1,588 research outputs found

    Optimization of Beyond 5G Network Slicing for Smart City Applications

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    Transitioning from the current fifth-generation (5G) wireless technology, the advent of beyond 5G (B5G) signifies a pivotal stride toward sixth generation (6G) communication technology. B5G, at its essence, harnesses end-to-end (E2E) network slicing (NS) technology, enabling the simultaneous accommodation of multiple logical networks with distinct performance requirements on a shared physical infrastructure. At the forefront of this implementation lies the critical process of network slice design, a phase central to the realization of efficient smart city networks. This thesis assumes a key role in the network slicing life cycle, emphasizing the analysis and formulation of optimal procedures for configuring, customizing, and allocating E2E network slices. The focus extends to catering to the unique demands of smart city applications, encompassing critical areas such as emergency response, smart buildings, and video surveillance. By addressing the intricacies of network slice design, the study navigates through the complexities of tailoring slices to meet specific application needs, thereby contributing to the seamless integration of diverse services within the smart city framework. Addressing the core challenge of NS, which involves the allocation of virtual networks on the physical topology with optimal resource allocation, the thesis introduces a dual integer linear programming (ILP) optimization problem. This problem is formulated to jointly minimize the embedding cost and latency. However, given the NP-hard nature of this ILP, finding an efficient alternative becomes a significant hurdle. In response, this thesis introduces a novel heuristic approach the matroid-based modified greedy breadth-first search (MGBFS) algorithm. This pioneering algorithm leverages matroid properties to navigate the process of virtual network embedding and resource allocation. By introducing this novel heuristic approach, the research aims to provide near-optimal solutions, overcoming the computational complexities associated with the dual integer linear programming problem. The proposed MGBFS algorithm not only addresses the connectivity, cost, and latency constraints but also outperforms the benchmark model delivering solutions remarkably close to optimal. This innovative approach represents a substantial advancement in the optimization of smart city applications, promising heightened connectivity, efficiency, and resource utilization within the evolving landscape of B5G-enabled communication technology

    Modern computing: Vision and challenges

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    Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

    Exploring the inner mechanisms of 5G networks for orchestrating container-based applications in edge data centers

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    One of the novel new features of mobile 5G networks is what is commonly known as "Ultra Reliable Low Latency" communication. To achieve the "Low Latency" part, it is necessary to introduce processing and storage capabilities closer to the radio access network, thus introducing Edge data centers. An Edge data center will be capable of hosting third-party applications and a user of these applications can access them using the cellular mobile network. This makes the network path between the user equipment (UE) and the application short in terms of physical distance and network hops, thus reducing the latency dramatically. This thesis looks into these new features of the 5th-generation mobile networks to establish if, and how they can be used to orchestrate container-based applications deployed at edge data centers. The orchestration mechanism suggested will be described in more detail in the thesis body but as an overview, it involves using the user's positions and the knowledge about which applications the users are accessing and information about where these applications reside to move applications between edge data centers. One of the 5G exploration findings was that the location of users in a 5G network can be determined using the Network Exposure Function (NEF) API. The NEF is one of the new 5G network functions and enables trusted third-party actors to interact with the 5G core through a publisher-subscriber-oriented API. The proposed orchestration strategy involves calculating the ``weighted average location'' of 5G users who have accessed the specific application residing in the Edge within a specified time frame. A live 5G network with a stand-alone (SA) core was not available at the time of writing and part of the thesis work has therefore been to identify if there exist network emulators with the functionality needed to reach the goal of this thesis, i.e. design and implement the orchestrator based on interaction with the network. More specifically: can we find a NEF emulator that can be configured to give us network data related to user equipment location? Unfortunately, the three alternatives considered: Open5Gs, NEF\_emulator, and Nokia's Open5Glab do not fully meet our requirements for generating user events. Open5Gs an open source 5G network implementation lacks the whole NEF north-bridge implementation, NEF\_emulator has limited implementation and integration complexities, and Nokia's Open5Glab's simulated users are inactive and thus do not generate sufficient data. Given the absence of suitable emulators to generate the needed data, the thesis pivoted to also include the design and implementation of a mobile network emulator with the following key components: a mobile network abstraction that encompasses crucial elements from 5G, such as users and radio access nodes, allowing users to connect to the mobile network; a network abstraction that hosts emulated edge data centers and the corresponding applications accessible to connected users; and mobile network exposure that exposes mobile network core events through a simplified NEF north-bound API implementation. Finally, the thesis concludes by implementing the proposed orchestration strategy using the mobile network emulator, demonstrating that orchestrating can effectively reduce the end-to-end latency from users to applications, as evidenced by the obtained results

