16 research outputs found

    Next generation single board clusters

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    Until recently, cluster computing was too expensive and too complex for commodity users. However the phenomenal popularity of single board computers like the Raspberry Pi has caused the emergence of the single board computer cluster. This demonstration will present a cheap, practical and portable Raspberry Pi cluster called Pi Stack. We will show pragmatic custom solutions to hardware issues, such as power distribution, and software issues, such as remote updating. We also sketch potential use cases for Pi Stack and other commodity single board computer cluster architectures

    Energy Usage Profiling for Virtualized Single Board Computer Clusters

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    With Network Function Virtualization (NFV) platforms gaining ground, we question the combination of NFV and Single Board Computers (SBCs) in terms of compatibility, reliability, and energy consumption. A mini cluster of SBCs is used to develop a scalable and resilient energy monitoring application. The application is employed to discover the energy demands of a NFV platform in modern SBCs, and build the energy profile of the devices and the deployed services. We use the results and the added knowledge from building the application to strengthen the argument that SBC clusters can support virtualized service deployment. This evidence, alongside the rich gamut of characteristics that SBCs hold, proves that they are a viable option for edge components of a fog network. Our results show that running different virtualised processes offers added functionality, resilience and scalability without heavily sacrificing energy consumption

    Harnessing single board computers for military data analytics

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    Executive summary: This chapter covers the use of Single Board Computers (SBCs) to expedite onsite data analytics for a variety of military applications. Onsite data summarization and analytics is increasingly critical for command, control, and intelligence (C2I) operations, as excessive power consumption and communication latency can restrict the efficacy of down-range operations. SBCs offer power-efficient, inexpensive data-processing capabilities while maintaining a small form factor. We discuss the use of SBCs in a variety of domains, including wireless sensor networks, unmanned vehicles, and cluster computing. We conclude with a discussion of existing challenges and opportunities for future use.https://digitalcommons.usmalibrary.org/books/1010/thumbnail.jp

    EdgeNet: A Multi-Tenant and Multi-Provider Edge Cloud

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    International audienceEdgeNet is a public Kubernetes cluster dedicated to network and distributed systems research, supporting experiments that are deployed concurrently by independent groups. Its nodes are hosted by multiple institutions around the world. It represents a departure from the classic Kubernetes model, where the nodes that are available to a single tenant reside in a small number of well-interconnected data centers. The free open-source EdgeNet code extends Kubernetes to the edge, making three key contributions: multi-tenancy, geographical deployments, and single-command node installation. We show that establishing a public Kubernetes cluster over the internet, with multiple tenants and multiple hosting providers is viable. Preliminary results also indicate that the EdgeNet testbed that we run provides a satisfactory environment to run a variety of experiments with minimal network overhead

    Commodity single board computer clusters and their applications

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    © 2018 Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked together, to create small, low-cost clusters that replicate some features of large data center clusters. The Raspberry Pi Foundation produces a series of SBCs with a price/performance ratio that makes SBC clusters viable, perhaps even expendable. These clusters are an enabler for Edge/Fog Compute, where processing is pushed out towards data sources, reducing bandwidth requirements and decentralizing the architecture. In this paper we investigate use cases driving the growth of SBC clusters, we examine the trends in future hardware developments, and discuss the potential of SBC clusters as a disruptive technology. Compared to traditional clusters, SBC clusters have a reduced footprint, are low-cost, and have low power requirements. This enables different models of deployment—particularly outside traditional data center environments. We discuss the applicability of existing software and management infrastructure to support exotic deployment scenarios and anticipate the next generation of SBC. We conclude that the SBC cluster is a new and distinct computational deployment paradigm, which is applicable to a wider range of scenarios than current clusters. It facilitates Internet of Things and Smart City systems and is potentially a game changer in pushing application logic out towards the network edge

