Eco Models in Heteregeneous Peer-topeer (P2P) Systems

研究成果の概要 (和文) : 情報システムは、コンピュータ、センサ等の種々の情報機器を含んだ異種なものとなってきている。こうしたシステムでは、これまでの応答時間、スループット等の性能目標に加えて、新たにシステム全体の消費電力の低減が重要となってきている。本研究では、自律的な対等なプロセスから構成される完全分散型の大規模P2Pシステムを考える。ピア間の自律的な協調動作により、システム全体の消費電力を低減できる分散型システムの新しいモデル、特に消費電力については実際のコンピュータの消費電力の実測に基づいて、消費電力のモデルの構築を行った。このモデルに基づいて、ピア間の分散型の協調動作方式を研究し、評価を行った。研究成果の概要 (英文) : Information systems are composed of nodes like computers and sensors interconnected in networks. Here, we have to reduce the total electric energy consumed by nodes in addition to achieving traditional performance objectives. In this research, we proposed a power consumption model of a node to perform application processes. We first measure the total electric power of types of computers to perform application processes and then abstract essential parameters which dominate the power consumed by nodes. The power consumption model which we proposed is referred to as simple power consumption (SPC) model. Here, a computer consumes maximum poser [W] if at least one process is performed, otherwise consumes minimum power. Based on the SPC model, we proposed the energy-aware server selection (EA) algorithm and evaluated the EA model. In the evaluation, we showed not only the total power consumption of a server cluster but also the average execution time of each process are reduced

An Energy-Efficient Node Selection Algorithm for Recovering from Faults in the Tree-Based Fog Computing (TBFC) Model

In the FC (Fog Computing) model of the IoT (Internet of Things), subprocesses of an application process to handle sensor data are distributed to fog nodes and servers. In the TBFC (Tree-Based Fog Computing) model in our previous studies, fog nodes are hierarchically structured. In this paper, we propose a TBFCG (TBFC for a General process) model to recover from faults of fog nodes. If a node gets faulty, the child nodes are disconnected. We newly propose MET (Minimum Energy in the TBFCG tree) and MPT (selecting Multiple Parents for recovery in the TBFCG tree) algorithms to select new parent nodes for disconnected nodes. A new parent node has to process data from not only the disconnected nodes but also its own child nodes. In the evaluation, the energy consumption and execution time of a new parent node can be reduced by the proposed algorithms

Blockchain for secured IoT and D2D applications over 5G cellular networks : a thesis by publications presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand

Author's Declaration: "In accordance with Sensors, SpringerOpen, and IEEE’s copyright policy, this thesis contains the accepted and published version of each manuscript as the final version. Consequently, the content is identical to the published versions."The Internet of things (IoT) is in continuous development with ever-growing popularity. It brings significant benefits through enabling humans and the physical world to interact using various technologies from small sensors to cloud computing. IoT devices and networks are appealing targets of various cyber attacks and can be hampered by malicious intervening attackers if the IoT is not appropriately protected. However, IoT security and privacy remain a major challenge due to characteristics of the IoT, such as heterogeneity, scalability, nature of the data, and operation in open environments. Moreover, many existing cloud-based solutions for IoT security rely on central remote servers over vulnerable Internet connections. The decentralized and distributed nature of blockchain technology has attracted significant attention as a suitable solution to tackle the security and privacy concerns of the IoT and device-to-device (D2D) communication. This thesis explores the possible adoption of blockchain technology to address the security and privacy challenges of the IoT under the 5G cellular system. This thesis makes four novel contributions. First, a Multi-layer Blockchain Security (MBS) model is proposed to protect IoT networks while simplifying the implementation of blockchain technology. The concept of clustering is utilized to facilitate multi-layer architecture deployment and increase scalability. The K-unknown clusters are formed within the IoT network by applying a hybrid Evolutionary Computation Algorithm using Simulated Annealing (SA) and Genetic Algorithms (GA) to structure the overlay nodes. The open-source Hyperledger Fabric (HLF) Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The quantitative arguments demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported methods. The proposed lightweight blockchain model is also better suited to balance network latency and throughput compared to a traditional global blockchain. Next, a model is proposed to integrate IoT systems and blockchain by implementing the permissioned blockchain Hyperledger Fabric. The security of the edge computing devices is provided by employing a local authentication process. A lightweight mutual authentication and authorization solution is proposed to ensure the security of tiny IoT devices within the ecosystem. In addition, the proposed model provides traceability for the data generated by the IoT devices. The performance of the proposed model is validated with practical implementation by measuring performance metrics such as transaction throughput and latency, resource consumption, and network use. The results indicate that the proposed platform with the HLF implementation is promising for the security of resource-constrained IoT devices and is scalable for deployment in various IoT scenarios. Despite the increasing development of blockchain platforms, there is still no comprehensive method for adopting blockchain technology on IoT systems due to the blockchain's limited capability to process substantial transaction requests from a massive number of IoT devices. The Fabric comprises various components such as smart contracts, peers, endorsers, validators, committers, and Orderers. A comprehensive empirical model is proposed that measures HLF's performance and identifies potential performance bottlenecks to better meet blockchain-based IoT applications' requirements. The implementation of HLF on distributed large-scale IoT systems is proposed. The performance of the HLF is evaluated in terms of throughput, latency, network sizes, scalability, and the number of peers serviceable by the platform. The experimental results demonstrate that the proposed framework can provide a detailed and real-time performance evaluation of blockchain systems for large-scale IoT applications. The diversity and the sheer increase in the number of connected IoT devices have brought significant concerns about storing and protecting the large IoT data volume. Dependencies of the centralized server solution impose significant trust issues and make it vulnerable to security risks. A layer-based distributed data storage design and implementation of a blockchain-enabled large-scale IoT system is proposed to mitigate these challenges by using the HLF platform for distributed ledger solutions. The need for a centralized server and third-party auditor is eliminated by leveraging HLF peers who perform transaction verification and records audits in a big data system with the help of blockchain technology. The HLF blockchain facilitates storing the lightweight verification tags on the blockchain ledger. In contrast, the actual metadata is stored in the off-chain big data system to reduce the communication overheads and enhance data integrity. Finally, experiments are conducted to evaluate the performance of the proposed scheme in terms of throughput, latency, communication, and computation costs. The results indicate the feasibility of the proposed solution to retrieve and store the provenance of large-scale IoT data within the big data ecosystem using the HLF blockchain

