Design and Evaluation of IoT-Enabled Instrumentation for a Soil-Bentonite Slurry Trench Cutoff Wall

In this work, we describe our approach and experiences bringing an instrumented soil-bentonite slurry trench cutoff wall into a modern IoT data collection and visualization pipeline. Soil-bentonite slurry trench cutoff walls have long been used to control ground water flow and contaminant transport. A Raspberry Pi computer on site periodically downloads the sensor data over a serial interface from an industrial datalogger and transmits the data wirelessly to a gateway computer located 1.3 km away using a reliable transmission protocol. The resulting time-series data is stored in a MongoDB database and data is visualized in real-time by a custom web application. The system has been in operation for over two years achieving 99.42% reliability and no data loss from the collection, transport, or storage of data. This project demonstrates the successful bridging of legacy scientific instrumentation with modern IoT technologies and approaches to gain timely web-based data visualization facilitating rapid data analysis without negatively impacting data integrity or reliability. The instrumentation system has proven extremely useful in understanding the changes in the stress state over time and could be deployed elsewhere as a means of on-demand slurry trench cutoff wall structural health monitoring for real-time stress detection linked to hydraulic conductivity or adapted for other infrastructure monitoring applications

The Minimum Scheduling Time for Convergecast in Wireless Sensor Networks

We study the scheduling problem for data collection from sensor nodes to the sink node in wireless sensor networks, also referred to as the convergecast problem. The convergecast problem in general network topology has been proven to be NP-hard. In this paper, we propose our heuristic algorithm (finding the minimum scheduling time for convergecast (FMSTC)) for general network topology and evaluate the performance by simulation. The results of the simulation showed that the number of time slots to reach the sink node decreased with an increase in the power. We compared the performance of the proposed algorithm to the optimal time slots in a linear network topology. The proposed algorithm for convergecast in a general network topology has 2.27 times more time slots than that of a linear network topology. To the best of our knowledge, the proposed method is the first attempt to apply the optimal algorithm in a linear network topology to a general network topology

BARI+: A Biometric Based Distributed Key Management Approach for Wireless Body Area Networks

Wireless body area networks (WBAN) consist of resource constrained sensing devices just like other wireless sensor networks (WSN). However, they differ from WSN in topology, scale and security requirements. Due to these differences, key management schemes designed for WSN are inefficient and unnecessarily complex when applied to WBAN. Considering the key management issue, WBAN are also different from WPAN because WBAN can use random biometric measurements as keys. We highlight the differences between WSN and WBAN and propose an efficient key management scheme, which makes use of biometrics and is specifically designed for WBAN domain

A Component-based Approach for Service Distribution in Sensor Networks

ABSTRACT The increasing number of distributed applications over Wireless Sensor Networks (WSNs) in ubiquitous environments raises the need for high-level mechanisms to distribute sensor services and integrate them in modern IT systems. Existing work in this area mostly focuses on low-level networking issues, and fails to provide high-level and off-the-shelf programming abstractions for this purpose. In this paper, we therefore consider WSN programming models and service distribution as two interrelated factors and we present a new component-based abstraction for integrating WSNs within existing IT systems. Our approach emphasizes on reifying distribution strategies at the software architecture level, thus allowing remote invocation of component services, and facilitating interoperability of sensor services with the Internet through Web service-enabled components. The latter is efficiently provided by incorporating the REST architectural style-emphasizing on abstraction of high-level services as resources-to our component-based framework. The preliminary evaluation results show that the proposed framework has an acceptable memory overhead on a TelosB sensor platform

Commodity single board computer clusters and their applications

© 2018 Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked together, to create small, low-cost clusters that replicate some features of large data center clusters. The Raspberry Pi Foundation produces a series of SBCs with a price/performance ratio that makes SBC clusters viable, perhaps even expendable. These clusters are an enabler for Edge/Fog Compute, where processing is pushed out towards data sources, reducing bandwidth requirements and decentralizing the architecture. In this paper we investigate use cases driving the growth of SBC clusters, we examine the trends in future hardware developments, and discuss the potential of SBC clusters as a disruptive technology. Compared to traditional clusters, SBC clusters have a reduced footprint, are low-cost, and have low power requirements. This enables different models of deployment—particularly outside traditional data center environments. We discuss the applicability of existing software and management infrastructure to support exotic deployment scenarios and anticipate the next generation of SBC. We conclude that the SBC cluster is a new and distinct computational deployment paradigm, which is applicable to a wider range of scenarios than current clusters. It facilitates Internet of Things and Smart City systems and is potentially a game changer in pushing application logic out towards the network edge

Enforcing Behavioral Profiles through Software-Defined Networks in the Industrial Internet of Things

