Mangharam, Rahul
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Introduction
Rahul's focus is on the development of life-critical and safety-critical real-time embedded systems in medical devices, automotive electronics, wireless control networks and energy-efficient buildings. He directs mLAB
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Now showing 1 - 10 of 115
Publication AUTOPLUG: An Architecture for Remote Electronic Controller Unit Diagnostics in Automotive Systems(2012-01-01) Pant, Yash Vardhan; Pajic, Miroslav; Mangharam, RahulIn 2010, over 20.3 million vehicles were recalled. Software issues related to automotive controls such as cruise control, anti-lock braking system, traction control and stability control, account for an increasingly large percentage of the overall vehicles recalled. There is a need for new and scalable methods to evaluate automotive controls in a realistic and open setting. We have developed AutoPlug, an automotive Electronic Controller Unit (ECU) architecture between the vehicle and a Remote Diagnostics Center to diagnose, test, update and verify controls software. Within the vehicle, we evaluate observerbased runtime diagnostic schemes and introduce a framework for remote management of vehicle recalls. The diagnostics scheme deals with both real-time and non-real time faults, and we introduce a decision function to detect and isolate faults in a system with modeling uncertainties. We also evaluate the applicability of “Opportunistic Diagnostics”, where the observerbased diagnostics are scheduled in the ECU’s RTOS only when there is slack available in the system. This aperiodic diagnostics scheme performs similar to the standard, periodic diagnostics scheme under reasonable assumptions. This approach works on existing ECUs and does not interfere with current task sets. The overall framework integrates in-vehicle and remote diagnostics and serves to make vehicle recalls management a less reactive and cost-intensive procedure.Publication Architecture for a Fully Distributed Wireless Control Network(2011-04-12) Pajic, Miroslav; Aneja, Mansimar; Vemuri, Srinivas; Pappas, George; Mangharam, Rahul; Sundaram, ShreyasWe demonstrate a distributed scheme for control over wireless networks. In our previous work, we introduced the concept of a Wireless Control Network (WCN), where the network itself, with no centralized node, acts as the controller. In this demonstration, we show how the WCN can be utilized for distillation column control, a well-known process control problem. To illustrate the use of a WCN, we have utilized a process-in-the-loop simulation, where the behavior of a distillation column was simulated in Simulink and interfaced with an actual, physical network (used as the control network), which consists of several wireless nodes, sensors and actuators. The goal of this demonstration is to show the benefits of a fully-distributed robust wireless control/actuator network, which include simple scheduling, scalability and compositionality.Publication Sometimes, Money Does Grow on Trees: DR-Advisor, A Data Driven Demand Response Recommender System(2015-09-01) Behl, Madhur; Mangharam, RahulUnprecedented amounts of information from millions of smart meters and thermostats installed in recent years has left the door open for better understanding, analyzing and using the insights that data can provide, about the power consumption patterns of a building. The challenge with using data-driven approaches, is to close the loop for near real-time control and decision making in large buildings. Furthermore, providing a technological solution alone is not enough, the solution must also be human centric. We consider the problem of end-user demand response for commercial buildings. Using historical data from the building, we build a family of regression trees based models for predicting the power consumption of the building in real-time. We have built DR-Advisor, a recommender system for the building's facilities manager, which provides optimal control actions to meet the required load curtailment while maintaining building operations and maximizing the economic reward.Publication Towards Synthesis of Platform-Aware Attack-Resilient Control Systems: Extended Abstract(2013-04-09) Pajic, Miroslav; Bezzo, Nicola; Weimer, James; Alur, Rajeev; Mangharam, Rahul; Michael, Nathan; Pappas, George J; Sokolsky, Oleg; Tabuada, Paulo; Weirich, Stephanie; Lee, InsupPublication Real-time Heart Model for Implantable Cardiac Device Validation and Verification(2010-01-20) Jiang, Zhihao; Pajic, Miroslav; Connolly, Allison T; Dixit, Sanjay; Mangharam, RahulDesigning bug-free medical device software is dif- ficult, especially in complex implantable devices that may be used in unanticipated contexts. Safety recalls of pacemakers and implantable cardioverter defibrillators due to firmware problems between 1990 and 2000 affected over 200,000 devices, comprising 41% of the devices recalled and are increasing in frequency. There is currently no formal methodology or open experimental platform to validate and verify the correct operation of medical device software. To this effect, a real-time Virtual Heart Model (VHM) has been developed to model the electrophysiological operation of the functioning (i.e. during normal sinus rhythm) and malfunctioning (i.e. during arrhythmia) heart. We present a methodology to extract timing properties of the heart to construct a timed-automata model. The platform exposes functional and formal interfaces for validation and verification of implantable cardiac devices. We demonstrate the VHM is capable of generating clinically-relevant response to intrinsic (i.e. premature stimuli) and external (i.e. artificial pacemaker) signals for a variety of common arrhythmias. By connecting the VHM with a pacemaker model, we are able to pace and synchronize the heart during the onset of irregular heart rhythms. The VHM has also been implemented on a hardware platform for closed-loop experimentation with existing and virtual medical devices. The VHM allows for exploratory electrophysiology studies for physicians to evaluate their diagnosis and determine the appropriate device therapy. This integrated functional and formal device design approach will potentially help expedite medical device certification for safer operation.Publication Green Scheduling for Radiant Systems in Buildings(2012-10-01) Nghiem, Truong X; Behl, Madhur; Pappas, George J.; Mangharam, RahulIn this report we look at the problem of peak power reduction for buildings with electric radiant floor heating systems. Uncoordinated operation of a multi-zone radiant floor heating system can result in temporally correlated electricity demand surges or peaks in the building’s electricity consumption. As peak power prices are 200-400 times that of the nominal rate, this uncoordinated activity can result in high electricity costs and expensive system operation. We have previously presented green scheduling as an approach for reducing the aggregate peak power consumption in buildings