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

Multi-attribute demand characterization and layered service pricing

As cloud computing gains popularity, understanding the pattern and structure of its workload is increasingly important in order to drive effective resource allocation and pricing decisions. In the cloud model, virtual machines (VMs), each consisting of a bundle of computing resources, are presented to users for purchase. Thus, the cloud context requires multi-attribute models of demand. While most of the available studies have focused on one specific attribute of a virtual request such as CPU or memory, to the best of our knowledge there is no work on the joint distribution of resource usage. In the first part of this dissertation, we develop a joint distribution model that captures the relationship among multiple resources by fitting the marginal distribution of each resource type as well as the non-linear structure of their correlation via a copula distribution. We validate our models using a public data set of Google data center usage. Constructing the demand model is essential for provisioning revenue-optimal configuration for VMs or quality of service (QoS) offered by a provider. In the second part of the dissertation, we turn to the service pricing problem in a multi-provider setting: given service configurations (qualities) offered by different providers, choose a proper price for each offered service to undercut competitors and attract customers. With the rise of layered service-oriented architectures there is a need for more advanced solutions that manage the interactions among service providers at multiple levels. Brokers, as the intermediaries between customers and lower-level providers, play a key role in improving the efficiency of service-oriented structures by matching the demands of customers to the services of providers. We analyze a layered market in which service brokers and service providers compete in a Bertrand game at different levels in an oligopoly market while they offer different QoS. We examine the interaction among players and the effect of price competition on their market shares. We also study the market with partial cooperation, where a subset of players optimizes their total revenue instead of maximizing their own profit independently. We analyze the impact of this cooperation on the market and customers' social welfare

Automated Trading Systems VS Manual Trading in Forex Exchange Market

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and ManagementIn the recent decades, automated trading has been widely used in Forex and Money Markets, as well as in financial markets. This auto trading provided substantial benefits to transaction efficiency. Many trading robots have been created to substitute humans, capable of simulating trading strategies and continuously making profits. Nevertheless, programs cannot reproduce all human behaviour and most robots are over-sensitive, therefore, it is difficult to have the same results as human traders. The study focuses on evaluating the trading machines sensitivity and effectiveness. The economic markets can benefit from the machine in several ways, through continuous operation, increasing diversification, short/term trading opportunities and by forecasting opportunities e. g. currency price changes. The further investigation indicates that the majority of forex trading robots are profitable, in fact, there is a great tendency for curve-fitting or data-mining. There are some impressive robots out there; of course, these systems maintain an advantage and successfully manage risk. The best ones are more about position sizing and cutting losses quickly and less about high win rates. The greater the sensitivity the greater the trading opportunities, but this decreases the performance. This research will contain interviews with experts that will validate the study

Toward Customizable Multi-tenant SaaS Applications

abstract: Nowadays, Computing is so pervasive that it has become indeed the 5th utility (after water, electricity, gas, telephony) as Leonard Kleinrock once envisioned. Evolved from utility computing, cloud computing has emerged as a computing infrastructure that enables rapid delivery of computing resources as a utility in a dynamically scalable, virtualized manner. However, the current industrial cloud computing implementations promote segregation among different cloud providers, which leads to user lockdown because of prohibitive migration cost. On the other hand, Service-Orented Computing (SOC) including service-oriented architecture (SOA) and Web Services (WS) promote standardization and openness with its enabling standards and communication protocols. This thesis proposes a Service-Oriented Cloud Computing Architecture by combining the best attributes of the two paradigms to promote an open, interoperable environment for cloud computing development. Mutil-tenancy SaaS applicantions built on top of SOCCA have more flexibility and are not locked down by a certain platform. Tenants residing on a multi-tenant application appear to be the sole owner of the application and not aware of the existence of others. A multi-tenant SaaS application accommodates each tenant’s unique requirements by allowing tenant-level customization. A complex SaaS application that supports hundreds, even thousands of tenants could have hundreds of customization points with each of them providing multiple options, and this could result in a huge number of ways to customize the application. This dissertation also proposes innovative customization approaches, which studies similar tenants’ customization choices and each individual users behaviors, then provides guided semi-automated customization process for the future tenants. A semi-automated customization process could enable tenants to quickly implement the customization that best suits their business needs.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Algorithms for bundling and pricing trucking services: Deterministic and stochastic approaches

