| 1. |
- Ali, Shaukat, et al.
(författare)
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Big data from the cloud to the edge : The aggregate computing solution
- 2019
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Ingår i: PervasiveHealth. - New York, NY, USA : ACM Publications. - 9781450371421 ; , s. 177-182
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Konferensbidrag (refereegranskat)abstract
- We advocate a novel concept of dependable intelligent edge systems (DIES) i.e., the edge systems ensuring a high degree of dependability (e.g., security, safety, and robustness) and autonomy because of their applications in critical domains. Building DIES entail a paradigm shift in architectures for acquiring, storing, and processing potentially large amounts of complex data: data management is placed at the edge between the data sources and local processing entities, with loose coupling to storage and processing services located in the cloud. As such, the literal definition of edge and intelligence is adopted, i.e., the ability to acquire and apply knowledge and skills is shifted towards the edge of the network, outside the cloud infrastructure. This paradigm shift offers flexibility, auto configuration, and auto diagnosis, but also introduces novel challenges. © 2019 ACM.
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| 2. |
- Alkhabbas, Fahed, et al.
(författare)
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A Goal driven Approach for Deploying Self-adaptive IoT Systems
- 2020
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Ingår i: Proceedings. - 9781728146591 - 9781728146607 ; , s. 146-156
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Konferensbidrag (refereegranskat)abstract
- Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.
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| 3. |
- Baresi, Luciano, et al.
(författare)
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Building Software for the Internet of Things
- 2015. - 9
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Ingår i: IEEE Internet Computing. - 1089-7801 .- 1941-0131. ; 19:2, s. 6-8
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Tidskriftsartikel (refereegranskat)abstract
- The guest editors present a special issue on building software for the Internet of Things (IoT).
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| 4. |
- Bucchiarone, Antonio, et al.
(författare)
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From Monolithic to Microservices An Experience Report from the Banking Domain
- 2018
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Ingår i: IEEE Software. - : IEEE Computer Society. - 0740-7459 .- 1937-4194. ; 35:3, s. 50-55
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Tidskriftsartikel (refereegranskat)abstract
- Microservices have seen their popularity blossoming with an explosion of concrete applications in real-life software. Several companies are currently involved in a major refactoring of their back-end systems in order to improve scalability. This article presents an experience report of a real-world case study, from the banking domain, in order to demonstrate how scalability is positively affected by reimplementing a monolithic architecture into microservices. The case study is based on the FX Core system for converting from one currency to another. FX Core is a mission-critical system of Danske Bank, the largest bank in Denmark and one of the leading financial institutions in Northern Europe.
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| 5. |
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| 6. |
- de Lemos, Rogerio, et al.
(författare)
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Software Engineering for Self-Adaptive Systems : A Second Research Roadmap
- 2013
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Ingår i: Software Engineering for Self-Adaptive Systems II. - Berlin, Heidelberg : Springer. - 9783642358128 ; , s. 1-32
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.
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| 7. |
- Deng, Shuiguang, et al.
(författare)
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Optimal Application Deployment in Resource Constrained Distributed Edges
- 2021
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Ingår i: IEEE Transactions on Mobile Computing. - : IEEE Computer Society. - 1536-1233 .- 1558-0660. ; 20:5, s. 1907-1923
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Tidskriftsartikel (refereegranskat)abstract
- The dramatically increasing of mobile applications make it convenient for users to complete complex tasks on their mobile devices. However, the latency brought by unstable wireless networks and the computation failures caused by constrained resources limit the development of mobile computing. A popular approach to solve this problem is to establish a mobile service provisioning system based on a mobile edge computing (MEC) paradigm. In the MEC paradigm, plenty of machines are placed at the edge of the network so that the performance of applications can be optimized by using the involved microservice instances deployed on them. In this paper, we explore the deployment problem of microserivce-based applications in the MEC environment and propose an approach to help to optimize the cost of application deployment with the constraints of resources and the requirement of performance. We conduct a series of experiments to evaluate the performance of our approach. The result shows that our approach can improve the average response time of mobile services.
