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The theory of agents and multiagent systems can provide a new model for managing Cloud Computing systems based on the distribution of responsibilities, flexibility and autonomy. Managing the functions of the nucleus of a CC system through an agent-based model allows the resulting platforms to be much more efficient, scalable and adaptable than they...
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... Virtualization is a foundational technology in cloud computing, enabling the creation of virtual instances of computing resources on physical hardware [3,4]. This abstraction offers several key benefits [5,6], including resource optimization by running multiple VMs or containers on one server, isolation for enhanced security and stability, dynamic resource allocation for scalability, and high portability, allowing for easy movement of virtualized Extended author information available on the last page of the article environments between servers and cloud providers. Through Virtualization, cloud providers can ensure the Quality of Service (QoS) of their services that ensure performance and reliability meet user expectations [7]. ...
With the growing adoption of cloud computing in both public and private sector enterprises, the industry has experienced rapid expansion. To fully unlock the potential of cloud computing, efficient task scheduling becomes crucial. In cloud computing, task scheduling involves optimizing the allocation of tasks to a diverse range of resources, such as virtual machines, with the goals of reducing makespan, maximizing resource utilization, and minimizing response times. This challenge becomes even more pronounced for large-scale tasks due to the NP-hard nature of the problem. Consequently, the integration of metaheuristic algorithms into task scheduling has emerged as a solution to equitably distribute complex and diverse tasks across limited resources within acceptable timeframes. To enhance the quality of cloud computing services, this research introduces the modified white shark optimizer (mWSO) as an alternative task scheduling technique. The improved variant mWSO boosts the performance of the original WSO by introducing the following three enhancement steps: (1) introduce memory-based WSO to boost the exploitation phase, (2) propose an exploration-exploitation balance phase to enhance the exploration phase, and (3) introduce a control randomization parameter to balance exploration and exploitation properly. The mWSO is subjected to testing on both the global optimization problems from CEC2020 and cloud task scheduling problems. The experimental results of mWSO demonstrate high performance for CEC2020 competition benchmarks compared to other state-of-the-art and recent metaheuristic algorithms. In the case of the task scheduling problem, the mWSO achieved − 0.01 to 13.53% and 0.62–10.42% makespan and energy consumption reduction, respectively, for CEA-Curie workloads. For HPC2N workloads, mWSO achieved 7.27–29.53% makespan reduction and 3.52–26.08% energy savings over the compared metaheuristics. The statistical validity of the performance is also verified using Wilcoxon’s rank-sum test. The experimental results and comparison analysis reveal the consistent and better performance of the proposed mWSO to solve optimization problems.
... The rapid growth of cloud computing occurred for several reasons, such as large companies' economic interest, cloud paradigm maturity, and positive public response [1]. Firstly, large technology companies, as Amazon, Google, and Microsoft, are widely interested in the economic aspects of the cloud paradigm, employing successful business models based on customers' cloud resources usage (pay-per-use). ...
... The system execution was in a private cloud platform, a non-provider-independent approach. 1 The authors do not present the prediction model to provide cloud resources. The agent reasoning model is based on CBR demanding previous experiences (i.e., cases to happen in the environment) to produce better results in each resource allocation. ...
