Cloud monitoring: A survey

Nowadays, Cloud Computing is widely used to deliver services over the Internet for both technical and economical reasons. The number of Cloud-based services has increased rapidly and strongly in the last years, and so is increased the complexity of the infrastructures behind these services. To properly operate and manage such complex infrastructures effective and efficient monitoring is constantly needed.Many works in literature have surveyed Cloud properties, features, underlying technologies (e.g. virtualization), security and privacy. However, to the best of our knowledge, these surveys lack a detailed analysis of monitoring for the Cloud. To fill this gap, in this paper we provide a survey on Cloud monitoring. We start analyzing motivations for Cloud monitoring, providing also definitions and background for the following contributions. Then, we carefully analyze and discuss the properties of a monitoring system for the Cloud, the issues arising from such properties and how such issues have been tackled in literature. We also describe current platforms, both commercial and open source, and services for Cloud monitoring, underlining how they relate with the properties and issues identified before. Finally, we identify open issues, main challenges and future directions in the field of Cloud monitoring.¹     

Editorial for FGCS special issue: Big Data in the cloud

Research associated with Big Data in the Cloud will be important topic over the next few years. The topic includes work on demonstrating architectures, applications, services, experiments and simulations in the Cloud to support the cases related to adoption of Big Data. A common approach to Big Data in the Cloud to allow better access, performance and efficiency when analysing and understanding the data is to deliver Everything as a Service. Organisations adopting Big Data this way find the boundaries between private clouds, public clouds and Internet of Things (IoT) can be very thin. Volume, variety, velocity, veracity and value are the major factors in Big Data systems but there are other challenges to be resolved.The papers of this special issue address a variety of issues and concerns in Big Data, including: searching and processing Big Data, implementing and modelling event and workflow systems, visualisation modelling and simulation and aspects of social media.     

Journey from cloud of things to fog of things: Survey,new trends,and research directions

With the advent of the Internet of Things (IoT) paradigm, the cloud model is unable to offer satisfactory services for latency-sensitive and real-time applications due to high latency and scalability issues. Hence, an emerging computing paradigm named as fog/edge computing was evolved, to offer services close to the data source and optimize the quality of services (QoS) parameters such as latency, scalability, reliability, energy, privacy, and security of data. This article presents the evolution in the computing paradigm from the client-server model to edge computing along with their objectives and limitations. A state-of-the-art review of Cloud Computing and Cloud of Things (CoT) is presented that addressed the techniques, constraints, limitations, and research challenges. Further, we have discussed the role and mechanism of fog/edge computing and Fog of Things (FoT), along with necessitating amalgamation with CoT. We reviewed the several architecture, features, applications, and existing research challenges of fog/edge computing. The comprehensive survey of these computing paradigms offers the depth knowledge about the various aspects, trends, motivation, vision, and integrated architectures. In the end, experimental tools and future research directions are discussed with the hope that this study will work as a stepping-stone in the field of emerging computing paradigms.     

A survey on data provenance in IoT

Internet of Things (IoT), as a typical representation of cyberization, enables the interconnection of physical things and the Internet, which provides intelligent and advanced services for industrial production and human lives. However, it also brings new challenges to IoT applications due to heterogeneity, complexity and dynamic nature of IoT. Especially, it is difficult to determine the sources of specified data, which is vulnerable to inserted attacks raised by different parties during data transmission and processing. In order to solve these issues, data provenance is introduced, which records data origins and the history of data generation and processing, thus possible to track the sources and reasons of any problems. Though some related researches have been proposed, the literature still lacks a comprehensive survey on data provenance in IoT. In this paper, we first propose a number of design requirements of data provenance in IoT by analyzing the features of IoT data and applications. Then, we provide a deep-insight review on existing schemes of IoT data provenance and employ the requirements to discuss their pros and cons. Finally, we summarize a number of open issues to direct future research.

     

A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion

Internet of Things (IoT) aims to create a world that enables the interconnection and integration of things in physical world and cyber space. With the involvement of a great number of wireless sensor devices, IoT generates a diversity of datasets that are massive, multi-sourcing, heterogeneous, and sparse. By taking advantage of these data to further improve IoT services and offer intelligent services, data fusion is always employed first to reduce the size and dimension of data, optimize the amount of data traffic and extract useful information from raw data. Although there exist some surveys on IoT data fusion, the literature still lacks comprehensive insight and discussion on it with regard to different IoT application domains by paying special attention to security and privacy. In this paper, we investigate the properties of IoT data, propose a number of IoT data fusion requirements including the ones about security and privacy, classify the IoT applications into several domains and then provide a thorough review on the state-of-the-art of data fusion in main IoT application domains. In particular, we employ the requirements of IoT data fusion as a measure to evaluate and compare the performance of existing data fusion methods. Based on the thorough survey, we summarize open research issues, highlight promising future research directions and specify research challenges.     

