Workflow is a collection of tasks organized to accomplish some business process. It also defines the order of task invocation or conditions under which task must be invoked, task synchronization, and information flow. Before the execution of the workflow, a correct execution schema, in other words, the schedule of the workflow, must be determined. Workflow scheduling is finding an execution sequence of tasks that obeys the business logic of workflow. Research on specification and scheduling of workflows has concentrated on temporal and causality constraints, which specify existence and order dependencies among tasks. However, another set of constraints that specify resource allocation is also equally important. The resources in a workflow environment are agents such as person, machine, software, etc. that execute the task. Execution of a task has a cost and this may vary depending on the resources allocated in order to execute that task. Resource allocation constraints define restrictions on how to allocate resources, and scheduling under resource allocation constraints provide proper resource allocation to tasks. In this thesis, we present two approaches to specify and schedule workflows under resource allocation constraints as well as temporal and causality constraints. In the first approach, we present an architecture whose core and novel parts are a specifi- cation language with the ability to express resources and resource allocation constraints and a scheduler module that contains a constraint solver in order to find correct resource assignments. In the second approach, we developed a new logical formalism, called Concurrent Constraint Transaction Logic (CCTR) which integrates constraint logic programming (CLP) and Concurrent Transaction Logic, and a logic-based work- flow scheduler that is based on this new formalism. CCTR has the constructs to specify resource allocation constraints as well as workflows and it provides semantics for these specifications so that validity of a schedule can be checked.

Over the past few years, the Swedish Armed Forces (SAF) in similarity with forces inmany other countries has been undergoing a major process of change. One of the majorreforms is the government‘s decision to replace the compulsory military service with aprofessional army. In order to manage this, SAF requires tools to evaluate the long-termconsequences of different decisions regarding its manpower, such as different recruitment,training and educations policies, mission rehearsal, mission planning, and etc.These tools should, for instance, include information about different type of resourcessuch as weapon systems and materials required for conducting training and missions, asthey directly affect planning of courses, training sessions, etc. These resources have a totallife cycle cost that besides the acquisition cost includes maintenance costs, cost forspare parts and cost of human resources which are required for training and deploymentof the resource.This thesis has been performed in collaboration with FOI (Swedish Defence ResearchAgency) in order to support development of a decision support simulation tool for assistingin the personnel planning process of the SAF. The main objective is to determinethe connection between LCC (Life cycle cost) of personnel and LCC of system Hence,the study facilitates flow of information between the Human Resource Department atSAF and the Defence Material Administration (FMV) in order to base their decisionmaking process on more accurate and complete information about resource costs relatedto different activities that are important to both organizations.In this paper, the inductive approach is the chosen approach as appropriate theories arestudied and used for making hypothesis in order to create a new model. Consequentlythe interpretive approach is deployed as it is associated with this reasoning style. Furthermore,the research purpose is exploratory as it is essential to identify the resourcescost factors and the relations between them.The research strategy is case study and the utilized technique for collecting primary datais interview. The secondary data is gathered by studying hard or digital copy of books,articles, journals, handbooks and dictionaries.Hence, through a set of interviews, information about different activities regarding theeducation and operation phases of the fighter pilots at the Swedish Air Force has beencollected. As a result a corresponding model consisting of resources employed in thoseiiactivities and their relation has been developed. The model is based on the Unified EnterpriseCompetence Modelling Language (UECML).The contributions of this thesis are (1) Identification of the cost factors of personnelrelatedactivities including courses, training sessions and missions, 2) Classification ofcost factor elements in a number of classes, and 3) Illustrating the connections betweenthe classes using UECML.

