27,827 research outputs found

    Beneath the Streets: New Tools for Managing Degrading Sewer Infrastructure

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    abstract: Infrastructure degradation is a chronic problem for fats, oils, and grease (FOG) pretreatment programs at wastewater utilities, which can lead to harmful bypass and high loss of a renewable energy feedstock. Not only does this exacerbate the potential for environmental harm, but not taking advantage of this resource leaves most FOG anaerobic digestion programs non-resilient and non-scalable. It is vital that there are strategies utilizing a sustainability perspective and integration of hard and soft infrastructure management principles to address this infrastructure degradation issue before there can be fully implemented zero-waste, FOG resource recovery initiatives. This applied project sought to answer the question, “How can municipalities sustainability manage the issue of degrading FOG pretreatment infrastructure?” with an emphasis on providing an applied example where a sustainability approach can mitigate complex, infrastructure problems. In partnership with the City of Tempe’s Environmental Services Section, this project addressed the issue of degrading infrastructure by crafting and implementing a comprehensive Infrastructure Assistance Program (IAP). Designed to assist food service establishments (FSEs) and wastewater utilities, the IAP provides pathways for preventing FOG infrastructure degradation through initiatives that bolster hard and soft infrastructure to support a more efficient means of achieving compliance and local goals for resource recovery and renewable energy

    Managing Service-Heterogeneity using Osmotic Computing

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    Computational resource provisioning that is closer to a user is becoming increasingly important, with a rise in the number of devices making continuous service requests and with the significant recent take up of latency-sensitive applications, such as streaming and real-time data processing. Fog computing provides a solution to such types of applications by bridging the gap between the user and public/private cloud infrastructure via the inclusion of a "fog" layer. Such approach is capable of reducing the overall processing latency, but the issues of redundancy, cost-effectiveness in utilizing such computing infrastructure and handling services on the basis of a difference in their characteristics remain. This difference in characteristics of services because of variations in the requirement of computational resources and processes is termed as service heterogeneity. A potential solution to these issues is the use of Osmotic Computing -- a recently introduced paradigm that allows division of services on the basis of their resource usage, based on parameters such as energy, load, processing time on a data center vs. a network edge resource. Service provisioning can then be divided across different layers of a computational infrastructure, from edge devices, in-transit nodes, and a data center, and supported through an Osmotic software layer. In this paper, a fitness-based Osmosis algorithm is proposed to provide support for osmotic computing by making more effective use of existing Fog server resources. The proposed approach is capable of efficiently distributing and allocating services by following the principle of osmosis. The results are presented using numerical simulations demonstrating gains in terms of lower allocation time and a higher probability of services being handled with high resource utilization.Comment: 7 pages, 4 Figures, International Conference on Communication, Management and Information Technology (ICCMIT 2017), At Warsaw, Poland, 3-5 April 2017, http://www.iccmit.net/ (Best Paper Award

    Edge/Fog Computing Technologies for IoT Infrastructure

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    The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies

    Move with Me: Scalably keeping virtual objects close to users on the move

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    The upcoming Cloud-Fog interplay is expected to grant service providers more degrees of freedom in the implementation and management of their service portfolios. However, recent advances in Mobile Internet have developed a growing need to support user mobility - as users move, the Fog counterparts of services that require close proximity may call for migration(s) to meet the desired quality of service (QoS). With the state-of-the-art virtualization technologies, next-generation Cloud/Fog services are being implemented in modular software (i.e., as a graph/chain of portable virtual objects (VOs)) that can be migrated around the Telco infrastructure, and yet scalability is still an open issue, especially with the inter-datacenter bulk live migration of VOs. In this perspective, a VO clustering and migration policy that jointly considers user proximity and inter-VO affinity is proposed to scalably support user mobility, while allowing service differentiation among users. Results confirm that introducing migrations improve the QoS to always meet or exceed the requirements, as compared to static service placement, and considering VO clusters as aggregate entities will initiate around 40% less migrations, on average - an improvement that increases with inter-VO affinity and could potentially simplify service management when supporting user mobility