Confidential smart-sensing framework in the IoT era

With the revolution of the Internet technology, smart-sensing applications and the Internet of Things (IoT) are coupled in critical missions. Wireless sensor networks (WSNs), for example, present the main enabling technology in IoT architectures and extend the spectrum of their smart applications. However, this technology has limited resources and suffers from several vulnerabilities and security issues. Since the wireless networks used by this technology are deployed in open areas, several challenges are faced by the service provider in terms of privacy and the quality of service. Encryption can be a good solution to preserve confidentiality and privacy, but it raises serious problems concerning time latency and performance. In this paper, we propose agile framework that enables authentication, confidentiality and integrity while collecting the sensed data by using elliptic curve cryptography.     

Fog computing for next-generation Internet of Things: Fundamental,state-of-the-art and research challenges

In recent times, the Internet of Things (IoT) applications, including smart transportation, smart healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision making. In the past decades, real-time sensory data have been offloaded to centralized cloud servers for data analysis through a reliable communication channel. However, due to the long communication distance between end-users and centralized cloud servers, the chances of increasing network congestion, data loss, latency, and energy consumption are getting significantly higher. To address the challenges mentioned above, fog computing emerges in a distributed environment that extends the computation and storage facilities at the edge of the network. Compared to centralized cloud infrastructure, a distributed fog framework can support delay-sensitive IoT applications with minimum latency and energy consumption while analyzing the data using a set of resource-constraint fog/edge devices. Thus our survey covers the layered IoT architecture, evaluation metrics, and applications aspects of fog computing and its progress in the last four years. Furthermore, the layered architecture of the standard fog framework and different state-of-the-art techniques for utilizing computing resources of fog networks have been covered in this study. Moreover, we included an IoT use case scenario to demonstrate the fog data offloading and resource provisioning example in heterogeneous vehicular fog networks. Finally, we examine various challenges and potential solutions to establish interoperable communication and computation for next-generation IoT applications in fog networks.     

MIFaaS: A Mobile-IoT-Federation-as-a-Service Model for dynamic cooperation of IoT Cloud Providers

In the Internet of Things (IoT) arena, a constant evolution is observed towards the deployment of integrated environments, wherein heterogeneous devices pool their capacities to match wide-ranging user requirements. Solutions for efficient and synergistic cooperation among objects are, therefore, required. This paper suggests a novel paradigm to support dynamic cooperation among private/public local clouds of IoT devices. Differently from device-oriented approaches typical of Mobile Cloud Computing, the proposed paradigm envisages an IoT Cloud Provider (ICP)-oriented cooperation, which allows all devices belonging to the same private/public owner to participate in the federation process. Expected result from dynamic federations among ICPs is a remarkable increase in the amount of service requests being satisfied. Different from the Fog Computing vision, the network edge provides only management support and supervision to the proposed Mobile-IoT-Federation-as-a-Service (MIFaaS), thus reducing the deployment cost of peripheral micro data centers. The paper proposes a coalition formation game to account for the interest of rational cooperative ICPs in their own payoff. A proof-of-concept performance evaluation confirms that obtained coalition structures not only guarantee the satisfaction of the players’ requirements according to their utility function, but also these introduce significant benefits for the cooperating ICPs in terms of number of tasks being successfully assigned.     

How to adapt applications for the Cloud environment

The migration of existing applications to the Cloud requires adapting them to a new computing paradigm. Existing works have focused on migrating the whole application stack by means of virtualization and deployment on the Cloud, delegating the required adaptation effort to the level of resource management. With the proliferation of Cloud services allowing for more flexibility and better control over the application migration, the migration of individual application layers, or even individual architectural components to the Cloud, becomes possible. Towards this goal, in this work we focus on the challenges and solutions for each layer when migrating different parts of the application to the Cloud. We categorize different migration types and identify the potential impact and adaptation needs for each of these types on the application layers based on an exhaustive survey of the State of the Art. We also investigate various cross-cutting concerns that need to be considered for the migration of the application, and position them with respect to the identified migration types. Finally, we present some of the open research issues in the field and position our future work targeting these research questions.     

