[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/197439/1207.0203v1.pdf

Internet of Things (IoT): A vision, architectural elements, and future directions

Data Mining Practical Machine Learning Tools and Techniques

http://cloud.pubs.dbs.uni-leipzig.de/sites/cloud.pubs.dbs.uni-leipzig.de/files/Brandic2008CloudcomputingandemergingITplatformsVisionhypeand.pdf

Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility

Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end-users under a usage-based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter-networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter-networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy-efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns. Copyright © 2010 John Wiley & Sons, Ltd.

https://beloglazov.info/papers/2010-cloudsim-spe.pdf

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Despite advances in vehicle technology and road modernization, traffic accidents are a huge global issue, causing deaths and injuries, especially among pedestrians and cyclists. This often happens due to pedestrians and cyclists in drivers' blind spots or distractions delaying drivers' reactions. Therefore, timely warning drivers about critical situations is important to increase traffic safety. New edge computing and communication technologies have been proposed to reduce latency in critical IoT systems. However, state-of-the-art solutions either do not focus on traffic safety or do not consider low-latency requirements in this context. We propose InTraSafEd5G (Increasing Traffic Safety with Edge and 5G) to address these issues. InTraSafEd5G performs real-time edge analytics to detect critical situations and deliver early warnings to drivers. After describing our design choices, we provide a prototype implementation and evaluate its performance in a real-world setup. The evaluation shows that InTraSafEd5G can (i) detect critical situations in real-time and (ii) notify affected drivers in 108.73ms on average using 5G, which is within expected latency requirements of road safety IoT applications. Our solution shows a promising step towards increasing overall traffic safety and supporting decision-making in critical situations.

https://dl.acm.org/doi/pdf/10.1145/3434770.3459732

Increasing Traffic Safety with Real-Time Edge Analytics and 5G

Abstract Cloud Computing represents a novel and promising approach for implementing scalable ICT systems for individual-, communities-, and business-use relying on the latest achievements of diverse research areas, such as Grid computing, Service oriented computing, business processes, and virtualization. From the technological point of view Grid computing is considered as the most related predecessor technology of Cloud computing. Although, Cloud and Grid computing differ in many aspects, as for example, in the general idea of the provision of computational resource, which is in Clouds commercial based and in Grids community based, there are many similarities. In this paper we investigate the similarities and differences between Clouds and Grids by evaluating two successful projects, namely for the provision of native hight performance copmputing applications as Grid workflows and for the self-management of Cloud infrastructures. Abstract Cloud Computing ist eine neuartige Methode für die Implementierung skalierbarer ICT Systeme, die von den Individuen, Gemeinschaften und Geschäftsprozessen benutzt wird. Cloud Computing basiert auf diversen Technologien wie z. B. Grid Computing, Serviceorientierte Architekturen, Geschäftsprozess-Management und Virtualisierung. Von dem technologischen Standpunkt wird Grid Computing als die wichtigste Vorläufertechnologie angesehen. Obwohl Grid und Cloud Infrastrukturen sich in vielen Aspekten unterscheiden, wie z. B. in der Idee wie die Computerressourcen angeboten werden — in Grid basiert dies auf der gemeinsamen Nutzung der Ressourcen in einer Gemeinschaft, in Clouds ist es kommerziell — haben beide Systeme auch sehr viele Gemeinsamkeiten. In dieser Arbeit untersuchen wir die Ähnlichkeiten und Unterschiede zwischen Grid und Cloud Systemen durch die Evaluierung von zwei erfolgreichen Projekten aus beiden Bereichen, nämlich eine Infrastruktur für die Bereitstellung der Hochleistungsapplikationen als Services für Grid und eine Cloud Infrastruktur für das Selbstmanagement der Cloud Applikationen.

Grid vs Cloud — A Technology Comparison

In Vehicular Ad-hoc NETworks (VANET) users do not necessarily trust each other and in some cases they may introduce dubios information in the network. Centralized approaches to improve the credibility of information do not easily scale, require trusting the service provider and have higher network delay. Blockchain solutions are promising in the area but they need consensus on the credibility of new information, which requires the participants solve computational puzzles in a competitive manner. To cope with vehicles' limited computational resources and mobility, we propose brokerage mechanism to decide whether to execute the validation locally, or to offload it to an edge or cloud infrastructure. We define a Satisfiability Modulo Theories (SMT) method to enable participants to decide whether to take part in the validation and whether to offload it considering the state of the infrastructure, energy efficiency, the offloading cost and the computation reward. Our method obtains 77.7% higher profit and consumes 39.2% less energy in comparison with the case where no offloading is allowed.

Energy and Profit-Aware Proof-of-Stake Offloading in Blockchain-based VANETs

Cloud computing markets face challenges, such as a large variety of different resource types in the market. A large variety of resource types results in a low number of matches of ask and bids. Consequently, the market has a low liquidity, which is economically inefficient and can lead to market failure. To counteract this problem, SLA templates (i.e., templates for electronic contracts) have been introduced. However, until now, SLA templates were static, not able to reflect changes in users requirements. In this paper, we apply the adaptive SLA mapping approach for deriving public SLA templates from private SLA templates of users. To achieve the adaptation of SLA templates, we combine clustering algorithms with adaptation methods. The result is a set of new public SLA templates, which reflect the market situation more accurately. This way, we enable marketplaces to automatically adapt to observed changes of market conditions. For the simulation-based evaluation of our approach, we formalize a utility and cost model, calculate the overall net utility, and assess the scalability of the approach. Our results show that the use of clustering algorithms can significantly improve the performance of the adaptive SLA mapping approach.

Towards autonomic market management in cloud computing infrastructures

Optimising the IT infrastructure of large, often geographically distributed, organisations goes beyond the classical virtual machine reassignment problem, for two reasons: (i) the data centres of these organisations are composed of a number of hosting departments which have different preferences on what to host and where to host it, (ii) the top-level managers in these data centres make complex decisions and need to manipulate possible solutions favouring different objectives to find the right balance. This challenge has not yet been comprehensively addressed in the literature and in this paper we demonstrate that a multi-objective VM reassignment is feasible for large decentralised data centres. We show on a realistic data set that our solution outperforms other classical multi-objective algorithms for VM reassignment in terms of quantity of solutions (by about 15% on average) and quality of the solutions set (by over 6% on average).

/pdf/towards-a-multi-objective-vm-reassignment-for-large-14719uutct.pdf

Ivona Brandic

Papers

Increasing Traffic Safety with Real-Time Edge Analytics and 5G

Grid vs Cloud — A Technology Comparison

Energy and Profit-Aware Proof-of-Stake Offloading in Blockchain-based VANETs

Towards autonomic market management in cloud computing infrastructures

Towards a multi-objective VM reassignment for large decentralised data centres