Harnessing single board computers for military data analytics

Executive summary: This chapter covers the use of Single Board Computers (SBCs) to expedite onsite data analytics for a variety of military applications. Onsite data summarization and analytics is increasingly critical for command, control, and intelligence (C2I) operations, as excessive power consumption and communication latency can restrict the efficacy of down-range operations. SBCs offer power-efficient, inexpensive data-processing capabilities while maintaining a small form factor. We discuss the use of SBCs in a variety of domains, including wireless sensor networks, unmanned vehicles, and cluster computing. We conclude with a discussion of existing challenges and opportunities for future use.https://digitalcommons.usmalibrary.org/books/1010/thumbnail.jp

Building real-time embedded applications on QduinoMC: a web-connected 3D printer case study

Single Board Computers (SBCs) are now emerging with multiple cores, ADCs, GPIOs, PWM channels, integrated graphics, and several serial bus interfaces. The low power consumption, small form factor and I/O interface capabilities of SBCs with sensors and actuators makes them ideal in embedded and real-time applications. However, most SBCs run non-realtime operating systems based on Linux and Windows, and do not provide a user-friendly API for application development. This paper presents QduinoMC, a multicore extension to the popular Arduino programming environment, which runs on the Quest real-time operating system. QduinoMC is an extension of our earlier single-core, real-time, multithreaded Qduino API. We show the utility of QduinoMC by applying it to a specific application: a web-connected 3D printer. This differs from existing 3D printers, which run relatively simple firmware and lack operating system support to spool multiple jobs, or interoperate with other devices (e.g., in a print farm). We show how QduinoMC empowers devices with the capabilities to run new services without impacting their timing guarantees. While it is possible to modify existing operating systems to provide suitable timing guarantees, the effort to do so is cumbersome and does not provide the ease of programming afforded by QduinoMC.http://www.cs.bu.edu/fac/richwest/papers/rtas_2017.pdfAccepted manuscrip

Intelligent Systems Development in a Non Engineering Curriculum

Much of computer system development today is programming in the large - systems of millions of lines of code distributed across servers and the web. At the same time, microcontrollers have also become pervasive in everyday products, economical to manufacture, and represent a different level of learning about system development. Real world systems at this level require integrated development of custom hardware and software. How can academic institutions give students a view of this other extreme - programming on small microcontrollers with specialized hardware? Full scale system development including custom hardware and software is expensive, beyond the range of any but the larger engineering oriented universities, and hard to fit into a typical length course. The course described here is a solution using microcontroller programming in high level language, small hardware components, and the Arduino open source microcontroller. The results of the hands-on course show that student programmers with limited hardware knowledge are able to build custom devices, handle the complexity of basic hardware design, and learn to appreciate the differences between large and small scale programming

Enterprise platform systems management security threats and mitigation techniques

Developers and technologists of enterprise systems such as servers, storage and networking products must constantly anticipate new cybersecurity threats and evolving security requirements. These requirements are typically sourced from marketing, customer expectations, manufacturing and evolving government standards. Much ongoing major research focus has been on securing the main enterprise system purpose functionality, operating system, network and storage. There appears, however, to be far less research and a growing number of reports of vulnerabilities in the area of enterprise systems management hardware and software subsystems. Many recent examples are within types of subsystems such as baseboard management controllers (BMCs), which are intricate embedded subsystems, independent of the host server system functionality. A BMC is typically comprised of a specialized system-on-a-chip, RAM, non-volatile storage, and sensors, and runs an embedded LINUX Operating System. The BMC’s primary roles are always increasing in scope including managing system inventory, system operational health, thermal and power control, event logging, remote console access, provisioning, performance monitoring, software updates and failure prediction and remediation. To compromise or create a denial of service of such subsystems has an increasing impact on equipment manufacturers and large and small enterprises. This report’s primary objective is to research real-world and theoretical hardware and software cyber-attack vectors on enterprise product platforms, inclusive of BMCs, BIOS and other embedded systems within such products. For each presented attack vector, best practices and suggestions for effective avoidance and mitigation are explored. Domains of particular interest are physical access security, hardware manipulation and secure boot protections against software image manipulation, BIOS recovery and secure field debug techniques.Electrical and Computer Engineerin

Teaching the Internet of Things: Bridging a Path from CPE329

“The ability to connect, communicate with, and remotely manage an incalculable number of networked, automated devices via the Internet is becoming pervasive, from the commercial kitchen to the residential basement room to the arm of the fitness buff.” - WSO2 In this report, we will investigate procedures and technologies used in IoT. A variety of cloud platforms will be described to demonstrate its strengths and usage on IoT applications. Furthermore, demonstrate the most popular hardware being used in several of these applications. This report is aimed to give a good understanding on what it takes to put together an IoT application from from choosing the appropriate hardware to choosing the right cloud platform. A thorough analysis has been done in order to help users choose the right hardware, communication protocol and cloud platform to deploy an application to the cloud. As Internet of Things is still a developing field, the information here may become outdated or even drastically altered, and new standardizations may arise

Facilitating the creation of IoT applications through conditional observations in CoAP

With the advent of IPv6, the world is getting ready to incorporate smart objects to the current Internet to realize the idea of Internet of Things. The biggest challenge faced is the resource constraint of the smart objects to directly utilize the existing standard protocols and applications. A number of initiatives are currently witnessed to resolve this situation. One of such initiatives is the introduction of Constrained Application Protocol. This protocol is developed to fit in the resource-constrained smart object with the ability to easily translate to the prominent representational state transfer implementation, hypertext transfer protocol (and vice versa). The protocol has several optional extensions, one of them being, resource observation. With resource observation, a client may ask a server to be notified every state change of the resource. However, in many applications, all state changes are not significant enough for the clients. Therefore, the client will have to decide whether to use a value sent by a server or not. This results in wastage of the already constrained resources (bandwidth, processing power,aEuro broken vertical bar). In this paper, we introduced an alternative to the normal resource observation function, named Conditional Observation, where clients tell the servers the criteria for notification. We evaluated the power consumption and number of packets transmitted between clients and servers by using different network sizes and number of servers. In all cases, we found out that the existing observe option results in excessive number of packets (most of them unimportant for the client) and higher power consumption. We also made an extensive theoretical evaluation of the two approaches which give consistent result with the results we got from experimentation

Sensor function virtualization to support distributed intelligence in the internet of things

It is estimated that-by 2020-billion devices will be connected to the Internet. This number not only includes TVs, PCs, tablets and smartphones, but also billions of embedded sensors that will make up the "Internet of Things" and enable a whole new range of intelligent services in domains such as manufacturing, health, smart homes, logistics, etc. To some extent, intelligence such as data processing or access control can be placed on the devices themselves. Alternatively, functionalities can be outsourced to the cloud. In reality, there is no single solution that fits all needs. Cooperation between devices, intermediate infrastructures (local networks, access networks, global networks) and/or cloud systems is needed in order to optimally support IoT communication and IoT applications. Through distributed intelligence the right communication and processing functionality will be available at the right place. The first part of this paper motivates the need for such distributed intelligence based on shortcomings in typical IoT systems. The second part focuses on the concept of sensor function virtualization, a potential enabler for distributed intelligence, and presents solutions on how to realize it