS. (1) We establish a new real-time scheduling theory for wireless sensor-actuator networks. (2) We develop a scheduling-control co-design approach for holistic optimization of control performance in a wireless control system. (3) We design and implement a wireless sensor-actuator network for CPS in data center power management. (4) We expand our research to develop scheduling algorithms and analyses for real-time parallel computing to support computation-intensive CPS

Architecting Data Centers for High Efficiency and Low Latency

Modern data centers, housing remarkably powerful computational capacity, are built in massive scales and consume a huge amount of energy. The energy consumption of data centers has mushroomed from virtually nothing to about three percent of the global electricity supply in the last decade, and will continuously grow. Unfortunately, a significant fraction of this energy consumption is wasted due to the inefficiency of current data center architectures, and one of the key reasons behind this inefficiency is the stringent response latency requirements of the user-facing services hosted in these data centers such as web search and social networks. To deliver such low response latency, data center operators often have to overprovision resources to handle high peaks in user load and unexpected load spikes, resulting in low efficiency. This dissertation investigates data center architecture designs that reconcile high system efficiency and low response latency. To increase the efficiency, we propose techniques that understand both microarchitectural-level resource sharing and system-level resource usage dynamics to enable highly efficient co-locations of latency-critical services and low-priority batch workloads. We investigate the resource sharing on real-system simultaneous multithreading (SMT) processors to enable SMT co-locations by precisely predicting the performance interference. We then leverage historical resource usage patterns to further optimize the task scheduling algorithm and data placement policy to improve the efficiency of workload co-locations. Moreover, we introduce methodologies to better manage the response latency by automatically attributing the source of tail latency to low-level architectural and system configurations in both offline load testing environment and online production environment. We design and develop a response latency evaluation framework at microsecond-level precision for data center applications, with which we construct statistical inference procedures to attribute the source of tail latency. Finally, we present an approach that proactively enacts carefully designed causal inference micro-experiments to diagnose the root causes of response latency anomalies, and automatically correct them to reduce the response latency.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144144/1/yunqi_1.pd

Capacity Allocation for Clouds with Parallel Processing, Batch Arrivals, and Heterogeneous Service Requirements

Problem Definition: Allocating sufficient capacity to cloud services is a challenging task, especially when demand is time-varying, heterogeneous, contains batches, and requires multiple types of resources for processing. In this setting, providers decide whether to reserve portions of their capacity to individual job classes or to offer it in a flexible manner. Methodology/results: In collaboration with Huawei Cloud, a worldwide provider of cloud services, we propose a heuristic policy that allocates multiple types of resources to jobs and also satisfies their pre-specified service level agreements (SLAs). We model the system as a multi-class queueing network with parallel processing and multiple types of resources, where arrivals (i.e., virtual machines and containers) follow time-varying patterns and require at least one unit of each resource for processing. While virtual machines leave if they are not served immediately, containers can join a queue. We introduce a diffusion approximation of the offered load of such system and investigate its fidelity as compared to the observed data. Then, we develop a heuristic approach that leverages this approximation to determine capacity levels that satisfy probabilistic SLAs in the system with fully flexible servers. Managerial Implications: Using a data set of cloud computing requests over a representative 8-day period from Huawei Cloud, we show that our heuristic policy results in a 20% capacity reduction and better service quality as compared to a benchmark that reserves resources. In addition, we show that the system utilization induced by our policy is superior to the benchmark, i.e., it implies less idling of resources in most instances. Thus, our approach enables cloud operators to both reduce costs and achieve better performance

Stochastic scheduling and workload allocation : QoS support and profitable brokering in computing grids

Abstract: The Grid can be seen as a collection of services each of which performs some functionality. Users of the Grid seek to use combinations of these services to perform the overall task they need to achieve. In general this can be seen as aset of services with a workflow document describing how these services should be combined. The user may also have certain constraints on the workflow operations, such as execution time or cost ----t~ th~ user, specified in the form of a Quality of Service (QoS) document. The users . submit their workflow to a brokering service along with the QoS document. The brokering service's task is to map any given workflow to a subset of the Grid services taking the QoS and state of the Grid into account -- service availability and performance. We propose an approach for generating constraint equations describing the workflow, the QoS requirements and the state of the Grid. This set of equations may be solved using Mixed-Integer Linear Programming (MILP), which is the traditional method. We further develop a novel 2-stage stochastic MILP which is capable of dealing with the volatile nature of the Grid and adapting the selection of the services during the lifetime of the workflow. We present experimental results comparing our approaches, showing that the . 2-stage stochastic programming approach performs consistently better than other traditional approaches. Next we addresses workload allocation techniques for Grid workflows in a multi-cluster Grid We model individual clusters as MIMIk. queues and obtain a numerical solutio~ for missed deadlines (failures) of tasks of Grid workflows. We also present an efficient algorithm for obtaining workload allocations of clusters. Next we model individual cluster resources as G/G/l queues and solve an optimisation problem that minimises QoS requirement violation, provides QoS guarantee and outperforms reservation based scheduling algorithms. Both approaches are evaluated through an experimental simulation and the results confirm that the proposed workload allocation strategies combined with traditional scheduling algorithms performs considerably better in terms of satisfying QoS requirements of Grid workflows than scheduling algorithms that don't employ such workload allocation techniques. Next we develop a novel method for Grid brokers that aims at maximising profit whilst satisfying end-user needs with a sufficient guarantee in a volatile utility Grid. We develop a develop a 2-stage stochastic MILP which is capable of dealing with the volatile nature . of the Grid and obtaining cost bounds that ensure that end-user cost is minimised or satisfied and broker's profit is maximised with sufficient guarantee. These bounds help brokers know beforehand whether the budget limits of end-users can be satisfied and. if not then???????? obtain appropriate future leases from service providers. Experimental results confirm the efficacy of our approach.Imperial Users onl

Virtual Organization Clusters: Self-Provisioned Clouds on the Grid

Virtual Organization Clusters (VOCs) provide a novel architecture for overlaying dedicated cluster systems on existing grid infrastructures. VOCs provide customized, homogeneous execution environments on a per-Virtual Organization basis, without the cost of physical cluster construction or the overhead of per-job containers. Administrative access and overlay network capabilities are granted to Virtual Organizations (VOs) that choose to implement VOC technology, while the system remains completely transparent to end users and non-participating VOs. Unlike alternative systems that require explicit leases, VOCs are autonomically self-provisioned according to configurable usage policies. As a grid computing architecture, VOCs are designed to be technology agnostic and are implementable by any combination of software and services that follows the Virtual Organization Cluster Model. As demonstrated through simulation testing and evaluation of an implemented prototype, VOCs are a viable mechanism for increasing end-user job compatibility on grid sites. On existing production grids, where jobs are frequently submitted to a small subset of sites and thus experience high queuing delays relative to average job length, the grid-wide addition of VOCs does not adversely affect mean job sojourn time. By load-balancing jobs among grid sites, VOCs can reduce the total amount of queuing on a grid to a level sufficient to counteract the performance overhead introduced by virtualization

Modelação e simulação de equipamentos de rede para Indústria 4.0

Currently, the industrial sector has increasingly opted for digital technologies in order to automate all its processes. This development comes from notions like Industry 4.0 that redefines the way these systems are designed. Structurally, all the components of these systems are connected in a complex network known as the Industrial Internet of Things. Certain requirements arise from this concept regarding industrial communication networks. Among them, the need to ensure real-time communications, as well as support for dynamic resource management, are extremely relevant. Several research lines pursued to develop network technologies capable of meeting such requirements. One of these protocols is the Hard Real-Time Ethernet Switch (HaRTES), an Ethernet switch with support for real-time communications and dynamic resource management, requirements imposed by Industry 4.0. The process of designing and implementing industrial networks can, however, be quite time consuming and costly. These aspects impose limitations on testing large networks, whose level of complexity is higher and requires the usage of more hardware. The utilization of network simulators stems from the necessity to overcome such restrictions and provide tools to facilitate the development of new protocols and evaluation of communications networks. In the scope of this dissertation a HaRTES switch model was developed in the OMNeT++ simulation environment. In order to demonstrate a solution that can be employed in industrial real-time networks, this dissertation presents the fundamental aspects of the implemented model as well as a set of experiments that compare it with an existing laboratory prototype, with the objective of validating its implementation.Atualmente o setor industrial tem vindo cada vez mais a optar por tecnologias digitais de forma a automatizar todos os seus processos. Este desenvolvimento surge de noções como Indústria 4.0, que redefine o modo de como estes sistemas são projetados. Estruturalmente, todos os componentes destes sistemas encontram-se conectados numa rede complexa conhecida como Internet Industrial das Coisas. Certos requisitos advêm deste conceito, no que toca às redes de comunicação industriais, entre os quais se destacam a necessidade de garantir comunicações tempo-real bem como suporte a uma gestão dinâmica dos recursos, os quais são de extrema importância. Várias linhas de investigação procuraram desenvolver tecnologias de rede capazes de satisfazer tais exigências. Uma destas soluções é o "Hard Real-Time Ethernet Switch" (HaRTES), um switch Ethernet com suporte a comunicações de tempo-real e gestão dinâmica de Qualidade-de-Serviço (QoS), requisitos impostos pela Indústria 4.0. O processo de projeto e implementação de redes industriais pode, no entanto, ser bastante moroso e dispendioso. Tais aspetos impõem limitações no teste de redes de largas dimensões, cujo nível de complexidade é mais elevado e requer o uso de mais hardware. Os simuladores de redes permitem atenuar o impacto de tais limitações, disponibilizando ferramentas que facilitam o desenvolvimento de novos protocolos e a avaliação de redes de comunicações. No âmbito desta dissertação desenvolveu-se um modelo do switch HaRTES no ambiente de simulação OMNeT++. Com um objetivo de demonstrar uma solução que possa ser utilizada em redes de tempo-real industriais, esta dissertação apresenta os aspetos fundamentais do modelo implementado bem como um conjunto de experiências que o comparam com um protótipo laboratorial já existente, no âmbito da sua validação.Mestrado em Engenharia Eletrónica e Telecomunicaçõe