A Large-Scale Software-Defined Internet of Things Platform for Provisioning IoT Services on Demand

University of Technology Sydney. Faculty of Engineering and Information Technology.Internet of Things (IoT) has developed into an interconnected platform infrastructure for providing essential services ranging from personal health care, smart homes and cities to the manufacturing industry. Relying on such an infrastructure, a multitude of emerging IoT services will no doubt be developed for not only local regions but also multiple separated regions spreading over a wide geographical area. However, existing IoT systems are mostly rigid and cannot be easily adapted or programmed to accommodate new services. The challenge is also in orchestrating a large number of sensors/IoT devices, many with limited capability, into intelligent, useful, and on-demand services. Many efforts have been made to address the issue, but very little has been attempted to consider an overall solution to a programmable IoT ecosystem that includes IoT service provision components, IoT devices, and transporting infrastructure. Moreover, there is no framework/platform that allows an end-to-end control, management, and orchestration of IoT resources in accordance with IoT demands. We apply the benefits of the two promising technologies including software-defined networking and network function virtualization in provisioning IoT services on demand over a wide region, and overcome challenges in applying the technologies to constrained IoT devices/systems. We propose a large-scale software-defined IoT (LSSD-IoT) model and develop the LSSD-IoT platform. The model provides two levels of management and orchestration at the cluster and device level. At the cluster level, we develop a software-defined Internet of Things Cluster (SD-IoTC) controller that is capable of controlling and managing both IoT clusters and network infrastructure that accommodates the IoT systems. At the device level, each IoT cluster under the control and management of the SD-IoTC controller needs to be programmable and manageable for provisioning IoT services on demand. For that purpose, we propose a software-defined Internet of Things (SD-IoT) model (local platform) with three novel components, including the IoT device-constrained controller, the S-MANAGE protocol, and the software-defined virtual sensor. The novelty of this research lies in the novel approach to programmable and re-usable devices in the provision of IoT services on demand over a wide area. It enables i) IoT service providers to control end-to-end quality of services of IoT services provision over a large-scale IoT environment; ii) owners of IoT systems to be able to gain benefits from sharing their IoT resources; iii) IoT application developers to develop innovative and comprehensive IoT applications on demand with more options regarding QoS, security, mobility, or billing

Software defined wireless sensor networks application opportunities for efficient network management : a survey

Wireless Sensor Networks (WSNs) are commonly used information technologies of modern networking and computing platforms. Today's network computing applications are faced with a high demand of powerful network functionalities. Functional network reach is central to customer satisfaction such as in mobile networks and cloud computing environments. However, efficient management of WSNs remains a challenge, due to problems supplemental to them. Recent technology shift proposes Software Defined Networking (SDN) for improving computing networks. This review paper highlights application challenges faced by WSNs for monitored environments and those faced by the proposed approaches, as well as opportunities that can be realized on applications of WSNs using SDN. We also highlight Implementation considerations by focusing on critical aspects that should not be disregarded when attempting to improve network functionalities. We then propose a strategy for Software Defined Wireless Sensor Network (SDWSN) as an effort for application improvement in monitored environments.The National Research Foundation (NRF) of South Africa (grant number: RDYR160404161474 and IFR160118156967).http://www.elsevier.com/locate/compeleceng2019-02-01hj2018Electrical, Electronic and Computer Engineerin

Flexible network management in software defined wireless sensor networks for monitoring application systems

Wireless Sensor Networks (WSNs) are the commonly applied information technologies of modern networking and computing platforms for application-specific systems. Today’s network computing applications are faced with high demand of reliable and powerful network functionalities. Hence, efficient network performance is central to the entire ecosystem, more especially where human life is a concern. However, effective management of WSNs remains a challenge due to problems supplemental to them. As a result, WSNs application systems such as in monitored environments, surveillance, aeronautics, medicine, processing and control, tend to suffer in terms of capacity to support compute intensive services due to limitations experienced on them. A recent technology shift proposes Software Defined Networking (SDN) for improving computing networks as well as enhancing network resource management, especially for life guarding systems. As an optimization strategy, a software-oriented approach for WSNs, known as Software Defined Wireless Sensor Network (SDWSN) is implemented to evolve, enhance and provide computing capacity to these resource constrained technologies. Software developmental strategies are applied with the focus to ensure efficient network management, introduce network flexibility and advance network innovation towards the maximum operation potential for WSNs application systems. The need to develop WSNs application systems which are powerful and scalable has grown tremendously due to their simplicity in implementation and application. Their nature of design serves as a potential direction for the much anticipated and resource abundant IoT networks. Information systems such as data analytics, shared computing resources, control systems, big data support, visualizations, system audits, artificial intelligence (AI), etc. are a necessity to everyday life of consumers. Such systems can greatly benefit from the SDN programmability strategy, in terms of improving how data is mined, analysed and committed to other parts of the system for greater functionality. This work proposes and implements SDN strategies for enhancing WSNs application systems especially for life critical systems. It also highlights implementation considerations for designing powerful WSNs application systems by focusing on system critical aspects that should not be disregarded when planning to improve core network functionalities. Due to their inherent challenges, WSN application systems lack robustness, reliability and scalability to support high computing demands. Anticipated systems must have greater capabilities to ubiquitously support many applications with flexible resources that can be easily accessed. To achieve this, such systems must incorporate powerful strategies for efficient data aggregation, query computations, communication and information presentation. The notion of applying machine learning methods to WSN systems is fairly new, though carries the potential to enhance WSN application technologies. This technological direction seeks to bring intelligent functionalities to WSN systems given the characteristics of wireless sensor nodes in terms of cooperative data transmission. With these technological aspects, a technical study is therefore conducted with a focus on WSN application systems as to how SDN strategies coupled with machine learning methods, can contribute with viable solutions on monitoring application systems to support and provide various applications and services with greater performance. To realize this, this work further proposes and implements machine learning (ML) methods coupled with SDN strategies to; enhance sensor data aggregation, introduce network flexibility, improve resource management, query processing and sensor information presentation. Hence, this work directly contributes to SDWSN strategies for monitoring application systems.Thesis (PhD)--University of Pretoria, 2018.National Research Foundation (NRF)Telkom Centre of ExcellenceElectrical, Electronic and Computer EngineeringPhDUnrestricte