Nowadays, scientific and commercial applications are often deployed to cloud environments requiring multiple resource types. This scenario increases the necessity for efficient resource management. However, efficient resource management remains challenging due to the complex nature of modern cloud-distributed systems since resources involve different characteristics, technologies, and financial costs. Thus, optimized cloud resource management to support the heterogeneous nature of applications balancing cost, time, and waste remains a challenge. Multi-agent technologies can offer noticeable improvements for resource management, with intelligent agents deciding on Virtual Machine (VM) resources. This article proposes MAS-Cloud+, a novel agent-based architecture for predicting, provisioning, and monitoring optimized cloud computing resources. MAS-Cloud+ implements agents with three reasoning models including heuristic, formal optimization, and metaheuristic. MAS-Cloud+ instantiates VMs considering Service Level Agreement (SLA) on cloud platforms, prioritizing user needs considering time, cost, and waste of resources providing appropriate selection for evaluated workloads. To validate MAS-Cloud+, we use a DNA sequence comparison application subjected to different workload sizes and a comparative study with state-of-the-art work with Apache Spark benchmark applications executed on the AWS EC2. Our results show that to execute the sequence comparison application, the best performance was obtained by the optimization model, whereas the heuristic model presented the best cost. By providing the choice among multiple reasoning models, our results show that MAS-Cloud+ could provide a more cost-effective selection of the instances reducing
aprox 58% of execution average cost of WordCount, Sort, and PageRank BigDataBench benchmarking workloads. As for the execution time, the WordCount and PageRank present reduction, the latter with aprox 58%. The results indicate a promising solution for efficient cloud resource management.
... Throughout the manufacturing life cycle, services contain Argumentation as a Service (AaaS), Design as a Service (DaaS), Fabrication as a Service (FaaS), Experiment as a Service (EaaS), Simulation as s Service (SaaS), Management as a Service (MaaS), and Integration as a Service (InaaS) (Tao et al. 2012a, b). In CMfg, cloud services include not only software services such as simulation, testing and data but also hardware services such as machine tools, sensors and chips (Prieta et al. 2016). All these studies have made the connotation of "services" in CMfg more profound and comprehensive. ...
To improve the accuracy of service modelling and optimal selection in cloud manufacturing (CMfg), a multi-level modelling methodology is proposed to describe manufacturing services. In this methodology, manufacturing services are divided into three levels: resource, functional and process services. Based on time, cost and reputation analysis of these three service levels, the corresponding objective functions and services composition constraints are established. Considering intelligent optimal selection, a niching behaviour-based gravitational search algorithm (NGSA) is designed to address manufacturing service composition and optimal selection (MSCOS) problems. In NGSA, the niche crowding factor and fitness sharing technology are introduced to the standard gravitational search algorithm (GSA) to improve its convergence speed and accuracy. The results of a simulation experiment demonstrate that the proposed algorithm can find better solutions in less time than previous algorithms, such as the adaptive genetic algorithm (AGA) and the modified particle swarm optimization (MPSO) algorithm.
... Cloud computing is an approach to distributed computing for dynamically provisioning of virtualized resources and services provided as a service over the Internet (Furht 2010;De la Prieta et al. 2017;Eze et al. 2017b). Cloud computing is one potential approach for achieving interoperable healthcare solutions (Bhaskaran et al. 2013) and enabling performance management of care processes. ...
Systematic performance management for complex patient care is challenging. Heterogeneous healthcare data silos and inconsistent patient identity, coupled with patient privacy regulations, limit our ability to correlate healthcare data for complex patients. Cloud computing is an emerging technology that could be leveraged to address the issue of heterogeneous healthcare data silos if a regional health authority provided data hosting with appropriate data sharing agreements and identity management, in order to correlate healthcare data for complex patients. This paper introduces a configurable identity matching algorithm for correlating shared data from multiple stakeholders into a common data model to support performance management of community healthcare. The authors illustrate its use in a case study of cloud-hosted performance management for community care of complex patients at a regional health authority in Canada.
... On the other hand, the growing number of users who takes advantage of cloud solutions force cloud providers to assure an appropriate level of security. Hence, more and more organizations decide to move their data into the cloud (Tang et al. 2010;Sriram and Khajeh-Hosseini 2010;De la Prieta et al. 2017). As an example, an organization that lacks a service management computer system, we analyze the Polish Billiards and Snooker Association (PBSA). ...
Recently, we have witnessed unprecedented use of cloud computing and its services. It is influencing the way software is built, as well as company’ resources such as servers, workstations or generally hardware are used. This paper aims to examine the benefits of cloud usage to support real-time service systems, using the Salesforce platform. First, we explore the meaning and the role of cloud computing for the real-time service systems efficient functioning. Then, we build a service management platform for the Polish Billiards and Snooker Association (PBSA), based on a real-time system located in the cloud. This way, PBSA managers are able to complete their tasks in this system on-demand. Moreover, it is set up as a private cloud to grant access only to the snooker organization employees.
