Complex Patterns of Failure:Fault Tolerance via Complex Event Processing for IoT Systems

Fault-tolerance (FT) support is a key challenge for ensuring dependable Internet of Things (IoT) systems. Many existing FT-support mechanisms for IoT are static, tightly coupled, and inflexible, and so they struggle to provide effective support for dynamic IoT environments. This paper proposes Complex Patterns of Failure (CPoF), an approach to providing FT support for IoT systems using Complex Event Processing (CEP) that promotes modularity and reusability in FT-support design. System defects are defined using our Vulnerabilities, Faults, and Failures (VFF) framework, and error-detection strategies are defined as nondeterministic finite automata (NFA) implemented via CEP systems. We evaluated CPoF on an automated agriculture system and demonstrated its effectiveness against three types of error-detection checks: reasonableness, timing, and reversal. Using CPoF, we identified unreasonable environmental conditions and performance degradation via sensor data analysis

A Semantic loT Early Warning System for Natural Environment Crisis Management

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model.We use lightweight semantics for metadata to enhance rich sensor data acquisition.We use heavyweight semantics for top level W3CWeb Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a reployed EWS infrastructure

Honeynet Implementation in Cyber Security Attack Prevention with Data Monitoring System Using AI Technique and IoT 4G Networks

Cyber Physical Systems (CPS) comprises of the ubiquitous object concept those are connected with Internet to provide ability of data transmission and sensing over network. The smart appliances transmits the data through CPS devices with the implementation of Internet of Things (IoT) exhibits improved performance characteristics with significant advantages such as time savings, reduced cost, higher human comfort and efficient electricity utilization. In the minimal complexity sensor nodes cyber physical system is adopted for the heterogeneous environment for the wireless network connection between clients or hosts. However, the conventional security scheme uses the mechanisms for desktop devices with efficient utilization of resources in the minimal storage space environment, minimal power processing and limited energy backup. This paper proposed a Secure Honeynet key authentication (SHKA) model for security attack prevention through effective data monitoring with IoT 4G communication. The proposed SHKA model uses the lightweight key agreement scheme for authentication to provide security threats and confidentiality issues in CPS applications. With the implementation of SHKA HoneyNet model the data in IoT are monitored for security mechanism in IoT environment. The middleware module in SHKA scheme uses the Raspberry platform to establish internetworking between CPS device to achieve dynamic and scalability. The secure IoT infrastructure comprises of flexible evaluation of user-centric environment evaluation for the effectiveness. The developed SHKA model perform mutual authentication between CPS devices for minimal computation overhead and efficiency. The wireless channel uses the dynamic session key for the secure communication for cyber-attacks security with lightweight security in CPS system. The SHKA model demonstrate the effectiveness based on consideration of three constraints such as low power processing, reduced storage and minimal backup energy. Experimental analysis stated that proposed SHKA scheme provides lightweight end-to-end key establishment in every session. The CPS devices generates the session key of 128 bit long. The minimum key size is implemented to provide effective security in IoT 4G communication with minimal execution time. The simulation results demonstrated that SHKA model exhibits effective cyber-attacks for the constraint devices to improve performance of IoT network

City Data Fusion: Sensor Data Fusion in the Internet of Things

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

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