A survey on software-defined wireless sensor networks : challenges and design requirements

Software defined networking (SDN) brings about innovation, simplicity in network management, and configuration in network computing. Traditional networks often lack the flexibility to bring into effect instant changes because of the rigidity of the network and also the over dependence on proprietary services. SDN decouples the control plane from the data plane, thus moving the control logic from the node to a central controller. A wireless sensor network (WSN) is a great platform for low-rate wireless personal area networks with little resources and short communication ranges. However, as the scale of WSN expands, it faces several challenges, such as network management and heterogeneous-node networks. The SDN approach to WSNs seeks to alleviate most of the challenges and ultimately foster efficiency and sustainability in WSNs. The fusion of these two models gives rise to a new paradigm: Software defined wireless sensor networks (SDWSN). The SDWSN model is also envisioned to play a critical role in the looming Internet of Things paradigm. This paper presents a comprehensive review of the SDWSN literature. Moreover, it delves into some of the challenges facing this paradigm, as well as the major SDWSN design requirements that need to be considered to address these challenges.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639hb2017Electrical, Electronic and Computer Engineerin

Internet of things security: A top-down survey

International audienceInternet of Things (IoT) is one of the promising technologies that has attracted a lot of attention in both industrial and academic fields these years. It aims to integrate seamlessly both physical and digital worlds in one single ecosystem that makes up a new intelligent era of Internet. This technology offers a huge business value for organizations and provides opportunities for many existing applications such as energy, healthcare and other sectors. However, as new emergent technology, IoT suffers from several security issues which are most challenging than those from other fields regarding its complex environment and resources-constrained IoT devices. A lot of researches have been initiated in order to provide efficient security solutions in IoT, particularly to address resources constraints and scalability issues. Furthermore, some technologies related to networking and cryptocurrency fields such as Software Defined Networking (SDN) and Blockchain are revolutionizing the world of the Internet of Things thanks to their efficiency and scalability. In this paper, we provide a comprehensive top down survey of the most recent proposed security and privacy solutions in IoT. We discuss particularly the benefits that new approaches such as blockchain and Software Defined Networking can bring to the security and the privacy in IoT in terms of flexibility and scalability. Finally, we give a general classification of existing solutions and comparison based on important parameters

Architecture of software defined cluster wireless sensor network of coal mine

For no guarantee of communication reliability of traditional coal mine wireless sensor network under accident condition because static route protocol cannot change route according to network states, an architecture of software defined cluster wireless sensor network of coal mine was designed by adding gateway nodes in cluster of coal mine wireless sensor network based on software defined network system and characteristic of the cluster topology. In the architecture, the gateway nodes in each domain collect data of sensor nodes for intra-domain or inter-domain communication, and controller manages flow, route and safety of the domain. Wireless sensor network based on the architecture can change route according to network states, which is suitable for coal mine safety monitoring

A software-defined network based lightweight cluster Yazilim-tanimli aǧ destekli hafif siklet bir küme

The objective of this project is to show that the Software-Defined Networking concept demonstrated by using the UDOOBoard development kit can be served with various configurations. Besides this, although small-scale development kits are very popular, their usage areas are restricted to amateur and personal development applications. In this work, we aimed at building up a lightweight experimentation environment for hardware development kits with Linux support. As a future work, the results of this study can be ported into a physical environment. It is shown that UDOOBoards can be used in a software-defined cluster network. Three different clustering substructures are studied and their results are presented