... This could be performed by monitoring algorithm presented in Fig. 2 (key messages monitoring in the informational space and probably by using certain kind of deep learning algorithms, neural networks etc.). This algorithm could be realized by means of implementing the scalable metadata fixation Computer Sciences platform, applicable approaches are described in the works [9][10][11]. An additional keywords injection process is depicted in Fig. 3. ...
This paper presents authors analytical view on social impacts as targeted advertisement into the network environment using Omori tectonic theory for description the processes of audience response evolution. This could be extremely important and useful in the modern world to realize desirable e-Gov informational policy in the circumstances of hybrid treats emergence that is especially relevant for the informational space and reaching a cyber-supremacy. Some mathematical and algorithmic basics were contributed for narrative description of information and communications technologies (ICT) architectural deployment could be used for outer regulation of audience response character by Social Media Marketing (SMM) principles. That could be performed by controlled distribution of specified digital content that contains respective key phrases, for example social advertisements and analyzing respective feed-backs. Some results of the empiric study of live audience response dependence on controlled impacts are discussed. Election processes data and recent media recordings for preliminary proof of the contributed concept feasibility have been analyzed. There were shown using gathered empiric data sets, that the extent of impacts to targeted audience response intensity could be the subject of outer regulation. The index has been contributed for assessment the efficiency of the impact’s propagation inside the audience by calculation of row correlation of keyword occurrence and audience response intensity. The approaches suggested in the article can be useful both for building effective interactive systems of state-society interaction and for detecting manipulative traits when influencing a specific audience
... This could be performed by monitoring algorithm presented in Fig. 2 (key messages monitoring in the informational space and probably by using certain kind of deep learning algorithms, neural networks etc.). This algorithm could be realized by means of implementing the scalable metadata fixation platform, applicable approaches are described in the works [9][10][11]. An additional keywords injection process is depicted in Fig. 3. ...
This paper presents authors analytical view on social impacts as targeted advertisement into the network environment using Omori tectonic theory for description the processes of audience response evolution. This could be extremely important and useful in the modern world to realize desirable e-Gov informational policy in the circumstances of hybrid treats emergence that is especially relevant for the informational space and reaching a cyber-supremacy. Some mathematical and algorithmic basics were contributed for narrative description of information and communications technologies (ICT) architectural deployment could be used for outer regulation of audience response character by Social Media Marketing (SMM) principles. That could be performed by controlled distribution of specified digital content that contains respective key phrases, for example social advertisements and analyzing respective feed-backs. Some results of the empiric study of live audience response dependence on controlled impacts are discussed. Election processes data and recent media recordings for preliminary proof of the contributed concept feasibility have been analyzed. There were shown using gathered empiric data sets, that the extent of impacts to targeted audience response intensity could be the subject of outer regulation. The index has been contributed for assessment the efficiency of the impact's propagation inside the audience by calculation of row correlation of keyword occurrence and audience response intensity. The approaches suggested in the article can be useful both for building effective interactive systems of state-society interaction and for detecting manipulative traits when influencing a specific audience. stress, and this law is the name of the Japanese scientist Omori, which at the end of the nineteenth century observed aftershocks of a strong earthquake in central Japan and foreshocks (small shocks preceding the main blow) [4]. In [1] two types of information shocks were distinguished, the "seismograms" of which differ radically. A graph similar to a bell for an endogenous (internal) stress present a peak preceded by a curve that fixes the gradual increase in the frequency of informational events (i. e. targeted informational activities intensity), followed by a near-symmetrical form of attenuation. The moments of stresses it fixes are induced by information circulating in the blogosphere of informational space for a long time, both before and after the peak. An example of the endogenous event is elected President's inauguration after final declaration of the poll. The authors of the article also point out that the peak