Cloud-edge orchestration manages a large pool of heterogeneous resources to improve latency and bandwidth for real-time use cases. It dynamically places computational resources and applications, usually microservices,...
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ISBN:
(纸本)9798350322392
Cloud-edge orchestration manages a large pool of heterogeneous resources to improve latency and bandwidth for real-time use cases. It dynamically places computational resources and applications, usually microservices, at cloud and edge locations to enable low-latency communication. For this complex task, various optimization techniques have emerged over recent years. However, the majority implement custom and prototypical infrastructures for evaluation. This limits the general applicability, reusability, and comparability. Therefore, our work wants to contribute a universal and lightweight cloud-edge orchestration platform that fully decouples the optimization logic from the infrastructure. We analyzed the state-of-the-art cloud-edge orchestration and designed a generic cloud-edge orchestration platform. Besides the scientific perspective, we aligned our proposal to the OpenFog Reference Architecture to consider a perspective also from the industry. Therefore, our conceptually designed platform is based on the perspective of both academia and industry. We conclude that our platform can foster advanced cloud-edge orchestration techniques' general applicability, reusability, and comparability.
service-oriented architecture (SOA) serves as a foundational technology for complex IT systems, such as e-commerce platforms, banking solutions, public-sector applications, and gaming systems. As these systems become ...
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Latency-sensitive applications, such as online gaming, require that the conditions of networks from the server to each client are almost the same to achieve fairness. Traditionally, the servers are always set fixedly ...
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ISBN:
(纸本)9789819608072;9789819608089
Latency-sensitive applications, such as online gaming, require that the conditions of networks from the server to each client are almost the same to achieve fairness. Traditionally, the servers are always set fixedly in certain locations and only the nearby clients can connect, which is not fair to some far-away clients. To tackle the fairness issue, the emerging cloud computing or sky computing is a potential solution, where the server cannot be fixed anymore. Hence, we design LibraCloud, a novel server selection and allocation mechanism for latency-sensitive applications, using globally distributed cloud infrastructure. LibraCloud aims to select the fairest server rather than the best one. By defining a fairness indicator and dynamically utilizing multiple clouds, it overcomes the limitations of traditional fixed servers. To validate LibraCloud, we conduct experiments using 85 probes to simulate clients and 13 data centers for server selection. Assuming 20 distributed clients, 78.8% of the experimental cases show that LibraCloud selects the fairest server, significantly outperforming random selection or fixed three-server mechanisms.
Many researchers have come up with different ways to build a business model architecture for efficient services to run m-commerce applications. The framework for developing mobile commerce applications needs to change...
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ISBN:
(纸本)9798350351491;9798350351484
Many researchers have come up with different ways to build a business model architecture for efficient services to run m-commerce applications. The framework for developing mobile commerce applications needs to change at the same time as the IT expansion and business transformation. We are pursuing a theoretical business framework to find an optimal solution for the seamless service-oriented m-commerce application performance. In this approach, we identify the components of m-commerce applications that could reduce mobility barriers and improve application execution time and device energy efficiency. This led us to propose a framework for m-commerce application performance that uses the Mobile Cloud computing (MCC) solutions. This plan focuses on making the application run faster and use less energy, and making it easier for users to move around. We help mobile commerce application developers make smart RDMCA (Resource-Demanding M-commerce applications) that provide good services for mobile commerce businesses and consumers. A theoretical proposed business framework is being set up to find an optimal solution for service-oriented m-commerce application performance. In this way, we find the important parts of the m-commerce system (signal range determiner) that help make the application run faster, use less energy, and make it easier to move around. We think that improving this framework will help mobile commerce app developers to make RDMCA's that provide good services for both mobile commerce enterprises and end users.
The integration of Network Function Virtualization (NFV) and Mobile Edge computing (MEC) allows for efficient, advanced network services via service Function Chains (SFCs). SFCs are sequences of ordered network functi...
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ISBN:
(纸本)9781728190549
The integration of Network Function Virtualization (NFV) and Mobile Edge computing (MEC) allows for efficient, advanced network services via service Function Chains (SFCs). SFCs are sequences of ordered network functions designed to provide specific network services. However, the placement of SFCs is critical, especially for latency-sensitive applications such as telemedicine, due to spatial proximity between service functions, their processing order, and limited edge resources. This paper addresses the multi-SFC placement problem in MEC-NFV networks, aiming to reduce both deploying cost and routing cost. We propose an innovative algorithm based on topological sort, called TD-NFP, to solve this problem. The experimental results show that the proposed TD-NFP approach outperforms other benchmarks.
Multi-Access Edge computing (MEC) is a key technology in the field of telecommunications and computing. It brings computing and storage resources closer to the edge of the network, typically at or near base stations a...