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| 8. |
- Donta, Praveen Kumar, et al.
(författare)
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Governance and sustainability of distributed continuum systems: a big data approach
- 2023
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Ingår i: Journal of Big Data. - 2196-1115. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Distributed computing continuum systems (DCCS) make use of a vast number of computing devices to process data generated by edge devices such as the Internet of Things and sensor nodes. Besides performing computations, these devices also produce data including, for example, event logs, configuration files, network management information. When these data are analyzed, we can learn more about the devices, such as their capabilities, processing efficiency, resource usage, and failure prediction. However, these data are available in different forms and have different attributes due to the highly heterogeneous nature of DCCS. The diversity of data poses various challenges which we discuss by relating them to big data, so that we can utilize the advantages of big data analytical tools. We enumerate several existing tools that can perform the monitoring task and also summarize their characteristics. Further, we provide a general governance and sustainable architecture for DCCS, which reflects the human body’s self-healing model. The proposed model has three stages: first, it analyzes system data to acquire knowledge; second, it can leverage the knowledge to monitor and predict future conditions; and third, it takes further actions to autonomously solve any issue or to alert administrators. Thus, the DCCS model is designed to minimize the system’s downtime while optimizing resource usage. A small set of data is used to illustrate the monitoring and prediction of the performance of a system through Bayesian network structure learning. Finally, we discuss the limitations of the governance and sustainability model, and we provide possible solutions to overcome them and make the system more efficient.
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| 9. |
- Fazio, Maria, et al.
(författare)
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A Note on the Convergence of IoT, Edge, and Cloud Computing in Smart Cities
- 2018
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Ingår i: IEEE Cloud Computing. - : IEEE. - 2325-6095. ; 5:5, s. 22-24
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of the special issue is to cover all aspects of design and implementation, as well as deployment and evaluation of solutions aimed at the osmotic convergence of IoT, edge, and cloud computing, with specific reference to the smart cities application scenario.
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| 10. |
- Gholami, Ali, 1978-
(författare)
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Security and Privacy of Sensitive Data in Cloud Computing
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cloud computing offers the prospect of on-demand, elastic computing, provided as a utility service, and it is revolutionizing many domains of computing. Compared with earlier methods of processing data, cloud computing environments provide significant benefits, such as the availability of automated tools to assemble, connect, configure and reconfigure virtualized resources on demand. These make it much easier to meet organizational goals as organizations can easily deploy cloud services. However, the shift in paradigm that accompanies the adoption of cloud computing is increasingly giving rise to security and privacy considerations relating to facets of cloud computing such as multi-tenancy, trust, loss of control and accountability. Consequently, cloud platforms that handle sensitive information are required to deploy technical measures and organizational safeguards to avoid data protection breakdowns that might result in enormous and costly damages. Sensitive information in the context of cloud computing encompasses data from a wide range of different areas and domains. Data concerning health is a typical example of the type of sensitive information handled in cloud computing environments, and it is obvious that most individuals will want information related to their health to be secure. Hence, with the growth of cloud computing in recent times, privacy and data protection requirements have been evolving to protect individuals against surveillance and data disclosure. Some examples of such protective legislation are the EU Data Protection Directive (DPD) and the US Health Insurance Portability and Accountability Act (HIPAA), both of which demand privacy preservation for handling personally identifiable information. There have been great efforts to employ a wide range of mechanisms to enhance the privacy of data and to make cloud platforms more secure. Techniques that have been used include: encryption, trusted platform module, secure multi-party computing, homomorphic encryption, anonymization, container and sandboxing technologies. However, it is still an open problem about how to correctly build usable privacy-preserving cloud systems to handle sensitive data securely due to two research challenges. First, existing privacy and data protection legislation demand strong security, transparency and audibility of data usage. Second, lack of familiarity with a broad range of emerging or existing security solutions to build efficient cloud systems. This dissertation focuses on the design and development of several systems and methodologies for handling sensitive data appropriately in cloud computing environments. The key idea behind the proposed solutions is enforcing the privacy requirements mandated by existing legislation that aims to protect the privacy of individuals in cloud-computing platforms. We begin with an overview of the main concepts from cloud computing, followed by identifying the problems that need to be solved for secure data management in cloud environments. It then continues with a description of background material in addition to reviewing existing security and privacy solutions that are being used in the area of cloud computing. Our first main contribution is a new method for modeling threats to privacy in cloud environments which can be used to identify privacy requirements in accordance with data protection legislation. This method is then used to propose a framework that meets the privacy requirements for handling data in the area of genomics. That is, health data concerning the genome (DNA) of individuals. Our second contribution is a system for preserving privacy when publishing sample availability data. This system is noteworthy because it is capable of cross-linking over multiple datasets. The thesis continues by proposing a system called ScaBIA for privacy-preserving brain image analysis in the cloud. The final section of the dissertation describes a new approach for quantifying and minimizing the risk of operating system kernel exploitation, in addition to the development of a system call interposition reference monitor for Lind - a dual sandbox.