Zugl.: Sankt Gallen, Univ., Diss., 2009

The technology push by Moore's law brings a paradigm shift in the adaption of many core systems which replace high frequency superscalar processors with many simpler ones. On the software side, in order to utilize the available computational power, applications are following the high performance parallel/multi-threading model. Thus, many-core systems raise the challenges of resource allocation and fragmentation making necessary ecient run-time resource management techniques. In this thesis, we propose SPA, a Simple Pool Architecture for managing resource allocation in many-core systems. The proposed framework follows a distributed approach in which cores are organized into clusters and multiple clusters form a pool. Clusters are created based on system's characteristics and the allocation of cores is performed in a distributed manner so as to increase resource utilization and reduce fragmentation. Specifically, SPA is responsible (i) to generate the pool-based structure and organize cores into clusters depending on the NoC architecture; (ii) to serve, at run-time, the needs of multithreaded applications, in terms or processing cores; and (iii) to allocate resources in order to take advantage of spatial features, shared resources and reduce fragmentation. Experimental results show that SPA produces on average 15% better application response time while waiting time is reduced by 45% on average compared to other state-of-art methodologies.

Cloud computing Infrastructure-as-a-Service (IaaS) has gained momentum in the cloud computing research field due to its ability to provide efficient infrastructures. Cloud Service Providers (CSPs) are striving to offer Quality of Service (QoS)-guaranteed IaaS services while also improving their resource utilization and maximizing profit. In addition, CSPs are challenged by the need to manipulate diverse and heterogeneous resources, realizing multiple objectives for both customers and CSPs, and handling scalability issues. These challenges are the motivations behind this work which aims at developing a multi-layered framework for constructing and managing efficient IaaS. The fundamental layer in this framework, the Virtual Infrastructure (VI) composition layer, is dedicated to composing and delivering VIs as an IaaS service. This framework relies on a preparatory step that is defined when all the available resources in the managed space are collected in a large repository, the Virtual Resource Pool (VRP). The VRP creation process unifies the representation of all the diverse and heterogeneous resources available. Subsequently, the proposed framework performs various resource allocation approaches as working solutions through the VI composition layer. These approaches adopt efficient techniques and methodologies in performing their operations. The working solutions are initiated by designing a composition approach that relies on an ontology-based model representation. The composition approach exploits semantic similarity, closeness centrality, and random walk techniques for efficient resource allocation. As a result, it provides an efficient solution in a reasonable computational time with no guarantee for the optimality of the obtained solutions. To achieve an optimal solution, the composition approach uses a mathematical modeling formulation. In this solution, the concepts of the composition approach have been integrated into a multi-objective Mixed Integer Linear Programming (MILP) model that has been solved optimally. Despite the optimality of the resulting solution, the MILP-based model restricts IaaS resource allocation to a computational running-time challenge, and the issue of limited-size datacenters. To circumvent these issues, a cost-efficient model is proposed. The new model introduces a Column Generation (CG) formulation for the IaaS resource allocation problem in large datacenters acquainted with QoS requirements. Furthermore, this formulation is realistic, adopts large-scale optimization tools that are adequate for large datacenters, and ensures optimal solutions in a reasonable time. However, growing costs in large datacenters in accordance with the growth of recent large-scale application demands, makes large datacenters economically inefficient. Thus, we advocate a distributed framework for IaaS provisioning that guarantees affordable, scalable, and QoS-assured infrastructure for hosting large-scale applications in geo-distributed datacenters. The framework incorporates two decentralized resource allocation approaches, hierarchical and distributed, that use efficient economic models. These approaches are quite promising solutions for the scalability and computational complexity issues of existing centralized approaches. Finally, the cost-efficient model has been extended to fit the distributed infrastructure by considering additional constraints that impact CSP revenue. Simulation results showcase the effectiveness of the presented work along with the potential benefits of the proposed solutions in terms of satisfying the customers’ requirements, while achieving a better resource utilization and CSP payoffs.

Encouraging positive work team growth depends on, in part, the form and availability of organizational resources and support. Support systems have been found to be important for work team health and survival. However, managers are challenged to make resource decisions while working within company budgetary restraints. Previous research has indicated a positive relationship exists between teams provided with appropriate resources and support, and increased team performance. This study extended previous research by exploring if team performance can predict resources and support. Specifically, the means by which managers allocate resources based on team performance was examined. Archival data included 36 work teams and their managers drawn from four geographically dispersed manufacturing companies. Information gathered from a modified version of an original team support system instrument was used to assess the importance and presence of four resource systems. Additionally, a gap score was calculated from these scores to assess the alignment between resource need and resource existence. Data was used to assess the potential relationships between managers' perceptions of team performance and the manner by which resources are allocated. All hypotheses produced non-significant findings. Results of the hypotheses, data patterns, and limitations of the study are discussed, and opportunities for future research are presented.

