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

Quality assessment technique for ubiquitous software and middleware

The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future

ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT.

Most computation-intensive industry applications and servers encounter service-reliability challenges due to the limited resource capability of the edge. Achieving quality data fusion and accurate service reliability with optimized service-x execution cost is challenging. While existing systems have taken into account factors such as device service execution, residual resource ratio, and channel condition; the service execution time, cost, and utility ratios of requested services from devices and servers also have a significant impact on service execution cost. To enhance service quality and reliability, we design a 2-step adaptive service-X cost consolidation (ASXC 2) approach. This approach is based on the node-centric Lyapunov method and distributed Markov mechanism, aiming to optimize the service execution error rate during offloading. The node-centric Lyapunov method incorporates cost and utility functions and node-centric features to estimate the service cost before offloading. Additionally, the Markov mechanism-inspired service latency prediction model design assists in mitigating the ratio of offload-service execution errors by establishing a mobility-correlation matrix between devices and servers. In addition, the non-linear programming multi-tenancy heuristic method design help to predict the service preferences for improving the resource utilisation ratio. The simulations show the effectiveness of our approach. The model performance is enhanced with 0.13% service offloading efficiency, 0.82% rate of service completion when transmitting data size is 400 kb, and 0.058% average service offloading efficiency with 40 CPU Megacycles when the vehicle moves 60 Km/h speed around the server communication range. Our model simulations indicate that our approach is highly effective and suitable for lightweight, complex environments

Robust, Resilient and Reliable Architecture for V2X Communication

The new developments in mobile edge computing (MEC) and vehicle-to-everything (V2X) communications has positioned 5G and beyond in a strong position to answer the market need towards future emerging intelligent transportation systems and smart city applications. The major attractive features of V2X communication is the inherent ability to adapt to any type of network, device, or data, and to ensure robustness, resilience and reliability of the network, which is challenging to realize. In this work, we propose to drive these further these features by proposing a novel robust, resilient and reliable architecture for V2X communication based on harnessing MEC and blockchain technology. A three stage computing service is proposed. Firstly, a hierarchcial computing architecture is deployed spanning over the vehicular network that constitutes cloud computing (CC), edge computing (EC), fog computing (FC) nodes. The resources and data bases can migrate from the high capacity cloud services (furthest away from the individual node of the network) to the edge (medium) and low level fog node, according to computing service requirements. Secondly, the resource allocation filters the data according to its significance, and rank the nodes according to their usability, and selects the network technology according to their physical channel characteristics. Thirdly, we propose a blockchain-based transaction service that ensures reliability. We discussed two use cases for experimental analysis, plug- in electric vehicles in smart grid scenarios, and massive IoT data services for autonomous cars. The results show that car connectivity prediction is accurate 98% of the times, where 92% more data blocks are added using micro-blockchain solution compared to the public blockchain, where it is able to reduce the time to sign and compute the proof-of-work (PoW), and deliver a low-overhead Proof-of-Stake (PoS) consensus mechanism. This approach can be considered a strong candidate architecture for future V2X, and with more general application for everything- to-everything (X2X) communications

An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

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