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| 11. |
- Hazra, Abhishek, et al.
(författare)
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Distributed AI in Zero-Touch Provisioning for Edge Networks: Challenges and Research Directions
- 2024
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Ingår i: Computer. - 0018-9162 .- 1558-0814. ; 57:3, s. 69-78
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Tidskriftsartikel (refereegranskat)abstract
- This article combines Distributed Artificial Intelligence (DAI) with zero-touch provisioning (ZTP) for edge networks. Several advantages are also highlighted that come with incorporating DAI into ZTP in the context of edge networks. Further, we draw potential research directions to foster novel studies in this field.
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| 12. |
- Li, Fei, et al.
(författare)
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Proactive Service Discovery in Pervasive Environments
- 2010
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Ingår i: Proceedings of the 7th ACM International Conference on Pervasive Services (ICPS). ; , s. 126-133
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Konferensbidrag (refereegranskat)abstract
- Pervasive environments are characterized by rich and dy-namic context, where users need to be continuously informed about services relevant to their current context. Implicit discovery requests, triggered by changes of user context, avail-able services, or user preferences are prevalent in such environments.This paper proposes a proactive service discovery approach for pervasive environments to address these implicit requests. Services and user preferences are described by a formal context model, which effectively captures the dynamics of context and the relationship between services and users. Based on the model, we propose a proactive discovery algorithm to continuously present the most relevant services to the user in response to changes of context, services or user preferences. Numeric coding methods are applied in different phases of the algorithm to improve its performance. A proactive service discovery system is proposed and the context model is grounded in a smart home environment. Experimental results show that our approach can efficiently provide the user with up-to-date information about useful services.
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| 13. |
- Mazzara, Manuel, et al.
(författare)
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Microservices : Migration of a Mission Critical System
- 2021
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Ingår i: IEEE Transactions on Services Computing. - : IEEE Press. - 1939-1374. ; 14:5, s. 1464-1477
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Tidskriftsartikel (refereegranskat)abstract
- An increasing interest is growing around the idea of microservices and the promise of improving scalability when compared to monolithic systems. Several companies are evaluating pros and cons of a complex migration. In particular, financial institutions are positioned in a difficult situation due to the economic climate and the appearance of agile competitors that can navigate in a more flexible legal framework and started their business since day one with more agile architectures and without being bounded to outdated technological standard. In this paper, we present a real world case study in order to demonstrate how scalability is positively affected by re-implementing a monolithic architecture (MA) into a microservices architecture (MSA). The case study is based on the FX Core system, a mission critical system of Danske Bank, the largest bank in Denmark and one of the leading financial institutions in Northern Europe. The technical problem that has been addressed and solved in this paper is the identification of a repeatable migration process that can be used to convert a real world Monolithic architecture into a Microservices architecture in the specific setting of financial domain, typically characterized by legacy systems and batch-based processing on heterogeneous data sources.
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| 14. |
- Noor, Ayman, et al.