A survey of cloud resource management for complex engineering applications

Traditionally, complex engineering applications (CEAs), which consist of numerous components (software) and require a large amount of computing resources, usually run in dedicated clusters or high performance computing (HPC) centers. Nowadays, Cloud computing system with the ability of providing massive computing resources and customizable execution environment is becoming an attractive option for CEAs. As a new type on Cloud applications, CEA also brings the challenges of dealing with Cloud resources. In this paper, we provide a comprehensive survey of Cloud resource management research for CEAs. The survey puts forward two important questions: 1) what are the main challenges for CEAs to run in Clouds? and 2) what are the prior research topics addressing these challenges? We summarize and highlight the main challenges and prior research topics. Our work can be probably helpful to those scientists and engineers who are interested in running CEAs in Cloud environment.     

Future Internet technologies for environmental applications

This paper investigates the usability of Future Internet technologies (aka “Generic Enablers of the Future Internet”) in the context of environmental applications. The paper incorporates the best aspects of the state-of-the-art in environmental informatics with geospatial solutions and scalable processing capabilities of Internet-based tools. It specifically targets the promotion of the “Environmental Observation Web” as an observation-centric paradigm for building the next generation of environmental applications. In the Environmental Observation Web, the great majority of data are considered as observations. These can be generated from sensors (hardware), numerical simulations (models), as well as by humans (human sensors). Independently from the observation provenance and application scope, data can be represented and processed in a standardised way in order to understand environmental processes and their interdependencies. The development of cross-domain applications is then leveraged by technologies such as Cloud Computing, Internet of Things, Big Data Processing and Analytics. For example, “the cloud” can satisfy the peak-performance needs of applications which may occasionally use large amounts of processing power at a fraction of the price of a dedicated server farm. The paper also addresses the need for Specific Enablers that connect mainstream Future Internet capabilities with sensor and geospatial technologies. Main categories of such Specific Enablers are described with an overall architectural approach for developing environmental applications and exemplar use cases.     

Internet of Things in Healthcare: Architecture,Applications, Challenges,and Solutions

Healthcare, the largest global industry, is undergoing significant transformations with the genesis of a new technology known as the Internet of Things (IoT). Many healthcare leaders are investing more money for transforming their services to harness the benefits provided by IoT, thereby paving the way for the Internet of Medical Things (IoMT), an extensive collection of medical sensors and associated infrastructure. IoMT has many benefits like providing remote healthcare by monitoring health vitals of patients at a distant place, providing healthcare services to elderly people, and monitoring a large group of people in a region or country for detection and prevention of epidemics. This paper provides a review of IoT in the healthcare domain by first describing the enabling technologies for delivering smart healthcare, followed by some of the key applications of IoT in healthcare. Next, a fog-based architecture consisting of three layers for IoT-based healthcare applications is proposed. Finally, we focus on some of the open challenges of IoT in healthcare, like fault tolerance, interoperability, latency, energy efficiency, and availability. Existing solutions for these challenges are also discussed.     

Cybermatics: Cyber–physical–social–thinking hyperspace based science and technology

The Internet of Things (IoT) is becoming an attractive system paradigm, in which physical perceptions, cyber interactions, social correlations, and even cognitive thinking can be intertwined in the ubiquitous things’ interconnections. It realizes a perfect integration of a new cyber–physical–social–thinking (CPST) hyperspace, which has profound implications for the future IoT. In this article, a novel concept Cybermatics is put forward as a broader vision of the IoT (called hyper IoT) to address science and technology issues in the heterogeneous CPST hyperspace. This article covers a broaden research field and presents a preliminary study focusing on its three main features (i.e., interconnection, intelligence, and greenness). Concretely, interconnected Cybermatics refers to the variants of Internet of anything, such as physical objects, cyber services, social people, and human thinking; intelligent Cybermatics considers the cyber–physical–social–thinking computing to provide algorithmic support for system infrastructures; green Cybermatics addresses energy issues to ensure efficient communications and networking. Finally, open challenging science and technology issues are discussed in the field of Cybermatics.     

A dependability evaluation tool for the Internet of Things

The Internet of Things (IoT) is a promising networking paradigm which immerses objects (cell phones, goods, watches, sensing motes, TVs, etc.) in a worldwide connection. Despite its high degree of applicability, the IoT faces some challenges. One of the most challenging problems is its dependability (reliability and availability), since a device failure might put people in danger or result in financial loss. The lack of a design tool for assessing the dependability of IoT applications at the early planning and design phases prevents system designers from optimizing their decisions so as to minimize the effects of such faults on the network devices. In this paper, we propose a dependability evaluation tool for IoT applications, when hardware faults and permanent link faults are considered.     