The fourth industrial revolution is being mainly driven by the integration of Internet of Things (IoT) technologies to support the development lifecycle of systems and products. Despite the well-known advantages for the industry, an increasingly pervasive industrial ecosystem could make such devices an attractive target for potential attackers. Recently, the Manufacturer Usage Description (MUD) standard enables manufacturers to specify the intended use of their devices, thereby restricting the attack surface of a certain system. In this direction, we propose a mechanism to manage securely the obtaining and enforcement of MUD policies through the use of a Software-Defined Network (SDN) architecture. We analyze the applicability and advantages of the use of MUD in industrial environments based on our proposed solution, and provide an exhaustive performance evaluation of the required processes

Alternative opportunistic alert diffusion to support infrastructure failure during disasters

International audienceOpportunistic communications present a promising solution for disaster network recovery in emergency situations such as hurricanes, earthquakes, and floods, where infrastructure might be destroyed. Some recent works in the literature have proposed opportunistic-based disaster recovery solutions, but they have omitted the consideration of mobile devices that come with different network technologies and various initial energy levels. This work presents COPE, an energy-aware Cooperative OPportunistic alErt diffusion scheme for trapped survivors to use during disaster scenarios to report their position and ease their rescue operation. It aims to maintain mobile devices functional for as long as possible for maximum network coverage until reaching proximate rescuers. COPE deals with mobile devices that come with an assortment of networks and aims to perform systematic network interface selection. Furthermore, it considers mobile devices with various energy levels and allows low-energy nodes to hold their charge for longer time with the support of high-energy nodes. A proof-of-concept implementation has been performed to study the doability and efficiency of COPE, and to highlight the lessons learned

Abstracting Application Development for Resource Constrained Wireless Sensor Networks

Ubiquitous computing is a concept whereby computing is distributed across smart objects surrounding users, creating ambient intelligence. Ubiquitous applications use technologies such as the Internet, sensors, actuators, embedded computers, wireless communication, and new user interfaces. The Internet-of-Things (IoT) is one of the key concepts in the realization of ubiquitous computing, whereby smart objects communicate with each other and the Internet. Further, Wireless Sensor Networks (WSNs) are a sub-group of IoT technologies that consist of geographically distributed devices or nodes, capable of sensing and actuating the environment.WSNs typically contain tens to thousands of nodes that organize and operate autonomously to perform application-dependent sensing and sensor data processing tasks. The projected applications require nodes to be small in physical size and low-cost, and have a long lifetime with limited energy resources, while performing complex computing and communications tasks. As a result, WSNs are complex distributed systems that are constrained by communications, computing and energy resources. WSN functionality is dynamic according to the environment and application requirements. Dynamic multitasking, task distribution, task injection, and software updates are required in field experiments for possibly thousands of nodes functioning in harsh environments.The development of WSN application software requires the abstraction of computing, communication, data access, and heterogeneous sensor data sources to reduce the complexities. Abstractions enable the faster development of new applications with a better reuse of existing software, as applications are composed of high-level tasks that use the services provided by the devices to execute the application logic.The main research question of this thesis is: What abstractions are needed for application development for resource constrained WSNs? This thesis models WSN abstractions with three levels that build on top of each other: 1) node abstraction, 2) network abstraction, and 3) infrastructure abstraction. The node abstraction hides the details in the use of the sensing, communication, and processing hardware. The network abstraction specifies methods of discovering and accessing services, and distributing processing in the network. The infrastructure abstraction unifies different sensing technologies and infrastructure computing platforms.As a contribution, this thesis presents the abstraction model with a review of each abstraction level. Several designs for each of the levels are tested and verified with proofs of concept and analyses of field experiments. The resulting designs consist of an operating system kernel, a software update method, a data unification interface, and all abstraction levels combining abstraction called an embedded cloud.The presented operating system kernel has a scalable overhead and provides a programming approach similar to a desktop computer operating system with threads and processes. An over-the-air update method combines low overhead and robust software updating with application task dissemination. The data unification interface homogenizes the access to the data of heterogeneous sensor networks. A unification model is used for various use cases by mapping everything as measurements. The embedded cloud allows resource constrained WSNs to share services and data, and expand resources with other technologies. The embedded cloud allows the distributed processing of applications according to the available services. The applications are implemented as processes using a hardware independent description language that can be executed on resource constrained WSNs. The lessons of practical field experimenting are analyzed to study the importance of the abstractions. Software complexities encountered in the field experiments highlight the need for suitable abstractions.The results of this thesis are tested using proof of concept implementations on real WSN hardware which is constrained by computing power in the order of a few MIPS, memory sizes of a few kilobytes, and small sized batteries. The results will remain usable in the future, as the vast amount, tight integration, and low-cost of future IoT devices require the combination of complex computation with resource constrained platforms

Operating systems for wireless sensor networks: A survey

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes' life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems