1,011 research outputs found
Towards Blockchain-enabled Wireless Mesh Networks
Recently, mesh networking and blockchain are two of the hottest technologies
in the telecommunications industry. Combining both can reformulate internet
access and make connecting to the Internet not only easy, but affordable too.
Hyperledger Fabric (HLF) is a blockchain framework implementation and one of
the Hyperledger projects hosted by The Linux Foundation. We evaluate HLF in a
real production mesh network and in the laboratory, quantify its performance,
bottlenecks and limitations of the current implementation. We identify the
opportunities for improvement to serve the needs of wireless mesh access
networks. To the best of our knowledge, this is the first HLF deployment made
in a production wireless mesh network
Distributed Access Control with Blockchain
The specification and enforcement of network-wide policies in a single
administrative domain is common in today's networks and considered as already
resolved. However, this is not the case for multi-administrative domains, e.g.
among different enterprises. In such situation, new problems arise that
challenge classical solutions such as PKIs, which suffer from scalability and
granularity concerns. In this paper, we present an extension to Group-Based
Policy -- a widely used network policy language -- for the aforementioned
scenario. To do so, we take advantage of a permissioned blockchain
implementation (Hyperledger Fabric) to distribute access control policies in a
secure and auditable manner, preserving at the same time the independence of
each organization. Network administrators specify polices that are rendered
into blockchain transactions. A LISP control plane (RFC 6830) allows routers
performing the access control to query the blockchain for authorizations. We
have implemented an end-to-end experimental prototype and evaluated it in terms
of scalability and network latency.Comment: 7 pages, 9 figures, 2 table
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
New Waves of IoT Technologies Research – Transcending Intelligence and Senses at the Edge to Create Multi Experience Environments
The next wave of Internet of Things (IoT) and Industrial Internet of Things (IIoT) brings new technological developments that incorporate radical advances in Artificial Intelligence (AI), edge computing processing, new sensing capabilities, more security protection and autonomous functions accelerating progress towards the ability for IoT systems to self-develop, self-maintain and self-optimise. The emergence of hyper autonomous IoT applications with enhanced sensing, distributed intelligence, edge processing and connectivity, combined with human augmentation, has the potential to power the transformation and optimisation of industrial sectors and to change the innovation landscape. This chapter is reviewing the most recent advances in the next wave of the IoT by looking not only at the technology enabling the IoT but also at the platforms and smart data aspects that will bring intelligence, sustainability, dependability, autonomy, and will support human-centric solutions.acceptedVersio
Decentralized Federated Learning on the Edge over Wireless Mesh Networks
The rapid growth of Internet of Things (IoT) devices has generated vast
amounts of data, leading to the emergence of federated learning as a novel
distributed machine learning paradigm. Federated learning enables model
training at the edge, leveraging the processing capacity of edge devices while
preserving privacy and mitigating data transfer bottlenecks. However, the
conventional centralized federated learning architecture suffers from a single
point of failure and susceptibility to malicious attacks. In this study, we
delve into an alternative approach called decentralized federated learning
(DFL) conducted over a wireless mesh network as the communication backbone. We
perform a comprehensive network performance analysis using stochastic geometry
theory and physical interference models, offering fresh insights into the
convergence analysis of DFL. Additionally, we conduct system simulations to
assess the proposed decentralized architecture under various network parameters
and different aggregator methods such as FedAvg, Krum and Median methods. Our
model is trained on the widely recognized EMNIST dataset for benchmarking
handwritten digit classification. To minimize the model's size at the edge and
reduce communication overhead, we employ a cutting-edge compression technique
based on genetic algorithms. Our simulation results reveal that the compressed
decentralized architecture achieves performance comparable to the baseline
centralized architecture and traditional DFL in terms of accuracy and average
loss for our classification task. Moreover, it significantly reduces the size
of shared models over the wireless channel by compressing participants' local
model sizes to nearly half of their original size compared to the baselines,
effectively reducing complexity and communication overhead
5G and the Internet of everyone: motivation, enablers, and research agenda
As mobile broadband subscriptions grow twice as fast as the fixed ones and the Internet of Things comes forth, the 5G vision of the Internet of Everything (people, devices, and things), becomes a substantial and credible part of the near future. In this paper, we argue that the 5G vision is still missing a fundamental concept to realize its societal promise: the Internet of EveryOne (IoEO), i.e., means and principles to overcome the concerns that the current 5G perspective raises for the digital divide and the network neutrality principle. We discuss open-source software and hardware, Community Networks, mobile edge computing and blockchains as enablers of the IoEO and highlight open research challenges with respect to them. The ultimate objective of our paper is to stimulate research with a short-term, lasting impact also on that 50% (or more) of population that will not enjoy 5G anytime soon. Internet of EveryOne, community networks, 5G, mobile edge computing, network neutrality, community cloud computing.Peer ReviewedPostprint (author's final draft
Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordCritical infrastructure systems are vital to underpin
the functioning of a society and economy. Due to ever-increasing
number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data generated and collected,
security and scalability are becoming burning concerns for
critical infrastructures in industry 4.0. The blockchain technology
is essentially a distributed and secure ledger that records all
the transactions into a hierarchically expanding chain of blocks.
Edge computing brings the cloud capabilities closer to the
computation tasks. The convergence of blockchain and edge
computing paradigms can overcome the existing security and
scalability issues. In this paper, we first introduce the IoT/IIoT
critical infrastructure in industry 4.0, and then we briefly present
the blockchain and edge computing paradigms. After that, we
show how the convergence of these two paradigms can enable
secure and scalable critical infrastructures. Then, we provide a
survey on state-of-the-art for security and privacy, and scalability
of IoT/IIoT critical infrastructures. A list of potential research
challenges and open issues in this area is also provided, which
can be used as useful resources to guide future research.Engineering and Physical Sciences Research Council (EPSRC
Blockchain for economically sustainable wireless mesh networks
This is the peer reviewed version of the following article: Kabbinale, AR, Dimogerontakis, E, Selimi, M, et al. Blockchain for economically sustainable wireless mesh networks. Concurrency Computat Pract Exper. 2020; 32:e5349, which has been published in final form at https://doi.org/10.1002/cpe.5349. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Decentralization, in the form of mesh networking and blockchain, two promising technologies, is coming to the telecommunications industry. Mesh networking allows wider low-cost Internet access with infrastructures built from routers contributed by diverse owners, whereas blockchain enables transparency and accountability for investments, revenue, or other forms of economic compensations from sharing of network traffic, content, and services. Crowdsourcing network coverage, combined with crowdfunding costs, can create economically sustainable yet decentralized Internet access. This means that every participant can invest in resources and pay or be paid for usage to recover the costs of network devices and maintenance. While mesh networks and mesh routing protocols enable self-organized networks that expand organically, cryptocurrencies and smart contracts enable the economic coordination among network providers and consumers. We explore and evaluate two existing blockchain software stacks, Hyperledger Fabric (HLF) and Ethereum geth with Proof of Authority (PoA) intended as a local lightweight distributed ledger, deployed in a real city-wide production mesh network and in laboratory network. We quantify the performance and bottlenecks and identify the current limitations and opportunities for improvement to serve locally the needs of wireless mesh networks, without the privacy and economic cost of relying on public blockchains.This paper has been supported by the AmmbrTech Group, the Spanish Government TIN2016‐77836‐C2‐2‐R and the European Community H2020 Programme netCommons (H2020‐688768). The authors would like to thank the people from the Guifi.net (Guifi‐Sants) community network for hosting the servers and supporting the experiments.Peer ReviewedPostprint (author's final draft
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