Bundling and pricing trucking services is an important strategic decision for carriers. This is helpful when they consider the incorporation of new businesses to their networks, look for economic and optimal operations, and develop revenue management strategies. Reverse combinatorial auctions for trucking services are real-world examples that illustrate the necessity of such strategies. In these auctions, a shipper asks carriers for quotes to serve combinations of lanes and the carriers have to bundle demand and price it properly. This dissertation explores several dimensions of the problem employing state-of-the-art analytical tools. These dimensions include: Truckload (TL) and less-than-truckload (LTL) operations, behavioral attributes driving the selection of trucking services, and consideration of deterministic and stochastic demand. Analytical tools include: advanced econometrics, network modeling, statistical network analysis, combinatorial optimization, and stochastic optimization. The dissertation is organized as follows. Chapter 1 introduces the problem and related concepts. Chapter 2 studies the attributes driving the selection of trucking services and proposes an econometric model to quantify the shipper willingness to pay using data from a discrete choice experiment. Chapter 3 proposes an algorithm for demand clustering in freight logistics networks using historical data from TL carriers. Chapter 4 develops an algorithmic approach for pricing and demand segmentation of bundles in TL combinatorial auctions. Chapter 5 expands the latter framework to consider stochastic demand. Chapter 6 uses an analytical approach to demonstrate the benefits of in-vehicle consolidation for LTL carriers. Finally, Chapter 7 proposes an algorithm for pricing and demand segmentation of bundles in LTL combinatorial auctions that accounts for stochastic demand. This research provides meaningful negotiation guidance for shippers and carriers, which is supported by quantitative methods. Likewise, numerical experiments demonstrate the benefits and efficiencies of the proposed algorithms, which are transportation modeling contributions