and post-peak reaction of the informational space correlates with the behavior of key word markers preceding an endogenous shake, that is, in a certain sense, predictable. Hence the hypothesis is reasonable that knowing the behavior of precursors can even control this reaction, to build a predictable SMM automated system. As of 2011, by the keywords there were revealed about 150 of individual endogenous events, but exogenous (that is, caused from the outside)-about 1000 [1]. In fact, it was shown that exogenous events are an order of magnitude greater than endogenous, and one media event generally corresponds to events in several word frequencies (occurrences) of related keywords. Obviously, the blogosphere, while being a part of the information space, is at the same time a highly-strung environment that loses equilibrium in two main scenarios. According to the first one, endogenous (Fig. 1, b), in part of this medium, the gradual ordering of information begins (participants in the information environment, bloggers show increasing interest in a particular topic), reaching at some point the least entropy (the maximum of discussion), followed by a gradual relaxation and loss of information (interest in the subject of information impact disappears). This is
... Wireless Sensor Networks provide features aimed at gathering information about users and their environment in real time [21], which allow them to easily relate to Ambient Intelligence and those applications based on this paradigm [22]. On the one hand, there is currently a wide range of bio-metric sensors that allow collecting real-time information such as heart rate, temperature, activity (by means of MEMS -Microelectromechanical Systems [23]) or even more breakthrough proposals such as oximeters [24] and blood glucose levels [25]. ...
The Internet of Things (IoT) ceased to be a novel technology to become part of daily life through the millions of sensors, devices and tools that measure, collect, process and transfer data. The need to exchange, process, filter and store this huge volume of data has led to the emergence of Edge Computing (EC). The purpose of this new paradigm is to solve the challenges of IoT such as localized computing, reducing latency in information exchange, balancing data traffic on the network and providing responses in real-time. In order to reduce the complexity in the implementation of EC architectures, Software Defined Networks (SDNs) and the related concept Network Function Virtualization (NFV) are proposed by different approaches. This paper addresses the characteristics and capabilities of SDNs and NFV and why can be successful an innovative integration between SDNs and EC for IoT scenarios.
... And, they allow human agents to communicate with the intelligent agent through queries [36,37,38]. One way to model these systems with heterogeneous intelligent agents is the Virtual Organization [11,13,32], based on the Theory of Human Organizations [9], allowing the description of the structure, behavior and dynamics of the organization [2]. Virtual organizations can be considered as a set of component grouped that need to coordinate resources and services across institutional boundaries [13,30]. ...
... The main characteristic of ambient environments its adaptability to the context. Multi-agent systems (MASs) (Ferber 1995) can be used to create a scalable and adaptable environment than what is currently available (De la Prieta et al. 2017;Zhang et al. 2017). MAS allows realizing multiple device agents that obtain information of context and perform their own context inferences on the basis of the monitor readings as well as improvement of the ability to rapidly detect context information changes (Ferrando and Onaindia 2013;Olaru 2011;Chaouche et al. 2016;Zhang et al. 2014Zhang et al. , 2017. ...
The ambient intelligence consists of the integration of computer science technologies in the objects of the environment around us in order to create a smart one. Each object in the environment performs a different service as part of achieving a task. The adaptive Service composition is a context-aware system used in the situation where the user’s needs cannot be satisfied by a single service but by the combination of several ones. One of the main and principal characteristics of ambient environments is the adaptability to the context. The multi-agent systems with their characteristics of autonomy, proactivity, mobility and sociability are one of the most promising techniques of service composition and they became a major and significant paradigm for developping ambient systems. In this paper, we present a model of adaptive service composition in ambient environment based on multi-agent system named Multi Agent System for Adaptive Service Composition (MAS-ASC). To each object of the environment is associated an agent. The set of the agents coordinate their competences taking into account the context in order to perform an activity. MAS-ASC is based on the Contract Net Protocol in which the agents exchange their proposals in the form of call for proposal. It is implemented on Java Agent DEvelopment framework platform and has been tested to economize the consumption of energy in an intelligent lighting system example.