Cloud services selection: A systematic review and future research directions

Cloud computing has developed in popularity as a large-scale computing paradigm that offers a range of computing resources as a service through the internet on a pay-as-you-go basis. The expansion in demand and commercial availability of cloud services brings new challenges to cloud services selection. Several research studies have been conducted to develop enhanced methodologies to assist service consumers in selecting appropriate services. In this paper, 105 primary studies published during January, 2011 to May, 2022 has been selected using a multi-stage scrutinizing approach. The selected preliminary studies were further classified based on various variables to answer the research questions stated for this work. A systematic review of existing cloud service selection approaches is performed, which are analyzed along eight dimensions: decision-making methods, context, purposes, cloud service performance parameters, simulation/language tools, domain, datasets, and experiment/validation methods. After a thorough review and comparison of these approaches across the above-mentioned dimensions, several open research issues in the current literature have been identified. The contribution of this research is fourfold: focusing on state-of-the-art cloud services selection approaches, highlighting the benefits and drawbacks of various cloud services selection methodologies and their future directions, offering a taxonomy based on a thorough literature study, and identifying nine critical challenges in cloud services selection that require further investigation. This systematic review study is anticipated to benefit both academics and business experts.     

Deadline-aware multi-objective IoT services placement optimization in fog environment using parallel FFD-genetic algorithm

Nowadays, Internet of things has become as an inevitable aspect of humans’ IT-based life. A huge number of geo-distributed IoT enabled devices such as smart phones, smart cameras, health care systems, vehicles, etc. are connected to the Internet and manage users’ applications. The IoT applications are generally time sensitive, so that giving them up to Cloud and receiving the response may violate their required deadline, due to distance between user device and centralized Cloud data center and consequently increasing network latency. Fog environment, as an intermediate layer between Cloud and IoT devices, brings a smaller scales of Cloud capabilities closer to user location. Processing real time applications in Fog layer helps more deadlines to be met. Although Fog computing enhances quality of service parameters, limited resources and power of Fog nodes is a challenge in processing applications. Furthermore, the network latency is still an issue for communications between applications’ services and between user device and Fog node, which seriously threatens deadline condition. Regarding to mentioned points, this paper proposes a 3-partite deadline-aware applications’ services placement optimization model in Fog environment which optimizes total power consumption, total resources wastage, and total network latency, simultaneously. The proposed model prioritizes applications in 3 levels based on their associated deadline, and then the model is solved using a parallel model of first fit decreasing and genetic algorithm combination. Simulations results indicates the superiority of proposed approach against counterpart algorithms in terms of reducing power consumption, resource wastage, network latency, and service rejection rate.     

Empirical evaluation of a cloud computing information security governance framework

ContextCloud computing is a thriving paradigm that supports an efficient way to provide IT services by introducing on-demand services and flexible computing resources. However, significant adoption of cloud services is being hindered by security issues that are inherent to this new paradigm. In previous work, we have proposed ISGcloud, a security governance framework to tackle cloud security matters in a comprehensive manner whilst being aligned with an enterprise’s strategy.ObjectiveAlthough a significant body of literature has started to build up related to security aspects of cloud computing, the literature fails to report on evidence and real applications of security governance frameworks designed for cloud computing environments. This paper introduces a detailed application of ISGCloud into a real life case study of a Spanish public organisation, which utilises a cloud storage service in a critical security deployment.MethodThe empirical evaluation has followed a formal process, which includes the definition of research questions previously to the framework’s application. We describe ISGcloud process and attempt to answer these questions gathering results through direct observation and from interviews with related personnel.ResultsThe novelty of the paper is twofold: on the one hand, it presents one of the first applications, in the literature, of a cloud security governance framework to a real-life case study along with an empirical evaluation of the framework that proves its validity; on the other hand, it demonstrates the usefulness of the framework and its impact to the organisation.ConclusionAs discussed on the paper, the application of ISGCloud has resulted in the organisation in question achieving its security governance objectives, minimising the security risks of its storage service and increasing security awareness among its users.     

Challenges in real-time virtualization and predictable cloud computing

Cloud computing and virtualization technology have revolutionized general-purpose computing applications in the past decade. The cloud paradigm offers advantages through reduction of operation costs, server consolidation, flexible system configuration and elastic resource provisioning. However, despite the success of cloud computing for general-purpose computing, existing cloud computing and virtualization technology face tremendous challenges in supporting emerging soft real-time applications such as online video streaming, cloud-based gaming, and telecommunication management. These applications demand real-time performance in open, shared and virtualized computing environments. This paper identifies the technical challenges in supporting real-time applications in the cloud, surveys recent advancement in real-time virtualization and cloud computing technology, and offers research directions to enable cloud-based real-time applications in the future.