(författare)
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A Framework for Monitoring Microservice-Oriented Cloud Applications in Heterogeneous Virtualization Environments
- 2019
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Ingår i: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). - : IEEE. - 9781728127057
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Konferensbidrag (refereegranskat)abstract
- Microservices have emerged as a new approach for developing and deploying cloud applications that require higher levels of agility, scale, and reliability. To this end, a microservice-based cloud application architecture advocates decomposition of monolithic application components into independent software components called "microservices". As the independent microservices can be developed, deployed, and updated independently of each other, it leads to complex run-time performance monitoring and management challenges. To solve this problem, we propose a generic monitoring framework, Multi-microservices Multi-virtualization Multi-cloud (M3) that monitors the performance of microservices deployed across heterogeneous virtualization platforms in a multi-cloud environment. We validated the efficacy and efficiency of M3 using a Book-Shop application executing across AWS and Azure.
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| 15. |
- Patros, Panos, et al.
(författare)
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Towards Sustainable Serverless Computing
- 2021
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Ingår i: IEEE Internet Computing. - 1089-7801 .- 1941-0131. ; 25:6, s. 42-50
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Tidskriftsartikel (refereegranskat)abstract
- Although serverless computing generally involves executing short-lived “functions,” the increasing migration to this computing paradigm requires careful consideration of energy and power requirements. serverless computing is also viewed as an economically-driven computational approach, often influenced by the cost of computation, as users are charged for per-subsecond use of computational resources rather than the coarse-grained charging that is common with virtual machines and containers. To ensure that the startup times of serverless functions do not discourage their use, resource providers need to keep these functions hot, often by passing in synthetic data. We describe the real power consumption characteristics of serverless, based on execution traces reported in the literature, and describe potential strategies (some adopted from existing VM and container-based approaches) that can be used to reduce the energy overheads of serverless execution. Our analysis is, purposefully, biased toward the use of machine learning workloads because: (1) workloads are increasingly being used widely across different applications; (2) functions that implement machine learning algorithms can range in complexity from long-running (deep learning) versus short-running (inference only), enabling us to consider serverless across a variety of possible execution behaviors. The general findings are easily translatable to other domains.
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| 16. |
- Pujol, Víctor Casamayor, et al.
(författare)
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On Causality in Distributed Continuum Systems
- 2024
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Ingår i: IEEE Internet Computing. - 1089-7801 .- 1941-0131. ; 28:2, s. 57-64
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Tidskriftsartikel (refereegranskat)abstract
- As distributed continuum systems (DCSs) are envisioned, they will have a massive impact on our future society. Hence, it is of utmost importance to ensure that their impact is socially responsible. Equipping these systems with causal models brings features such as explainability, accountability, and auditability, which are needed to provide the right level of trust. Furthermore, by combining causality with graph-based service-level objectives, we can cope with dynamic and complex system requirements while achieving sustainable development of DCSs’ capacities and applications.
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| 17. |
- Schwiegelshohn, Uwe, et al.
(författare)
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Perspectives on grid computing
- 2010
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Ingår i: Future generations computer systems. - : Elsevier BV. - 0167-739X .- 1872-7115. ; 26:8, s. 1104-1115
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Tidskriftsartikel (refereegranskat)abstract
- Grid computing has been the subject of many large national and international IT projects. However, not all goals of these projects have been achieved. In particular. the number of users lags behind the initial forecasts laid out by proponents of grid technologies. This underachievement may have led to claims that the grid concept as a whole is on its way to being replaced by Cloud computing and various X-as-a-Service approaches. In this paper, we try to analyze the current situation and to identify promising directions for future grid development. Although there are shortcomings in current grid systems, we are convinced that the concept as a whole remains valid and can benefit from new developments, including Cloud computing. Furthermore, we strongly believe that some future applications will require the grid approach and that, as a result, further research is required in order to turn this concept into reliable, efficient and user-friendly computing platforms. (c) 2010 Elsevier B.V. All rights reserved.