    Flexible fog computing and telecom architecture for 5G networks

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    We review a novel, secure, highly distributed and ultra-dense fog computing infrastructure, which can be allocated at the extreme edge of a wired/wireless network for a Telecom Operator to provide multiple unified, cost-effective and new 5G services, such as Network Function Virtualization (NFV), Mobile Edge Computing (MEC), and services for third parties (e.g., smart cities, vertical industries or Internet of Things (IoT)). The distributed and programmable fog technologies are expected to strengthen the position of the Mobile Network and cloud markets; key benefits are the dynamic deployment of new distributed low-latency services. The architecture consists of three main building blocks: a) a scalable node, that is seamlessly integrated in the Telecom infrastructure; b) a controller, focused on service assurance, that is integrated in the management and orchestration architecture of the Telecom operator; and c) services running on top of the Telecom infrastructure.Peer ReviewedPostprint (author's final draft

    Multi-tier fog computing with large-scale IoT data analytics for smart cities

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    Analysis of Internet of Things (IoT) sensor data is a key for achieving city smartness. In this paper a multi-tier fog computing model with large-scale data analytics service is proposed for smart cities applications. The multi-tier fog is consisted of ad-hoc fogs and dedicated fogs with opportunistic and dedicated computing resources, respectively. The proposed new fog computing model with clear functional modules is able to mitigate the potential problems of dedicated computing infrastructure and slow response in cloud computing. We run analytics benchmark experiments over fogs formed by Rapsberry Pi computers with a distributed computing engine to measure computing performance of various analytics tasks, and create easy-to-use workload models. QoS aware admission control, offloading and resource allocation schemes are designed to support data analytics services, and maximize analytics service utilities. Availability and cost models of networking and computing resources are taken into account in QoS scheme design. A scalable system level simulator is developed to evaluate the fog based analytics service and the QoS management schemes. Experiment results demonstrate the efficiency of analytics services over multi-tier fogs and the effectiveness of the proposed QoS schemes. Fogs can largely improve the performance of smart city analytics services than cloud only model in terms of job blocking probability and service utility

    Software Defined Networking-based Vehicular Adhoc Network with Fog Computing

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    Vehicular Adhoc Networks (VANETs) have been attracted a lot of research recent years. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. We propose a new VANET architecture called FSDN which combines two emergent computing and network paradigm Software Defined Networking (SDN) and Fog Computing as a prospective solution. SDN-based architecture provides flexibility, scalability, programmability and global knowledge while Fog Computing offers delay-sensitive and location-awareness services which could be satisfy the demands of future VANETs scenarios. We figure out all the SDN-based VANET components as well as their functionality in the system. We also consider the system basic operations in which Fog Computing are leveraged to support surveillance services by taking into account resource manager and Fog orchestration models. The proposed architecture could resolve the main challenges in VANETs by augmenting Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Base Station communications and SDN centralized control while optimizing resources utility and reducing latency by integrating Fog Computing. Two use-cases for non-safety service (data streaming) and safety service (Lane-change assistance) are also presented to illustrate the benefits of our proposed architecture

    A Holistic Monitoring Service for Fog/Edge Infrastructures: a Foresight Study

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    International audienceAlthough academic and industry experts are now advocating for going from large-centralized Cloud Computing infrastructures to smaller ones massively distributed at the edge of the network, management systems to operate and use such infrastructures are still missing. In this paper, we focus on the monitoring service which is a key element to any management system in charge of operating a distributed infrastructure. Several solutions have been proposed in the past for cluster, grid and cloud systems. However, none is well appropriate to the Fog/Edge context. Our goal in this study, is to pave the way towards a holistic monitoring service for a Fog/Edge infrastructure hosting next generation digital services. The contributions of our work are: (i) the problem statement, (ii) a classification and a qualitative analysis of major existing solutions, and (iii) a preliminary discussion on the impact of the deployment strategy of functions composing the monitoring service
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