    Attributes in Cloud Service Descriptions : A comprehensive Content Analysis

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    The exponential growth of cloud services can make it challenging for customers to find the best available service. This problem is further aggregated by not comprehensive and non-standardized service descriptions on cloud providers’ websites. This issue has not yet been adequately researched. In response to this gap and following the call (Lehner & Floerecke, 2023) to analyse IT service catalogues directed toward external customers, the purpose of this work is to examine the attribute usage in customer-facing service descriptions available on providers’ websites. A literature review thereby identified 76 different attributes used for cloud service description. Although there are a vast number of attributes used for cloud service descriptions, a core of attributes that were named in most papers, could be detected. In a following step, a content analysis of 100 service descriptions available on cloud providers’ websites was performed to understand, how frequently each attribute was used in the cloud service description from Cloud providers in general and also differentiated by size, cloud service model (IaaS, PaaS, SaaS), and geographical location of the provider. The majority of attributes of the literature review could thereby be found in the content analysis as well. 15 more attributes have been added to the initial list as they could not be matched to any of the attributes from the literature. In addition, it could be verified that criteria such as size, service model, and geographical location have a significant impact on the attribute usage for service descriptions. Finally, expert interviews were conducted to get additional insights. The consent of the expert is that the main purpose of cloud service descriptions available on cloud providers’ websites is not necessarily to inform customers, but to attract and convince them. The insights of this work can provide valuable information to customers as well as cloud providers to understand, which attributes are currently used or not used for cloud service descriptions on provider’s websites. This research provides valuable information for both customers and cloud providers by identifying which attributes are currently used or not used for cloud service descriptions and can serve as a foundation for further research

    Review of Path Selection Algorithms with Link Quality and Critical Switch Aware for Heterogeneous Traffic in SDN

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    Software Defined Networking (SDN) introduced network management flexibility that eludes traditional network architecture. Nevertheless, the pervasive demand for various cloud computing services with different levels of Quality of Service requirements in our contemporary world made network service provisioning challenging. One of these challenges is path selection (PS) for routing heterogeneous traffic with end-to-end quality of service support specific to each traffic class. The challenge had gotten the research community\u27s attention to the extent that many PSAs were proposed. However, a gap still exists that calls for further study. This paper reviews the existing PSA and the Baseline Shortest Path Algorithms (BSPA) upon which many relevant PSA(s) are built to help identify these gaps. The paper categorizes the PSAs into four, based on their path selection criteria, (1) PSAs that use static or dynamic link quality to guide PSD, (2) PSAs that consider the criticality of switch in terms of an update operation, FlowTable limitation or port capacity to guide PSD, (3) PSAs that consider flow variabilities to guide PSD and (4) The PSAs that use ML optimization in their PSD. We then reviewed and compared the techniques\u27 design in each category against the identified SDN PSA design objectives, solution approach, BSPA, and validation approaches. Finally, the paper recommends directions for further research

    HeteroSketch: coordinating network-wide monitoring in heterogeneous and dynamic networks

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    CNS-2107086 - National Science Foundation; CNS-2106946 - National Science FoundationPublished versio

    Optimisation for Optical Data Centre Switching and Networking with Artificial Intelligence

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    Cloud and cluster computing platforms have become standard across almost every domain of business, and their scale quickly approaches O(106)\mathbf{O}(10^6) servers in a single warehouse. However, the tier-based opto-electronically packet switched network infrastructure that is standard across these systems gives way to several scalability bottlenecks including resource fragmentation and high energy requirements. Experimental results show that optical circuit switched networks pose a promising alternative that could avoid these. However, optimality challenges are encountered at realistic commercial scales. Where exhaustive optimisation techniques are not applicable for problems at the scale of Cloud-scale computer networks, and expert-designed heuristics are performance-limited and typically biased in their design, artificial intelligence can discover more scalable and better performing optimisation strategies. This thesis demonstrates these benefits through experimental and theoretical work spanning all of component, system and commercial optimisation problems which stand in the way of practical Cloud-scale computer network systems. Firstly, optical components are optimised to gate in ≈500ps\approx 500 ps and are demonstrated in a proof-of-concept switching architecture for optical data centres with better wavelength and component scalability than previous demonstrations. Secondly, network-aware resource allocation schemes for optically composable data centres are learnt end-to-end with deep reinforcement learning and graph neural networks, where 3×3\times less networking resources are required to achieve the same resource efficiency compared to conventional methods. Finally, a deep reinforcement learning based method for optimising PID-control parameters is presented which generates tailored parameters for unseen devices in O(10−3)s\mathbf{O}(10^{-3}) s. This method is demonstrated on a market leading optical switching product based on piezoelectric actuation, where switching speed is improved >20%>20\% with no compromise to optical loss and the manufacturing yield of actuators is improved. This method was licensed to and integrated within the manufacturing pipeline of this company. As such, crucial public and private infrastructure utilising these products will benefit from this work
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