An optimized capacity planning approach for virtual infrastructure exhibiting stochastic workload

Algorithmic metatheorems state that if a problem can be described in a certain logic and the inputs are structured in a certain way, then the problem can be solved with a certain amount of resources. As an example, by Courcelle’s Theorem, all monadic second-order (“in a certain logic”) properties of graphs of bounded tree width (“structured in a certain way”) can be solved in linear time (“with a certain amount of resources”). Such theorems have become valuable tools in algorithmics: if a problem happens to have the right structure and can be described in the right logic, they immediately yield a (typically tight) upper bound on the time complexity of the problem. Perhaps even more importantly, several complex algorithms rely on algorithmic metatheorems internally to solve subproblems, which considerably broadens the range of applications of these theorems. This paper is intended as a gentle introduction to the ideas behind algorithmic metatheorems, especially behind some recent results concerning space and circuit classes, and tries to give a flavor of the range of their applications.

In distributed manufacturing systems, manufacturing resource composition is one of the most important problems. This is because efficiency of resource selection and resource utilization can all be improved if it is tackled well. However, most of the existing methods neglect temporal relationship between resources. This leads to an inefficient use of resources, because all resources have to be kept available before a business process is started. A temporal composition of resources is more suitable, as it expresses the scheduling and the flow of servicing to a business process. Therefore, resource services invoked in sequential order are called the resource-service chain (RSC), in view that distributed resources are encapsulated into cloud services in a cloud manufacturing (CMfg) environment. We propose an approach, called RSC composition algorithm (RSCCA) that can better cope with the temporal relationship between the resource services in a business process. Specifically, a two-stage composition method based on the degrees of dependency between resource services in workflow is proposed. To begin, in the build-time stage algorithm, RSCCA resolves initial compositions based on task relatedness and temporal dependencies between resource services, and then calculates the usage frequencies of ICs by mining workflow log at workflow runtime stage. Based on this, RSCCA can compose individual resource services as more than sets, especially as chains, allowing flow directions and dynamics to be considered. RSCCA has been tested with different data sets and the results show that it can be very promising.

The development of the information sphere and the corresponding increase in its volume and cost is accompanied by the introduction of advanced information technologies in all spheres of public life of the state, which leads to an increase in the frequency of attacks and potential losses from information leakage. As a result, the complexity of protection systems and an increase in their cost. In these conditions, the task to efficiently distribute limited financial resources to protect the information of business entities becomes more and more important and largely determines the level of financial and economic security of the enterprise and the state as a whole. Of particular relevance is the development of issues of optimisation of indicators of the information security system in a dynamic confrontation. Such indicators can be the amount of damage caused from the implementation of information threats, which determines the effectiveness of the protection system, the profit from making investments in information protection, their profitability, and the like. It was established that it is necessary to determine the total amount of protection resources, which minimises the total losses from possible information leakage in conditions of instability. The authors believe that the optimal control mechanism is the distribution of resources between objects that contain a different share of information and are distinguished by natural security, dynamic vulnerability, and the probability of an attack with the allocation of a certain amount of resources. The practical significance of the study lies in determining the optimal moment for the introduction of defence resources – after the direction and intensity of attacks and, accordingly, the possible level of losses was clarified.

Capacity planning for IaaS cloud providers offering multiple service classes

Fast multi-resource allocation with patterns in large scale cloud data center

Sharding technology has been recognized to be a promising solution for blockchain scalability problems in recent years. For safety guarantees in each shard, mainly to prevent the single-shard takeover attack, sharding requires an identity establishment protocol in which participants have to pay a certain amount of resources (i.e., ticket price) to get a node and participate in the network. However, state-of-the-art sharding protocols overlook a non-democratic state of the real-world where every participant has a different amount of resources, termed a non-democratic environment. This oversight raises combined problems of security and scalability due to the design of the identity establishment protocol.In this paper, we examine the effects of the non-democracy of blockchain networks in terms of the security and scalability of blockchain sharding and suggest formulae to quantitatively analyze the trade-off between security and scalability. Moreover, we conduct a numerical analysis by capturing four real-world resource distributions from renowned permissionless cryptocurrency networks. We re-evaluate the well-known sharding protocols through this numerical analysis and present the changed fault tolerance bounds and damage to scalability. The results show that the ticket price plays a leading role in tuning the effect of non-democracy. The main contribution of this paper is the proposal of new metrics for accessing the degree of security and scalability with regard to the ticket price in the identity establishment phase. Our discussion suggests further research on a more delicate ticket price control algorithm when designing a new sharding model for blockchain.KeywordsBlockchain shardingScalabilitySecurity

Cloud service level agreement negotiation is a process of joint decision-making between cloud clients and providers to resolve their conflicting objectives. With the advances of cloud technology, operations such as discovery, scaling, monitoring and decommissioning are accomplished automatically. Therefore,negotiationbetweencloudclientsandproviderscanbeabottleneckifitiscarriedoutmanually. Our objective is to propose a state-of-the-art solution to automate the negotiation process for cloud environments and specifically infrastructure as a service category. The proposed negotiation strategy is based on a time-dependent tactic. For cloud providers, the strategy uniquely considers utilization of resources when generating new offers and automatically adjusts the tactic’s parameters to concedemoreonthepriceoflessutilizedresources.Inaddition,whilethepreviousnegotiationstrategiesinliteraturetrustofferedqualityofservicevaluesregardlessoftheirdependability,ourproposed strategy is capable of assessing reliability of offers received from cloud providers. Furthermore, to find the right configuration of the time-dependent tactic in cloud computing environments, we investigate the effect of modifying parameters such as initial offer value and deadline on negotiation outputsthatincluderatioofdealsmade,andinequalityindex.Theproposednegotiationstrategyistested with different workloads and in diverse market conditions to show how the time-dependent tactic’s settings can dynamically adapt to help cloud providers increase their profits.

