Twenty security considerations for cloud-supported Internet of Things

To realise the broad vision of pervasive computing, underpinned by the “Internet of Things” (IoT), it is essential to break down application and technology-based silos and support broad connectivity and data sharing; the cloud being a natural enabler. Work in IoT tends towards the subsystem, often focusing on particular technical concerns or application domains, before offloading data to the cloud. As such, there has been little regard given to the security, privacy and personal safety risks that arise beyond these subsystems; that is, from the wide-scale, crossplatform openness that cloud services bring to IoT. In this paper we focus on security considerations for IoT from the perspectives of cloud tenants, end-users and cloud providers, in the context of wide-scale IoT proliferation, working across the range of IoT technologies (be they things or entire IoT subsystems). Our contribution is to analyse the current state of cloud-supported IoT to make explicit the security considerations that require further work.This work was supported by UK Engineering and Physical Sciences Research Council grant EP/K011510 CloudSafetyNet: End-to-End Application Security in the Cloud and Microsoft through the Microsoft Cloud Computing Research Centre

Policy-driven Security Management for Gateway-Oriented Reconfigurable Ecosystems

abstract: With the increasing user demand for low latency, elastic provisioning of computing resources coupled with ubiquitous and on-demand access to real-time data, cloud computing has emerged as a popular computing paradigm to meet growing user demands. However, with the introduction and rising use of wear- able technology and evolving uses of smart-phones, the concept of Internet of Things (IoT) has become a prevailing notion in the currently growing technology industry. Cisco Inc. has projected a data creation of approximately 403 Zetabytes (ZB) by 2018. The combination of bringing benign devices and connecting them to the web has resulted in exploding service and data aggregation requirements, thus requiring a new and innovative computing platform. This platform should have the capability to provide robust real-time data analytics and resource provisioning to clients, such as IoT users, on-demand. Such a computation model would need to function at the edge-of-the-network, forming a bridge between the large cloud data centers and the distributed connected devices. This research expands on the notion of bringing computational power to the edge- of-the-network, and then integrating it with the cloud computing paradigm whilst providing services to diverse IoT-based applications. This expansion is achieved through the establishment of a new computing model that serves as a platform for IoT-based devices to communicate with services in real-time. We name this paradigm as Gateway-Oriented Reconfigurable Ecosystem (GORE) computing. Finally, this thesis proposes and discusses the development of a policy management framework for accommodating our proposed computational paradigm. The policy framework is designed to serve both the hosted applications and the GORE paradigm by enabling them to function more efficiently. The goal of the framework is to ensure uninterrupted communication and service delivery between users and their applications.Dissertation/ThesisMasters Thesis Computer Science 201

IoT-Fog-Edge-Cloud Computing Simulation Tools, A Systematic Review

The Internet of Things (IoT) perspective promises substantial advancements in sectors such as smart homes and infrastructure, smart health, smart environmental conditions, smart cities, energy, transportation and mobility, manufacturing and retail, farming, and so on. Cloud computing (CC) offers appealing computational and storage options; nevertheless, cloud-based explanations are frequently conveyed by downsides and constraints, such as energy consumption, latency, privacy, and bandwidth. To address the shortcomings related to CC, the advancements like Fog Computing (FC) and Edge Computing (EC) are introduced later on. FC is a novel and developing technology that connects the cloud to the network edges, allowing for decentrali zed computation. EC, in which processing and storage are performed nearer to where data is created, may be able to assist address these issues by satisfying particular needs such as low latency or lower energy use. This study provides a comprehensive overview and analysis of IoT-Fog-Edge-Cloud Computing simulation tools to assist researchers and developers in selecting the appropriate device for research studies while working through various scenarios and addressing current reality challenges. This study also takes a close look at various modeling tools, which are examined and contrasted to improve the future

Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

Performance and efficiency optimization of multi-layer IoT edge architecture

Abstract. Internet of Things (IoT) has become a backbone technology that connects together various devices with diverse capabilities. It is a technology, which enables ubiquitously available digital services for end-users. IoT applications for mission-critical scenarios need strict performance indicators such as of latency, scalability, security and privacy. To fulfil these requirements, IoT also requires support from relevant enabling technologies, such as cloud, edge, virtualization and fifth generation mobile communication (5G) technologies. For Latency-critical applications and services, long routes between the traditional cloud server and end-devices (sensors /actuators) is not a feasible approach for computing at these data centres, although these traditional clouds provide very high computational and storage for current IoT system. MEC model can be used to overcome this challenge, which brings the CC computational capacity within or next on the access network base stations. However, the capacity to perform the most critical processes at the local network layer is often necessary to cope with the access network issues. Therefore, this thesis compares the two existing IoT models such as traditional cloud-IoT model, a MEC-based edge-cloud-IoT model, with proposed local edge-cloud-IoT model with respect to their performance and efficiency, using iFogSim simulator. The results consolidate our research team’s previous findings that utilizing the three-tier edge-IoT architecture, capable of optimally utilizing the computational capacity of each of the three tiers, is an effective measure to reduce energy consumption, improve end-to-end latency and minimize operational costs in latency-critical It applications