Problems that confront the farmer are varied, but one of the most important is the combination of his possible enterprises so that maximum financial return from farming is obtained. This problem has been made more important in the last decade by the severity of the agricultural price-cost squeeze.

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The complexity of networked systems has been continuously growing, and the abundance of online resources has presented practical management challenges. Specifically, system administrators are required to carefully configure their online systems to minimize security vulnerabilities of resource management, including resource creation, maintenance, and disposal. However, numerous networked systems have been exploited or compromised by adversaries, due to misconfiguration and mismanagement of human errors. In this dissertation, we explore different network systems to identify security vulnerabilities that adversaries could exploit for malicious purposes. First, we investigate the identity-account inconsistency threat, a new SSO vulnerability that can cause the compromise of online accounts. We demonstrate that this inconsistency in SSO authentication allows adversaries controlling a reused email address to take over online accounts without using any credentials. To substantiate our findings, we conduct a measurement study on the account management policies of various cloud email providers, highlighting the feasibility of acquiring previously used email accounts. To gain insight into email reuse in the wild, we examine commonly employed naming conventions that contribute to a significant number of potential email address collisions. To mitigate the identity-account inconsistency threat, we propose a range of useful practices for end-users, service providers, and identity providers. Secondly, we present a comprehensive study on the vulnerability of container registries to typosquatting attacks. In typosquatting attacks, adversaries intentionally upload malicious container images with identifiers similar to those of benign images, leading users to inadvertently download and execute malicious images. Our study demonstrates that typosquatting attacks can pose a significant security threat across public and private container registries, as well as across multiple platforms. To mitigate the typosquatting attacks in container registries, we propose CRYSTAL, a lightweight extension to the existing Docker command-line interface. Thirdly, we present an in-depth study on hardware resource management in cloud gaming services. Our research uncovers that adversaries can intentionally inject malicious programs or URLs into these services using game mods. To demonstrate the severity of these vulnerabilities, we conduct four proof-of-concept attacks on cloud gaming services, including crypto-mining, machine-learning model training, Command and Control, and censorship circumvention. In response to these threats, we propose several countermeasures that cloud gaming services can implement to safeguard their valuable assets from malicious exploitation. These countermeasures aim to enhance the security of cloud gaming services and mitigate the security risks associated with hardware mismanagement. Last but not least, we present a comprehensive and systematic study on NXDomain, examining its scale, origin, and security implications. By leveraging a large-scale passive DNS database, we analyze a vast dataset spanning from 2014 to 2022, identifying an astonishing 146 trillion NXDomains queried by DNS users. To gain further insights into the usage patterns and security risks associated with NXDomains, we carefully select and register 19 NXDomains in the DNS database. To analyze the behavior and sources of these queries, we deploy a honeypot for our registered domains and collect 5,925,311 queries over a period of six months. Furthermore, we conduct extensive traffic analysis on the collected data, uncovering various malicious uses of NXDomains, including botnet takeovers, malicious file injections, and exploitation of residual trust. / Doctor of Philosophy / This dissertation investigates the security risks arising from resource management in various network systems. On the one hand, we explore the security risks of software resource mismanagement, examining two specific threats: the identity-account inconsistency threat in Single Sign-On authentication schemes and the typosquatting attack in container registries. On the other hand, we investigate hardware resource misuse in network systems, focusing on two security issues: the exploitation of computing hardware in cloud gaming services and the analysis of NXDomains within the Domain Name System (DNS). By thoroughly analyzing and understanding these security risks, this dissertation contributes to the advancement of networked system security and provides necessary countermeasures to protect Internet users against these threats.