Adaptive Management of Shared Resource Pools with Decentralized Optimization and Epidemics

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.

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.

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

Traditionally, any capacity planning problem is modeled with deterministic workloads by considering the peak workload for resource allocation. In the context of businesses using cloud service, cloud provider could allocate resources for peak workload which could lead to under utilization of resource and charging users for unused yet provisioned resources. Hence we came up with a better capacity planning algorithm which could ensure that we plan for peak usage but do not provision for it.In our approach, we modeled the problem as a stochastic optimization problem with the objective of minimizing the number of servers considering two important constraints a) stochastic nature of workloads and b) minimizing the application SLA violations. We implemented the model using genetic algorithm and to address the stochastic nature of work loads, we reserved a free pool of resources in each server by the quantity determined by our algorithm. We evaluated the solution with real sever utilization data from a datacenter seeking consolidation. We did comparative analysis on the number of servers required suggested by our solution vs. peak work loads based solutions for various service levels. Our results illustrate that reserving certain amount of resources in servers for addressing variability of workloads gives better results in terms of lesser number of servers compared to packing resources based on peak workloads for the same service levels.

Episodic gene expression, with periods of high expression separated by periods of no expression, is a pervasive biological phenomenon. This bursty pattern of expression draws from a finite reservoir of expression machinery in a highly time variant way, i.e., requiring no resources most of the time but drawing heavily on them during short intense bursts, that intimately links expression bursting and resource sharing. Yet, most recent investigations have focused on specific molecular mechanisms intrinsic to the bursty behavior of individual genes, while little is known about the interplay between resource sharing and global expression bursting behavior. Here, we confine Escherichia coli cell extract in both cell-sized microfluidic chambers and lipid-based vesicles to explore how resource sharing influences expression bursting. Interestingly, expression burst size, but not burst frequency, is highly sensitive to the size of the shared transcription and translation resource pools. The intriguing implication of these results is that expression bursts are more readily amplified than initiated, suggesting that burst formation occurs through positive feedback or cooperativity. When extrapolated to prokaryotic cells, these results suggest that large translational bursts may be correlated with large transcriptional bursts. This correlation is supported by recently reported transcription and translation bursting studies in E. coli. The results reported here demonstrate a strong intimate link between global expression burst patterns and resource sharing, and they suggest that bursting plays an important role in optimizing the use of limited, shared expression resources.

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

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

We study the problem of scheduling VMs (Virtual Machines) in a distributed server platform, motivated by cloud computing applications. The VMs arrive dynamically over time to the system, and require a certain amount of resources (e.g. memory, CPU, etc) for the duration of their service. To avoid costly preemptions, we consider non-preemptive scheduling: Each VM has to be assigned to a server which has enough residual capacity to accommodate it, and once a VM is assigned to a server, its service cannot be disrupted (preempted). Prior approaches to this problem either have high complexity, require synchronization among the servers, or yield queue sizes/delays which are excessively large. We propose a non-preemptive scheduling algorithm that resolves these issues. In general, given an approximation algorithm to Knapsack with approximation ratio r , our scheduling algorithm can provide rβ fraction of the throughput region for β

The article is devoted to the contribution of the prominent Italian economist Vilfredo Pareto to the theory of public welfare. The main theoretical achievements of the economist regarding the definition and measurement of public welfare are highlighted. Vilfredo Pareto rejected the principle of quantitative utility and developed his own concept of welfare maximization through the theory of such an optimal distribution of resources, including goods, in which any redistribution of them will not lead to an increase in the utility of an individual without a decrease in utility for other individuals. Giving decisive importance to the effective distribution of resources as opposed to their endless maximization, V. Pareto noted for the first time in the many years of development of economic thought that the sources of social well-being cannot be considered solely enrichment with material goods, since the possibility of their effective redistribution on the basis of humanity and high moral and ethical values. That is, for the first time in the theory of well-being, the level of human development of society, its moral values, and the weight of ethical and humanistic principles become important. These approaches make it possible to determine a relative criterion for the efficiency (optimality) of the functioning of the economic system, which specifies the state of optimality according to the following principle: it is the achievement of such a state when no one can improve their situation without getting worse. The importance of determining the optimum from the point of view of production is indicated. At the same time, we are talking about the structure of production with a certain amount of resources and technical support, which, according to his approach, becomes optimal when it is impossible to increase the production of one product without simultaneously reducing production. Such an optimal situation occurs when the marginal productivity of production factors is the same in all variants of their application. An analysis was made of provisions where the growth of social welfare does not concern the volume of production or resources, but the consumption of materials and the creation of aggregate social demand. Since, according to the terminology, gross output and gross income of the country are one and the same (the estimate of production volumes is equal to the sum of payments to the owners of input resources), the "Pareto Optimum" is the maximum production (or income) of the economy and is the most effective operational indicator. From the perspective of political decision-making, the idea of the "Pareto optimum" leads to the following Pareto criterion for the formulation of political goals: a change in social policy is justified if, as a result of such a change, all members of society will be better off, or if the improvement will affect some of its members and the condition of all others will not deteriorate. This distribution of goods in an economy is otherwise efficient when they cannot be redistributed to improve the position of one member of society without simultaneously worsening the position of another member of society. Based on this, the quality of life should become a consolidating idea in Ukraine, which will enable the nation to build its own path of development, in which ensuring the conditions for the successful realization of the individual will become the main way for evaluating the effectiveness of economic reforms

Even if CU jealously envies the public data auditing task of stored data to a trustworthy third-party auditor to prevent communication costs as well as computing costs after data outsourcing. Practically speaking, neither TPA nor CSP can be trusted. Data may be deleted by CSPs in order to clear up storage space for financial gain or in order to protect their own reputation among cloud consumers by fabricating data loss instances. Since they do not have physical control over the outsourced data, cloud users are unable to identify the person claiming responsibility for unlawful data treatment. Internal security risks and risks to shared cloud storage still exist. On the other hand, TPA errs on occasion and acts deliberately or is the victim of other illegal activities. As a result, either the audit message might be spoofed or TPA could create a misleading audit message without performing any data verification work, in which case CSP would be up against it. In this study, we provide an innovative acknowledgment verification scheme for cloud storage services to resolve these challenging issues.

As a convenient, on-demand access service model for network based, configurable shared calculation resource pool, cloud computing has many advantages. At the same time, there are many challenges in the development and application of cloud computing, especially in cloud security. For quantification demand of cloud security services, drawing on cloud computing risk control security assess framework related to the international organizations, based on China's classification protection assessment requirements, the cloud computing security evaluation index system is built using of Delphi method, and the weight of each index entry is calculated using the AHP(Analytic Hierarchy Process). The cloud security assessment model has been validated through examples, and the results show that the proposed model can make quantitative assessment on secure cloud platform effectively, with much more efficiency.

Resource provisioning in scalable cloud using bio-inspired artificial neural network model