Khalid Halba
Johns Hopkins University, Computer Science, Faculty Member
- Autonomous Systems, Internet of Things (IoT), Cyber Physical Systems, Digital twins, Software Defined Networks (SDN), Autonomous Underwater Vehicles, and 6 moreTelecommunications Engineering, Cisco Networking, Machine Learning, Artificial Intelligence, Generative design, and Satellite Communicationsedit
- I am currently an Associate Research Scientist at The Johns Hopkins University's Institute for Assured Autonomy. My primary objective is to utilize my skills and expertise to dr... moreI am currently an Associate Research Scientist at The Johns Hopkins University's Institute for Assured Autonomy. My primary objective is to utilize my skills and expertise to drive advancements in the automation, communications, and mission success rate of Autonomous Underwater Vehicles. I hold a PhD degree in Computer Science from Université Grenoble Alpes, France, and an Engineering Degree in Networks and Telecommunications Engineering from EMI, Rabat, Morocco. Previously, I worked as a Telecommunication Engineer at AFD, which is part of Accenture, where I gained experience in configuring and optimizing 3G/4G networks. I have also served as a scientist at NIST and JHU, contributing to the field by proposing innovations in reliability and interoperability for automotive in-vehicle networks through software-defined networks. Additionally, I have made several contributions to the field of IoT/CPS service composition and assessment, as well as the engineering, composition, formal verification, and co-simulation of IoT and cyber-physical systems.edit
Autonomous vehicles bring the promise of enhancing the consumer experience in terms of comfort and convenience and, in particular, the safety of the autonomous vehicle. Safety functions in autonomous vehicles such as Automatic Emergency... more
Autonomous vehicles bring the promise of enhancing the consumer experience in terms of comfort and convenience and, in particular, the safety of the autonomous vehicle. Safety functions in autonomous vehicles such as Automatic Emergency Braking and Lane Centering Assist rely on computation, information sharing, and the timely actuation of the safety functions. One opportunity to achieve robust autonomous vehicle safety is by enhancing the robustness of in-vehicle networking architectures that support built-in resiliency mechanisms. Software Defined Networking (SDN) is an advanced networking paradigm that allows fine-grained manipulation of routing tables and routing engines and the implementation of complex features such as failover, which is a mechanism of protecting in-vehicle networks from failure, and in which a standby link automatically takes over once the main link fails. In this paper, we leverage SDN network programmability features to enable resiliency in the autonomous vehicle realm. We demonstrate that a Software Defined In-Vehicle Networking (SDIVN) does not add overhead compared to Legacy In-Vehicle Networks (LIVNs) under non-failure conditions and we highlight its superiority in the case of a link failure and its timely delivery of messages. We verify the proposed architectures benefits using a simulation environment that we have developed and we validate our design choices through testing and simulations
As billions of IoT devices join the Internet, researchers and innovators increasingly explore IoT capabilities achieved via service composition or reuse of existing capabilities via service decomposition. Many systematic literature... more
As billions of IoT devices join the Internet, researchers and innovators increasingly explore IoT capabilities achieved via service composition or reuse of existing capabilities via service decomposition. Many systematic literature reviews (SLRs) were produced on this subject; however, two issues remain to be addressed: i) a reference taxonomy of the different aspects of IoT capabilities composition and decomposition is needed, and ii) many formal questions (e.g., standards role, formal representations applications, state-space explosion countermeasures, etc.), technical questions (e.g., composition process types and automation levels synergies, service decomposition categories, the role of AI/ML, etc.), and QoS questions (e.g., privacy, interoperability, and scalability challenges and solutions, etc.) remain unanswered. We introduce this work by discussing notions of IoT capabilities composition and decomposition in a layered IoT architecture while highlighting the strengths and weaknesses of existing SLRs. We identify unanswered questions through gaps in related work and motivate these questions using the PICOC methodology. We explain the search methodology and organize the topic questions using the proposed reference taxonomy. The identified research questions are answered, and trends and gaps that need additional attention from the research community are highlighted. This effort benefits city planners and end-users of IoT systems as it contributes to a better understanding of the role of composition and decomposition of IoT capabilities in building value-added services or reusing existing ones for resource optimization. For researchers, this effort contributes a reference taxonomy for the topic and sheds light on important questions while highlighting corresponding trends and gaps requiring further attention.
Research Interests:
As future transportation systems evolve, new in-vehicle network designs are required to handle the heterogeneous data generated by different Electronic Control Modules (ECUs). Enabling interaction between these data sources can trigger... more
As future transportation systems evolve, new in-vehicle network designs are required to handle the heterogeneous data generated by different Electronic Control Modules (ECUs). Enabling interaction between these data sources can trigger innovation and the emergence of new smart features significantly impacting upon security and riders experience. The interoperability between the ECUs is of high value in the context of autonomous transportation systems. Indeed, it enables different technologies to collaborate for achieving complex tasks. Without this interoperability, features like radar system connected to the Media Oriented Systems Transport bus (MOST) cannot trigger the electronic stability control connected to the Controller Area Network (CAN). These features allow the car to mitigate a high-risk situation using existing modules. In this work, we propose a Software Defined Network (SDN) approach that enables in-vehicle data sources interoperability that allows ECUs to share a medium. The benefits of the proposed approach are backed by the implementation of a relevant use case and the generation of simulation results.