    Fog Orchestration and Simulation for IoT Services

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    The Internet of Things (IoT) interconnects physical objects including sensors, vehicles, and buildings into a virtual circumstance, resulting in the increasing integration of Cyber-physical objects. The Fog computing paradigm extends both computation and storage services in Cloud computing environment to the network edge. Typically, IoT services comprise of a set of software components running over different locations connected through datacenter or wireless sensor networks. It is significantly important and cost-effective to orchestrate and deploy a group of microservices onto Fog appliances such as edge devices or Cloud servers for the formation of such IoT services. In this chapter, we discuss the challenges of realizing Fog orchestration for IoT services, and present a software-defined orchestration architecture and simulation solutions to intelligently compose and orchestrate thousands of heterogeneous Fog appliances. The resource provisioning, component placement and runtime QoS control in the orchestration procedure can harness workload dynamicity, network uncertainty and security demands whilst considering different applications’ requirement and appliances’ capabilities. Our practical experiences show that the proposed parallelized orchestrator can reduce the execution time by 50% with at least 30% higher orchestration quality. We believe that our solution plays an important role in the current Fog ecosystem

    LEGIoT: a Lightweight Edge Gateway for the Internet of Things

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    International audienceThe stringent latency together with the higher bandwidth requirements of current Internet of Things (IoT) applications, are leading to the definition of new network-infrastructures, such as Multi-access Edge Computing (MEC). This emerging paradigm encompasses the execution of many network tasks at the edge and in particular on constrained gateways that have also to deal with the plethora of disparate technologies available in the IoT landscape. To cope with these issues, we introduce a Lightweight Edge Gateway for the Internet of Things (LEGIoT) architecture. It relies on the modular characteristic of microservices and the flexibility of lightweight virtualization technologies to guarantee an extensible and flexible solution. In particular, by combining the implementation of specific frameworks and the benefits of container-based virtualization, our proposal enhances the suitability of edge gateways towards a wide variety of IoT protocols/applications (for both downlink and uplink) enabling an optimized resource management and taking into account requirements such as energy efficiency, multi-tenancy, and interoperability. LEGIoT is designed to be hardware agnostic and its implementation has been tested within a real sensor network. Achieved results demonstrate its scalability and suitability to host different applications meant to provide a wide range of IoT services

    A Blockchain-based Decentralized Electronic Marketplace for Computing Resources

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    AbstractWe propose a framework for building a decentralized electronic marketplace for computing resources. The idea is that anyone with spare capacities can offer them on this marketplace, opening up the cloud computing market to smaller players, thus creating a more competitive environment compared to today's market consisting of a few large providers. Trust is a crucial component in making an anonymized decentralized marketplace a reality. We develop protocols that enable participants to interact with each other in a fair way and show how these protocols can be implemented using smart contracts and blockchains. We discuss and evaluate our framework not only from a technical point of view, but also look at the wider context in terms of fair interactions and legal implications

    Performance Evaluation of an Edge Computing Implementation of Hyperledger Sawtooth for IoT Data Security

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    Blockchain offers a potential solution to some of the security challenges faced by the internet-of-things (IoT) by using its practically immutable ledger to store data transactions. However, past applications of blockchain in IoT encountered limitations in the rate at which transactions were committed to the chain as new blocks. These limitations were often the result of the time-consuming and computationally expensive consensus mechanisms found in public blockchains. Hyperledger Sawtooth is an open-source private blockchain platform that offers an efficient proof-of-elapsed-time (PoET) consensus mechanism. Sawtooth has performed well in benchmarks against other blockchains. However, a performance evaluation for a practical application of Sawtooth for IoT data security using real data was found to be lacking in the literature. To address this gap, an experiment was designed to evaluate the performance of an edge computing implementation of Sawtooth to store temperature data from a physical IoT device. Experiments were then performed for a range of input transaction rates to evaluate performance under different workloads. The results of the experiments indicate that Sawtooth can store transactions at a rate of at least 10 transactions per second in the edge computing implementation that was evaluated. The implementation was highly reliable in terms of transactions submitted versus transactions committed. The experiment also demonstrates that blockchain applications for IoT data security can be extended to any environment that has access to relatively low specification hardware and Wi-Fi internet connectivity. Some limitations were encountered during the experiments, particularly in relation to the amount of variance in the rate at which transactions were committed to the blockchain. This could have implications for some use cases at the business solution layer that depend on stable and consistent performance
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