Internet of Things From Hype to Reality

The Internet of Things (IoT) has gained significant mindshare, let alone attention, in academia and the industry especially over the past few years. The reasons behind this interest are the potential capabilities that IoT promises to offer. On the personal level, it paints a picture of a future world where all the things in our ambient environment are connected to the Internet and seamlessly communicate with each other to operate intelligently. The ultimate goal is to enable objects around us to efficiently sense our surroundings, inexpensively communicate, and ultimately create a better environment for us: one where everyday objects act based on what we need and like without explicit instructions

Energy Consumption and Computation Models of Storage Systems

It is critical to reduce the electric energy consumption of information systems to realize green societies. Applications like database and web applications take usage of data in storages systems of servers. In this paper, we consider RAID storage systems which are composed of multiple drives like hard disk drives (HDDs) and solid state drives (SSDs). Types of RAID storage systems, RAID0, RAID10(1+0), and RAID5 are considered in this paper. The performance and reliability of RAID storage systems are so far studied by many researchers. The more number of storage drives are possibly in parallel accessed in the RAID storage systems, the more amount of electric energy is consumed while the higher reliability and availability are supported. The electric energy consumption of the RAID storage systems to read and write data is so far not discussed. In this paper, we measure the power consumption of RAID storage systems and time to read and write data in the storage systems in order to make a power consumption model of a storage system. We make clear how much energy each type of RAID storage system consumes to sequentially and randomly read and write data through experiment in this paper

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

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda

Multi-source and Multi-target Node Selection in Energy-efficient Fog Computing Model

In the fog computing model to realize the IoT, each fog node supports application processes to calculate output data on input data received from a fog node and sends the output data to another fog node. In our previous studies, types of the TBFC (Tree-Based Fog Computing) models are proposed to reduce the electric energy consumption and execution time of fog nodes and servers and to be tolerant of node faults. In the TBFC models, the tree structure of fog nodes is not changed even if some fog node is overloaded and underloaded. In this paper, we consider the DNFC (Dynamic Network-based Fog Computing) model. Here, there is one or more than one possible target fog node for each fog node and also one or more than one possible source node for each target node. A pair of a source node and target node which exchange data have to be selected. In this paper, we propose an MSMT (Multi-Source and Multi-Target node selection) protocol among multiple source and target nodes. Here, a pair of a source node and a target node are selected so that the total energy consumption of the nodes can be reduced. In the evaluation, we show the total energy consumption and total execution time by target nodes can be more reduced in the MSMT protocol