With the increasing interest in studying Automated Driving System (ADS)-equipped vehicles through simulation, there is a growing need for comprehensive and agile middleware to provide novel Virtual Analysis (VA) functions of ADS-equipped... more
With the increasing interest in studying Automated Driving System (ADS)-equipped vehicles through simulation, there is a growing need for comprehensive and agile middleware to provide novel Virtual Analysis (VA) functions of ADS-equipped vehicles towards enabling a reliable representation for pre-deployment test. The National Institute of Standards and Technology (NIST) Universal Cyber-physical systems Environment for Federation (UCEF) is such a VA environment. It provides Application Programming Interfaces (APIs) capable of ensuring synchronized interactions across multiple simulation platforms such as LabVIEW, OMNeT++, Ricardo IGNITE, and Internet of Things (IoT) platforms. UCEF can aid engineers and researchers in understanding the impact of different constraints associated with complex cyber-physical systems (CPS). In this work UCEF is used to produce a simulated Operational Domain Design (ODD) for ADS-equipped vehicles where control (drive cycle/speed pattern), sensing (obstacle detection, traffic signs and lights), and threats (unusual signals, hacked sources) are represented as UCEF federates to simulate a drive cycle and to feed it to vehicle dynamics simulators (e.g. OpenModelica or Ricardo IGNITE) through the Functional Mock-up Interface (FMI). In this way we can subject the vehicle to a wide range of scenarios, collect data on the resulting interactions, and analyze those interactions using metrics to understand trustworthiness impact. Trustworthiness is defined here as in the NIST Framework for Cyber-Physical Systems, and is comprised of system reliability, resiliency, safety, security, and privacy. The goal of this work is to provide an example of an experimental design strategy using Fractional Factorial Design for statistically assessing the most important safety metrics in ADS-equipped vehicles.
By 2030, over a half trillion devices will be connected to the internet. With so many devices providing a wide range of features, there is a need for a framework for innovation and reuse of Internet of Things (IoT) and Cyber-Physical... more
By 2030, over a half trillion devices will be connected to the internet. With so many devices providing a wide range of features, there is a need for a framework for innovation and reuse of Internet of Things (IoT) and Cyber-Physical Systems (CPS) capabilities. Such framework should facilitate the composition of capabilities and provide stakeholders means to reliably model and verify compositions. An IoT and CPS Composition Framework (ICCF) is proposed to achieve this goal. ICCF is based on the NIST CPS framework composition guidelines, intuitive composition semantics inspired from the mPlane protocol, and strong formal verification capabilities of the Temporal Logic of Actions (TLA) formal descriptors and tools. This paper demonstrates why such framework, semantics, and formal specification and verification components form a powerful and intuitive composition framework that satisfies different stakeholders concerns. To achieve this purpose, semantics and formal specification of the composition algebra were provided, a well-being composite capability within a smart building was specified, its prototype model in a formal verification tool was run, an analysis of the results of symbolic execution quantitatively and qualitatively was performed, and assessment of the trustworthiness of the composition was done. Lastly, implementation details were provided and proposed extensions to other domains such as smart transportation and smart health were discussed.
Smart building value-added capabilities are gaining significant attention from various stakeholders, including the general public, researchers, and industry. One such capability is well-being, a composition of multiple atomic capabilities... more
Smart building value-added capabilities are gaining significant attention from various stakeholders, including the general public, researchers, and industry. One such capability is well-being, a composition of multiple atomic capabilities that characterize a smart building. Atomic functions that compose a well-being capability include temperature, noise level, pollution level, and humidity, to name a few. Multiple efforts have addressed this specific capability and its composition requirements and techniques from standardization, technical, and quality of service aspects. One such effort is the IoT and CPS Composition Framework (ICCF), a novel framework for rapid modeling, specifying, verifying, and prototyping IoT and CPS capabilities. ICCF relies on the NIST CPS Framework guidelines to address different stakeholders' concerns; it also leverages composition semantics inspired by the mPlane platform to describe entities and interactions intuitively. In addition, it uses the Temporal Logic of Actions + (TLA+) formal verification techniques to verify the correctness of core functions. This work leverages the ICCF framework to provide the following contributions: i) description of a stakeholder-defined well-being composition capability based on the ICCF framework foundations, ii) an in-depth characterization of the well-being capability, iii) considerations regarding the formal aspects of the well-being capability, including verifying its correctness, deadlock, and state-space, iv) implementation of the composite capability using a lightweight microservices environment, v) discussion of results based on the different domains of interest including residential buildings and factories. Finally, a summary of this effort is provided, and challenges to capabilities composition as well as future plans for improvement are highlighted.
By 2030, over half a trillion devices will be connected to the internet. With so many devices providing a wide range of services, a framework for prototyping, verifying, and assessing Internet of Things (IoT) and Cyber-Physical Systems... more
By 2030, over half a trillion devices will be connected to the internet. With so many devices providing a wide range of services, a framework for prototyping, verifying, and assessing Internet of Things (IoT) and Cyber-Physical Systems (CPS) capabilities is needed. Based on our research, existing IoT and CPS service composition frameworks either lack solid composition foundations that consider the various stakeholders' concerns, don't propose modeling semantics, or don't provide the means to formally verify the different states a composite system might yield. A comprehensive composition framework should facilitate the composition of capabilities and give the stakeholders means to model and verify compositions reliably. An IoT and CPS Composition Framework (ICCF) is proposed to achieve this goal. ICCF is based on the NIST CPS framework composition guidelines, mPlane-based composition semantics, and TLA-based (Temporal Logic of Actions) formal verification descriptors and tools. For experimental validation, we propose an implementation of ICCF, named IoTCaP (IoT Capabilities Platform), which takes into consideration ICCF foundations and enables the composition of novel capabilities in various domains. We have implemented ICCF in three domains of interest: Well-being in smart buildings, safety in Autonomous Driving Systems, and health improvement in Intensive Care Units.