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ISBN:
(纸本)9781728190549
Multi-Access Edge computing (MEC) is a key technology in the field of telecommunications and computing. It brings computing and storage resources closer to the edge of the network, typically at or near base stations and hence reduces the access latency of User Equipment (UE) to applications hosted at the edge. However, mobility of UEs brings challenging issues for service continuity and service Level Agreement (SLA) fulfilment of 5G services. To solve these issues, 3GPP introduced a new Network Function (NF) called the Edge Application Server Discovery Function (EASDF) [1]. The latter aims to support session breakouts by dynamically resolving the Domain Name service (DNS) of MEC applications to application servers closer to the UE's physical location. However, the 3GPP specifications [1] do not provide details about how the EASDF handles the UE's mobility. To fill this gap, we propose a novel design and implementation of the EASDF on the top of OpenAirInterface (OAI) open-source 5G network [2]. Simulation results show the efficiency of the EASDF in reducing the access latency during the UE's mobility with a small overhead of less than 4ms in high-load scenarios.
The fifth generation (5G) cellular network technology is mature and increasingly utilized in many industrial and robotics applications, while an important functionality is the advanced Quality of service (QoS) feature...
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ISBN:
(纸本)9798350384581;9798350384574
The fifth generation (5G) cellular network technology is mature and increasingly utilized in many industrial and robotics applications, while an important functionality is the advanced Quality of service (QoS) features. Despite the prevalence of 5G QoS discussions in the related literature, there is a notable absence of real-life implementations and studies concerning their application in time-critical robotics scenarios. This article considers the operation of time-critical applications for 5G-enabled unmanned aerial vehicles (UAVs) and how their operation can be improved by the possibility to dynamically switch between QoS data flows with different priorities. As such, we introduce a robotics oriented analysis on the impact of the 5G QoS functionality on the performance of 5G-enabled UAVs. Furthermore, we introduce a novel framework for the dynamic selection of distinct 5G QoS data flows that is autonomously managed by the 5G-enabled UAV. This problem is addressed in a novel feedback loop fashion utilizing a probabilistic finite state machine (PFSM). Finally, the efficacy of the proposed scheme is experimentally validated with a 5G-enabled UAV in a real-world 5G stand-alone (SA) network.
The Internet of Things (IoT) continues to expand and increasingly integrate into day-to-day life supporting multiple applications ranging from smart homes, and smart cities to autonomous vehicles and healthcare. Devel...
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ISBN:
(纸本)9798350304367;9798350304374
The Internet of Things (IoT) continues to expand and increasingly integrate into day-to-day life supporting multiple applications ranging from smart homes, and smart cities to autonomous vehicles and healthcare. Developing a sustainable IoT architecture to accommodate advanced applications presents a global challenge. A critical aspect of this challenge is ensuring energy efficiency while supporting a vast array of IoT devices and their service level agreements. A layered IoT architecture, encompassing edge, fog, and cloud layers, offers a viable solution to support these varied IoT applications. By optimally selecting nodes for processing incoming IoT requests from different use cases, energy efficiency can be significantly enhanced. In our research, we have developed frameworks for node selection across the edge-fog-cloud layers using Integer Linear Programming (ILP), and meta-heuristic methods. The frameworks we have implemented ensure not only energy efficiency but also adherence to the network and application-specific Quality of service (QoS) requirements. The proposed frameworks will be implemented in an event-driven simulation environment to validate their effectiveness in real-time network applications.
To harness the potential of edge resources, two-tier client-cloud applications require transformation into three-tier client-edge-cloud applications. Such transformations are hard for programmers to perform correctly ...
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ISBN:
(纸本)9798350386066;9798350386059
To harness the potential of edge resources, two-tier client-cloud applications require transformation into three-tier client-edge-cloud applications. Such transformations are hard for programmers to perform correctly by hand. Many cloud services maintain a runtime state that needs to be replicated at the edge. Once replicated, this state must then be synchronized efficiently and correctly. To facilitate the transition to edge computing, we present a framework that automatically transforms client-cloud apps to their client-edge-cloud versions. Our framework, EdgStr, automatically replicates cloud-based services at the edge. EdgStr synchronizes the replicated service state by relying on a third-party Conflict-Free Replicated Data Type (CRDT). It generates code that connects service state changes to CRDT update operations, thus ensuring that the state changes at each replica eventually converge to the same replicated state. As an evaluation, we applied EdgStr to transform representative distributed mobile apps for deployment in dissimilar network and device setups. EdgStr correctly replicates cloud services (targeting the important domain of ***), deploying the resulting replicas on an ad-hoc edge cluster, hosted by Raspberry PI devices. As long as eventual consistency is congruent with the functionality of a cloud service, EdgStr can automatically replicate this service and deploy the replicas at the edge, thus offering the performance benefits of edge-based execution, without the high costs of manual program transformation.
The evolution in the generations of smart applications has led to great challenges in terms of providing low latency and high computing efficiency. One of the most important of these applications is for smart homes, t...
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ISBN:
(纸本)9798350361261;9798350361278
The evolution in the generations of smart applications has led to great challenges in terms of providing low latency and high computing efficiency. One of the most important of these applications is for smart homes, through which various connected devices can be controlled by smart and efficient systems to achieve high service quality. In this paper, we propose a smart home controller based on fog computing, where home services are migrated from the cloud to the fog servers at the edge of the network. We propose an exact algorithm called Optimal Migration Algorithm (OMA) that allocates unified fog computing servers to different services. Moreover, to deal with large-scale networks, we propose an efficient algorithm called Efficient Migration Algorithm (EMA). The performance evaluation shows that the proposed optimization solutions are efficient in terms of migration cost, time, and end-to-end latency.
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