Comparison of impedance cardiography with thermodilution and direct fick methods for noninvasive measurement of stroke volume and cardiac output during incremental exercise in patients with ischemic cardiomyopathy

Capacity planning for large‐scale systems like mainframe installations is typically based on rather coarse historical workload data. Hence, it is advisable to employ techniques and tools that use the same “macroscopic” (high‐level) view of the overall system. We follow the classic approach known from performance modelling to compose a model essentially out of two parts, the system model (or machine) and the workload model. The system model is an aggregated mainframe system model that is focussed primarily on processing resources that are given by processors of different types (i.e. general all purpose processors and processors dedicated to Java, Linux, Database and others) and their processing capacity given by scaling tables. The workload model follows the structuring given by logical partitions and is built from historical utilization data that are permanently collected during normal operation. Based on this framework it is possible to define and improve the allocation of logical partitions to processors or processor pools. Employing the CapSys tool the designer can interactively vary the configuration of processor pools as well as the shape and intensity of the workloads to be allocated. In this report we describe background, architecture and functionality of the CapSys tool.

In this study, we made a simple, low-cost algorithm for tracking eye movements and eye blinks in real-time and non-real-time. Several methods are being used right now. Show parts of the face, like the eyes or the whole face. For this reason, open-source libraries like OpenCV enable high-level programming to implement reliable and accurate detection algorithms like Haar Cascade. Since everything is processed in real-time, payment must be made quickly. Pay attention to how hardware, like a computer, can only use a certain amount of resources (processing power). The system has been proven to work by tests with 15 people of different ages and backgrounds. These tests are done to see how the user and the device work together and ensure everything works correctly. The In the tests done, the system worked between 80% and 100% of the time. The results showed that Haar Cascade had a significant effect by Detection of faces in 100% of cases, while the eyes and pupil where they overlap (light and shade) is less effective. In addition to looking at how well the Through these activities, the demo application also showed that user restrictions shouldn't stop people from enjoying and using a certain type of technology. The program was written in C++, and the OpenCV library makes it work on Windows. This system has many uses in the real world and science. By looking at the data from this algorithm from afar, for example, it can tell if someone has an eye disease or is tired. It can also help people who have physical or mental problems

Shared resource pools are facilities featuring a certain amount of resources which can be used by different applications. For managing resources in such pools, the demand of each application can be used. Such a demand, however, is driven by the workload, which varies over time. For that reason, adaptive approaches have been proposed for the management of shared resources pools. Whereas a number of solutions exist in this context, they are either not truly decentralized or do not apply to the problem we are dealing with. In this paper, we then present Darma, an approach for managing shared resource pools in a truly decentralized, adaptive, and optimal way.

Big but also small and medium-sized enterprises (SMEs) are driven by the idea of entering foreign markets. Globalisation plays an important role for many companies. Based on its size and its financial strength, each company has access to a certain amount of resources. SMEs have limited resources. This disadvantage influences, inter alia, internationalisation strategy and process of SMEs. Social capital can compensate disadvantages, and plays a significant role for SMEs and their strategy. This study focuses on the whole internationalisation to clarify the influence of social capital including the generation and use of knowledge and experience for further market entries. Theoretical fundamentals are network and social capital theory, and multiple case-study method. These approaches help to explore the influence of social capital on the internationalisation process and strategy. The results of this study present the significance of social capital for the internationalisation and the limited awareness of SMEs' network resources.

In this paper, we utilize the framework of compressed sensing (CS) for device detection and distributed resource allocation in large-scale machine-to-machine (M2M) communication networks. The devices are partitioned into clusters according to some pre-defined criteria, e.g., proximity or service type. Moreover, by the sparse nature of the event occurrence in M2M communications, the activation pattern of the M2M devices can be formulated as a particular block sparse signal with additional in-block structure in CS based applications. This paper introduces a novel scheme for distributed resource allocation to the M2M devices based on block-CS related techniques, which mainly consists of three phases: (1) In a full-duplex acquisition phase, the network activation pattern is collected in a distributed manner. (2) The base station detects the active clusters and the number of active devices in each cluster, and then assigns a certain amount of resources accordingly. (3) Each active device detects the order of its index among all the active devices in the cluster and accesses the corresponding resource for transmission. The proposed scheme can efficiently reduce the acquisition time with much less computation complexity compared with standard CS algorithms. Finally, extensive simulations confirm the robustness of the proposed scheme under noisy conditions.

The earlier parts of this book suggest the areas which require empirical illumination. Chapter 1 presented a general model of technological choice: each technique is associated with a vector of characteristics; the set of techniques available depends on the historical development of technology, and specifically the economic/social conditions of the economy for which the techniques were originally developed; each decision maker has certain objectives, a certain amount of knowledge about the technological possibilities, faces certain restraints, and controls a certain amount of resources. The actual choice made then depends on the interaction between decision makers and technological possibilities, given the various objectives and restraints. Ideally, empirical studies should try and illuminate this complex process — revealing for example how the historical development of the industry affects the technology available; whether and how one set of decision makers, e.g. multinational firms, make a different choice from another, e.g. local publicly owned firms; and why — e.g. because objectives differ, or because access to resources differ, or because markets differ. Chapter 4 presented a more specific empirical question: that is, the question of the existence and relative efficiency of an appropriate technology, and the sort of socio-economic changes that would be needed to get such a technology — if it exists — into use. This question is in a way a sub-question of the general model of technological choice in Chapter 1.KeywordsInvestment CostCapacity UtilisationLocal FirmTechnological ChoiceSurplus GenerationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Spectrum-efficient mode selection and fair resource allocation for D2D-enabled uplink/downlink MC-NOMA networks