Supporting SLA Provisioning in Grids by Risk Management Processes

Gridtechnologien haben heutzutage einen hohen Entwicklungsstand erreicht, aber für die Etablierung eines kommerziellen Grids ist es erforderlich, Defizite in den Bereichen Sicherheit, Vertrauenswürdigkeit und Verlässlichkeit zu beheben. Anwender fordern eine Ausführung ihrer Applikation (Grid Jobs) gemäß einer gewünschten Priorität und Qualität. Um vertraglich derartige Aspekte einzufordern, können Service Level Agreements (SLAs) zwischen Dienstbenutzern und Dienstanbietern verhandelt werden. Dienstanbieter kennen jedoch die Unzuverlässigkeit von Grid Ressourcen und sind daher vorsichtig, strenge Forderungen zu akzeptieren und entsprechende Qualitäten zu garantieren. Können strenge Forderungen jedoch nicht vertraglich vereinbart werden, so bevorzugen es viele Anwender, eigene Rechenressourcen zu verwenden. Zwar ist die Unterhaltung eigener Ressourcen in vielen Fällen teurer, aber sie haben die Kontrolle über ihre Applikation, was ihnen mehr Sicherheit bietet. Für die Etablierung eines kommerziellen Grids ist es daher unerlässlich, dass Grid Provider auch strenge SLAs akzeptieren. Damit Provider strenge SLAs akzeptieren können, benötigen sie Abschätzungen dafür, dass sie die SLA nicht erfüllen können (Risikoberechnung). Des Weiteren sollten solche Abschätzungen als Entscheidungskriterium bei der Ressourcenallokation oder Initiierung von Fehlertoleranzmaßnahmen fungieren (Risikomanagement). Diese Arbeit integriert die Betrachtung von Risiken in die Abläufe des Providers, die in die Erbringung von SLAs involviert sind. Während der SLA Verhandlung wird evaluiert welche Ressourcen für die Diensterbringung verwendet werden. Basierend darauf wird die Fehlerwahrscheinlichkeit dieser Ressourcen und der SLA Erbringung im Gesamten berechnet. Falls die mögliche Fehlerwahrscheinlichkeit zu hoch ist, können risikoreduzierende Maßnahmen durchgeführt werden, so dass die SLA akzeptiert werden kann. Die berechnete Fehlerwahrscheinlichkeit wird von Provider und Benutzer ebenfalls bei der Bestimmung des Preises und der Konventionalstrafe betrachtet. Nach dem Vertragsabschluss ist es für die Vermeidung von SLA Verletzungen aus Grid Provider Sicht essentiell, Ressourcenausfälle kompensieren zu können. Die Verwendung von Fehlertoleranzmaßnahmen in Zusammenhang mit einer Risikobetrachtung unterstützt Grid Provider bei der Bewältigung dieser Aufgabe. Risikomanagementprozesse werden dabei direkt mit dem Ressourcenmanagement verknüpft und sind nicht sichtbar für Anwender. Ein wichtiger Aspekt des entwickelten Risikomanagements sind selbstorganisierende Mechanismen, die eine Fehlertoleranzmaßnahme oder eine Kette solcher initiieren, um auf Instabilitäten oder Ausfälle von Ressourcen zu reagieren. Für kommerzielle Grid Provider ist die Betrachtung finanzieller Aspekte im Ressourcenbetrieb und in der Diensterbringung stets von hoher Bedeutung. Folglich werden alle Entscheidungen unter Berücksichtigung finanzieller Aspekte getroffen, wie zum Beispiel der Gewinnmarge, den Kosten für eine Fehlertoleranzmaßnahme sowie dem erwarteten Profit für eine Jobausführung. Zusammengefasst gilt die Integration von Risikomanagement in die Abläufe eines Grid Providers als initialer Schritt für ein risikobetrachtendes Grid. Es wird die Transparenz, Zuverlässigkeit und Vertrauenswürdigkeit steigern und dient als objektives Kriterium für Entscheidungsprozesse im Ressourcenmanagement. Ein integriertes Risikomanagement bringt enorme Vorteile sowohl während der SLA Verhandlung als auch nach Vertragsabschluss - und damit insgesamt für die Diensterbringung im Rahmen von SLAs.Grid technologies have reached a high level of development, however core shortcomings have been identified relating to security, trust, and dependability of the Grid which reduce its appeal to potential commercial adopters. Users require a job execution with a desired priority and quality. In order to stipulate such requirements, Service Level Agreements (SLA) can be negotiated. These are a powerful instrument enabling the specification of the business relationships between service providers and service users in detail. However, providers are aware of various threats for SLA violations and are reluctant to adopt a mechanism which requires them to meet strict requirements and to guarantee associated quality constraints. If strict guarantees cannot be agreed by contract, many users prefer to operate their own resources instead of using the Grid. This is more expensive but they control their applications, which removes the issues of trust and ensures dependability concerning its successful completion. To establish a commercial Grid environment, it is essential that Grid providers are prepared to accept an approach involving SLAs with associated guarantees. In order to enable providers to accept such SLAs, they need estimates of the likelihood that they are unable to fulfill an SLA, i. e. Risk Assessment. Furthermore the resource management should take into account such estimations when allocating resources or initiating fault-tolerance mechanisms, i. e. Risk Management. This work integrates risk awareness in the provider’s processes which are involved in SLA provisioning: During SLA negotiation they evaluate which resources can be used for service provisioning and estimate the Probability of Failure (PoF) of resources and of fulfilling the SLA. If the estimated PoF is too high, then, by applying risk reduction mechanisms, the provider may be able to reduce it sufficiently to accept the SLA. The estimated PoF will also be considered by the service provider and service consumer when determining the revenue and the contractual penalty. Compared to a service request requiring a relatively low quality of service, providing a more reliable service requires to receive a higher price since more guarantees have to be ensured. If a more reliable service is provided, the consumer might also define a higher contractual penalty. Thus, the PoF is an additional decision making element in the SLA negotiation since it enables end-users to compare different SLA offers by an objective measurement. When providers have accepted an SLA, they have to be able to compensate for resource failures in order to prevent SLA violations. The usage of fault-tolerance mechanisms combined with risk awareness support Grid providers in this task. The Risk Management processes are interlaced with the resource management and thereby transparent for Grid service consumers. An important aspect of the Risk Management developed for the Grid are self-organising mechanisms, which initiate a fault-tolerance action or a chain of them, in order to manage resource instabilities or resource outages. Decisions are made on the basis of financial considerations, such as the profit margin, the cost for performing fault-tolerance, and the expected profit when executing a job. Taking into account such financial factors is of high importance for commercial Grid providers. In conclusion, the integration of Risk Management in the processes of Grid providers is the initial step towards a risk aware Grid. It will increase transparency, reliability, and trust and provides an objective basis for decision processes in the resource management. Risk Management is integrated to address the SLA negotiation as well as the post-negotiation phase and thereby improves the SLA provisioning process in general

Agile Market Engineering: Bridging the gap between business concepts and running markets

The agile market engineering process model (AMEP) is built on the insight, that market design and development is a wicked problem. Electronic markets are too complex to be completely designed upfront. Instead, AMEP tries to bridge the gap between theoretic market design and practical electronic market platform development using an agile, iterative approach that relies on early customer feedback and continuous improvement. The AMEP model is complemented by several supporting software artifacts