KUBERNETES CLUSTER MANAGEMENT FOR CLOUD COMPUTING PLATFORM: A SYSTEMATIC LITERATURE REVIEW

Kubernetes is designed to automate the deployment, scaling, and operation of containerized applications. With the scalability feature of Kubernetes technology, container automation processes can be implemented according to the number of concurrent users accessing them. Therefore, this research focuses on how Kubernetes as cluster management is implemented on several cloud computing platforms. Standard literature review method employing a manual search for several journals and conference proceedings. From 15 relevant studies, 5 addressed Kubernetes performance and scalability. Seven literature review addressed Kubernetes deployments. Two articles addressed Kubernetes comparison and the rest is addressed Kubernetes in IoT. Regarding the cloud computing cluster management challenges that must be overcome using Kubernetes: it is necessary to ensure that all configuration and management required for Docker containers are successfully set up on on-premises systems before deploying to the cloud or on-premises. Data from Kubernetes deployments can be leveraged to support capacity planning and design Kubernetes-based elastic applications

Internet of Things Applications - From Research and Innovation to Market Deployment

The book aims to provide a broad overview of various topics of Internet of Things from the research, innovation and development priorities to enabling technologies, nanoelectronics, cyber physical systems, architecture, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from technology to international cooperation and the global "state of play".The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level. Internet of Things is creating a revolutionary new paradigm, with opportunities in every industry from Health Care, Pharmaceuticals, Food and Beverage, Agriculture, Computer, Electronics Telecommunications, Automotive, Aeronautics, Transportation Energy and Retail to apply the massive potential of the IoT to achieving real-world solutions. The beneficiaries will include as well semiconductor companies, device and product companies, infrastructure software companies, application software companies, consulting companies, telecommunication and cloud service providers. IoT will create new revenues annually for these stakeholders, and potentially create substantial market share shakeups due to increased technology competition. The IoT will fuel technology innovation by creating the means for machines to communicate many different types of information with one another while contributing in the increased value of information created by the number of interconnections among things and the transformation of the processed information into knowledge shared into the Internet of Everything. The success of IoT depends strongly on enabling technology development, market acceptance and standardization, which provides interoperability, compatibility, reliability, and effective operations on a global scale. The connected devices are part of ecosystems connecting people, processes, data, and things which are communicating in the cloud using the increased storage and computing power and pushing for standardization of communication and metadata. In this context security, privacy, safety, trust have to be address by the product manufacturers through the life cycle of their products from design to the support processes. The IoT developments address the whole IoT spectrum - from devices at the edge to cloud and datacentres on the backend and everything in between, through ecosystems are created by industry, research and application stakeholders that enable real-world use cases to accelerate the Internet of Things and establish open interoperability standards and common architectures for IoT solutions. Enabling technologies such as nanoelectronics, sensors/actuators, cyber-physical systems, intelligent device management, smart gateways, telematics, smart network infrastructure, cloud computing and software technologies will create new products, new services, new interfaces by creating smart environments and smart spaces with applications ranging from Smart Cities, smart transport, buildings, energy, grid, to smart health and life. Technical topics discussed in the book include: • Introduction• Internet of Things Strategic Research and Innovation Agenda• Internet of Things in the industrial context: Time for deployment.• Integration of heterogeneous smart objects, applications and services• Evolution from device to semantic and business interoperability• Software define and virtualization of network resources• Innovation through interoperability and standardisation when everything is connected anytime at anyplace• Dynamic context-aware scalable and trust-based IoT Security, Privacy framework• Federated Cloud service management and the Internet of Things• Internet of Things Application

Towards Enhancing the Capability of IoT Applications by Utilizing Cloud Computing Concept

The emergence of smart and innovative applications in diverse domains has inspired our lives by presenting many state-of-The art applications ranging from offline to smart online systems, smart communication system to tracking systems, and many others. The availability of smart internet enabled systems has made the world as a global village where people can collaborate, communicate, and share information in secure and timely manner. Innovation in information technology focuses on investigating characteristics that make it easier for the people to accept and distribute innovative IT-based processes or products. To provide elastic services and resource the Internet service provider developed cloud computing to support maximal number of users. Cloud computing is a subscription paradigm in which users do not buy various resources permanently, but they purchase it with block chain-driven payment schemes (credit cards). A flexible, on-demand, and dynamically scalable computer infrastructure is offered by cloud providers to its clients on charging some amount of subscription. This research article provides an introduction of cloud computing and the integration of IoT concept, its impacts on crowd and organizations, provision of various services, and analyzing and selecting the appropriate features using probability distribution function for enhancing cloud-based IoT capabilities. In ambiguous and complex situations, decision makers use quantitative techniques combined with traditional approaches to select the appropriate one among a group of features. Probability distribution function is used to evaluate the appropriate features that will enhance the capabilities of cloud-based IoT application

Internet of Things (IoT) and Changing Face of Project Management

Internet of Things (IoT) or Industrial Internet is a modern day catchword, which over the past few years has tremendously impacted numerous aspects of almost-all the advanced technology fields. IoT framework envisions transforming the everyday objects into intelligent systems, while working under a common infrastructure and by connecting the global network of devices and machines over the internet. Based on many underlying interdisciplinary ecosystems, like sensor network, embedded systems, big data platforms, cloud computing and service-oriented architecture; IoT projects are non-traditional in many ways. Such projects involve research and development phase, more technical work, are lengthy, require advanced skill sets and lacks well-defined business models. A recent alarming rate of IoT project failures provide incentive to look for project management philosophies, which would emphasize on more flexibility, agility, teamwork and a developing a strong technical framework. This thesis work provides overview of IoT concepts and through a systematic review of scholarly research papers, blogs, review articles, and other literature available online, it addresses the current managerial challenges for such projects. Finally, to solve this issue a focused survey was conducted and collected data was analyzed. Based on the responses from IoT professionals various suggestions are made, which can be used to improve management of such projects