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| 18. |
-
SE4COG '18: Proceedings of the 1st International Workshop on Software Engineering for Cognitive Services
- 2018
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Proceedings (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Welcome to the 1st International Workshop on Software Engineering for Cognitive Services (SE4COG 2018). We are excited and happy to have you here. The motivation for the workshop comes from the recognition that we are entering a new era of computing and we are moving in a somewhat uncharted territory. We are transitioning from a deterministic model where services are invoked with known, fixed, understood parameters and the service performs exactly what is requested, barring systems error, to a scenario where services try to interpret the user request in the best possible way and access the resources they consider appropriate for fulfilling the request, amongst a large and rapidly evolving set of available base APIs to be invoked. In this workshop, we will discuss the issues and challenges that such services bring from a software engineering perspective. Through a set of talks, panels, and open discussions we will try to understand and identify which are the fundamental differences of cognitive services and how we need to approach both the challenges they present but also the opportunities. Are current approaches to service design valid and applicable for cognitive services? What about requirements, testing, and even entirely new problems from a service engineering perspective, such as training? Even basic notions of correctness change and become somewhat blurred in cognitive service design, and it seems that disciplines such as HCI, information retrieval, knowledge management, and various sides of artificial intelligence become deeply intertwined in the service engineering process. How about service deployment in distributed elastic cloud infrastructures that are ubiquitous? How do we address service quality assurance at run-time such as response time, security, regulatory compliance of data mobility in the face of non-deterministic fluctuations in workloads and available computing resources? Are current software engineering practices adequate to harness the multi-core servers, GPUs, Optical software defined WANs to provide the scale, resiliency and efficiency demanded by global communication, collaboration and commerce services? These are only some of the issues and questions we will consider during the workshop. We hope in your active participation as we will need all your brainpower to identify the promising research directions and lay out a map that is hopefully useful for researchers exploring this new ground.
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| 19. |
- Sudharsan, Bharath, et al.
(författare)
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Toward Distributed, Global, Deep Learning Using IoT Devices
- 2021
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Ingår i: IEEE Internet Computing. - : IEEE. - 1089-7801 .- 1941-0131. ; 25:3
-
Tidskriftsartikel (refereegranskat)abstract
- Deep learning (DL) using large scale, high-quality IoT datasets can be computationally expensive. Utilizing such datasets to produce a problem-solving model within a reasonable time frame requires a scalable distributed training platform/system. We present a novel approach where to train one DL model on the hardware of thousands of mid-sized IoT devices across the world, rather than the use of GPU cluster available within a data center. We analyze the scalability and model convergence of the subsequently generated model, identify three bottlenecks that are: high computational operations, time consuming dataset loading I/O, and the slow exchange of model gradients. To highlight research challenges for globally distributed DL training and classification, we consider a case study from the video data processing domain. A need for a two-step deep compression method, which increases the training speed and scalability of DL training processing, is also outlined. Our initial experimental validation shows that the proposed method is able to improve the tolerance of the distributed training process to varying internet bandwidth, latency, and Quality of Service metrics.
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| 20. |
- Taheri, Javid, et al.
(författare)
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Edge Intelligence : From Theory to Practice
- 2023. - 1
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.
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| 21. |
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| 22. |
- Truong, Hong-Linh, 1975, et al.
(författare)
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Governing Bot-as-a-Service in Sustainability Platforms–Issues and Approaches
- 2012
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Ingår i: Procedia Computer Science. - : Elsevier BV. - 1877-0509. ; 10, s. 561-568
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Konferensbidrag (refereegranskat)abstract
- The emerging cloud computing models for Internet-of-Things have fostered the development of lightweight applications using cloud services for monitoring and optimizing devices and equipment hosted in distributed facilities. Such applications – called bots in our work – can be composed and deployed with multiple types of governance policies from cloud platforms to distributed hosting environments and they can access not only local data and devices but also cloud data and features. Therefore, it is a great challenge to govern them. In this paper, we discuss governance issues and state-of-the-art on supporting the emerging Bot-as-a-Service in sustainability governance platforms. Based on that we outline our approaches to policy development and enforcement for the Bot-as-a-Service model
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