while ensuring that indoor thermal comfort is always maintained. This report extends the theoretical results for general affine dynamical systems and applies them to electric radiant floor heating systems. The potential of the proposed method in reducing the peak power demand is demonstrated for a small-scale system through simulation in EnergyPlus and for a large-scale system through simulation in Matlab.Publication Optimizing Transmission and Shutdown for Energy-Efficient Real-Time Packet Scheduling in Clustered Ad Hoc Networks(2005-01-01) Pollin, Sofie; Bougard, Bruno; Mangharam, Rahul; Catthoor, Francky; Moerman, Ingrid; Rajkumar, Ragunathan; Van der Perre, LiesbetEnergy efficiency is imperative to enable the deployment of ad hoc networks. Conventional power management focuses independently on the physical orMAC layer and approaches differ depending on the abstraction level. At the physical layer, the fundamental tradeoff between transmission rate and energy is exploited, which leads to transmit as slow as possible. At MAC level, power reduction techniques aim to transmit as fast as possible to maximize the radios power-off interval. The two approaches seem conflicting and it is not obvious which one is the most appropriate.We propose a transmission strategy that optimally mixes both techniques in a multiuser context.We present a cross-layer solution considering the transceiver power characteristics, the varying system load, and the dynamic channel constraints. Based on this, we derive a low-complexity online scheduling algorithm. Results considering an M-ary quadrature amplitude modulation radio show that for a range of scenarios a large power reduction is achieved, compared to the case where only scaling or shutdown is considered.Publication The Car and The Cloud: Automotive Architectures for 2020(2012-11-01) Mangharam, RahulThree trends are emerging in drivers’ expectations for their vehicle: (1) continuous connectivity with both the infrastructure (e.g., smart traffic intersections) and other commuters, (2) enhanced levels of productivity and entertainment for the duration of travel, and (3) reduction in cognitive load through semiautonomous operation and automated congestion-aware route planning. To address these demands, vehicles should become more programmable so that almost every aspect of engine control, cabin comfort, connectivity, navigation, and safety will be remotely upgradable and designed to evolve over the lifetime of the vehicle. Progress toward the vehicle of the future will entail new approaches in the design and sustainability of vehicles so that they are connected to networked traffic systems and are programmable over the course of their lifetime. To that end, our automotive research team at the University of Pennsylvania is devel- oping an in-vehicle programmable system, AutoPlug, an automotive architecture for remote diagnostics, testing, and code updates for dispatch from a datacenter to vehicle electronic controller units. For connected vehicles, we are implementing a networked vehicle platform, GrooveNet, that allows communication between real and simulated vehicles to evaluate the feasibility and application of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication; the focus in this paper is on its application to safety. Finally, we are working on a tool for large-scale traffic congestion analysis, AutoMatrix, capable of simulating over 16 million vehicles on any US street map and computing real-time fastest paths for a large subset of vehicles. The tools and platforms described here are free and open-source from the author.Publication Anytime Algorithms for GPU Architectures(2011-11-01) Mangharam, Rahul; Saba, Aminreza AbrahimiMost algorithms are run-to-completion and provide one answer upon completion and no answer if interrupted before completion. On the other hand, anytime algorithms have a monotonic increasing utility with the length of execution time. Our investigation focuses on the development of time-bounded anytime algorithms on Graphics Processing Units (GPUs) to trade-off the quality of output with execution time. Given a time-varying workload, the algorithm continually measures its progress and the remaining contract time to decide its execution pathway and select system resources required to maximize the quality of the result. To exploit the quality-time tradeoff, the focus is on the construction, instrumentation, on-line measurement and decision making of algorithms capable of efficiently managing GPU resources. We demonstrate this with a Parallel A* routing algorithm on a CUDA-enabled GPU. The algorithm execution time and resource usage is described in terms of CUDA kernels constructed at design-time. At runtime, the algorithm selects a subset of kernels and composes them to maximize the quality for the remaining contract time. We demonstrate the feedback-control between the GPU-CPU to achieve controllable computation tardiness by throttling request admissions and the processing precision. As a case study, we have implemented AutoMatrix, a GPU-based vehicle traffic simulator for real-time congestion management which scales up to 16 million vehicles on a US street map. This is an early effort to enable imprecise and approximate real-time computation on parallel architectures for stream-based timebounded applications such as traffic congestion prediction and route allocation for large transportation networks.Publication Embedded Virtual Machines for Wireless Industrial Automation (Demo)(2009-01-01) Pajic, Miroslav; Mangharam, RahulThe factory of the future is the Wireless Factory - fully programmable, nimble and adaptive to planned mode changes and unplanned faults. Today automotive assembly lines loose over $22,000 per minute of downtime. The systems are rigid, difficult to maintain, operate and diagnose. Our goal is to demonstrate the initial architecture and protocols for all-wireless factory control automation. Embedded wireless networks have largely focused on open-loop sensing and monitoring. To address actuation in closed-loop wireless control systems there is a strong need to re-think the communication architectures and protocols for reliability, coordination and control. As the links, nodes and topology of wireless systems are inherently unreliable, such time-critical and safety-critical applications require programming abstractions where the tasks are assigned to the sensors, actuators and controllers as a single component rather than statically mapping a set of tasks to a specific physical node at design time. To this end, we introduce the Embedded Virtual Machine (EVM), a powerful and flexible runtime system where virtual components and their properties are maintained across node boundaries. EVM-based algorithms introduce new capabilities such as provably minimal graceful degradation during sensor/actuator failure, adaptation to mode changes and runtime optimization of resource consumption. Through the design of a micro-factory we aim to demonstrate the capabilities of EVM-based wireless networks.