Power Analysis and Optimization Techniques for Energy Efficient Computer Systems

Reducing power consumption has become a major challenge in the design and operation of to-day’s computer systems. This chapter describes different techniques addressing this challenge at different levels of system hardware, such as CPU, memory, and internal interconnection network, as well as at different levels of software components, such as compiler, operating system and user applications. These techniques can be broadly categorized into two types: Design time power analysis versus run-time dynamic power management. Mechanisms in the first category use ana-lytical energy models that are integrated into existing simulators to measure the system’s power consumption and thus help engineers to test power-conscious hardware and software during de-sign time. On the other hand, dynamic power management techniques are applied during run-time, and are used to monitor system workload and adapt the system’s behavior dynamically to save energy

Mobile platform-independent solutions for body sensor network interface

Body Sensor Networks (BSN) appeared as an application of Wireless Sensor Network (WSN) to medicine and biofeedback. Such networks feature smart sensors (biosensors) that capture bio-physiological parameters from people and can offer an easy way for data collection. A new BSN platform called Sensing Health with Intelligence Modularity, Mobility and Experimental Reusability (SHIMMER) presents an excellent opportunity to put the concept into practice, with suitable size and weight, while also supporting wireless communication via Bluetooth and IEEE 802.15.4 standards. BSNs also need suitable interfaces for data processing, presentation, and storage for latter retrieval, as a result one can use Bluetooth technology to communicate with several more powerful and Graphical User Interface (GUI)-enabled devices such as mobile phones or regular computers. Taking into account that people currently use mobile and smart phones, it offers a good opportunity to propose a suitable mobile system for BSN SHIMMER-based networks. This dissertation proposes a mobile system solution with different versions created to the four major smart phone platforms: Symbian, Windows Mobile, iPhone, and Android. Taking into account that, currently, iPhone does not support Java, and Java cannot match a native solution in terms of performance in other platforms such as Android or Symbian, a native approach with similar functionality must be followed. Then, four mobile applications were created, evaluated and validated, and they are ready for use

cytonGrasp: Cyton Alpha Controller via GraspIt! Simulation

This thesis addresses an expansion of the control programs for the Cyton Alpha 7D 1G arm. The original control system made use of configurable software which exploited the arm’s seven degrees of freedom and kinematic redundancy to control the arm based on desired behaviors that were configured off-line. The inclusions of the GraspIt! grasp planning simulator and toolkit enables the Cyton Alpha to be used in more proactive on-line grasping problems, as well as, presenting many additional tools for on-line learning applications. In short, GraspIt! expands what is possible with the Cyton Alpha to include many machine learning tools and opportunities for future research. Noteworthy features of GraspIt!: • A 3D user interface allowing the user to see and interact virtual objects, obstacles, and robots, in addition to a 3D representation of the Cyton Alpha • A collision detection and contact determination system within simulation • On-line grasp analysis routines • Visualization methods for determining the weak points within a grasp, as well as, creating projections of grasp quality and ability to resist dynamic forces. • Computation of numerical grasp quality metrics and visualization methods for proposed grasps • Dynamics engine • Support for lower-dimensional hand posture subspaces • Interaction with sensors (Flock of Birds tracker) and hardware (Pioneer robot) within simulation • GraspIt! can generate huge databases of labeled grasp data, which can be used for data-driven grasp-planning algorithms and has built in support for the Columbia Grasp Database. By making use of the GraspIt! simulator, it is possible to test algorithms for grasp manipulation, grasp planning, or grasp synthesis more quickly and with greater repeatability than would be possible on the real robot. Contributions of this system include: 1. A joint based 3D rendering of the Cyton Alpha 7D 1G arm 2. Simulated bodies for several objects in the DI Lab 3. Support for multiple representations of joint data within three-dimensional space • Euler Angles • Quaternions • Denavit-Hartenberg Parameters 4. Framework for future work in grasp-planning, grasp synthesis, cooperative grasping tasks, and transfer learning applications with the Cyton Alpha arm

A Finite State Machine Approach to Cluster Identification Using the Hoshen-Kopelman Algorithm

The purpose of this study was to develop an efficient finite state machine implementation of the eponymous Hoshen-Kopelman cluster identification algorithm using the nearest-eight neighborhood rule suitable to applications such as computer modeling for landscape ecology. The implementation presented in this study was tested using both actual land cover maps, as well as randomly generated data similar to those in the original presentation of the Hoshen-Kopelman algorithm for percolation analysis. The finite state machine implementation clearly outperformed a straightforward adaptation of the original Hoshen-Kopelman algorithm on either data type. Research was also conducted to explore the finite state machine\u27s performance on a Palm mobile computing device, and while it was competitive, it did not exceed the performance of the straightforward Hoshen-Kopelman implementation. However, a discussion of why this was the case is provided along with a possible remedy for future hardware designs

Energy Demand Response for High-Performance Computing Systems

The growing computational demand of scientific applications has greatly motivated the development of large-scale high-performance computing (HPC) systems in the past decade. To accommodate the increasing demand of applications, HPC systems have been going through dramatic architectural changes (e.g., introduction of many-core and multi-core systems, rapid growth of complex interconnection network for efficient communication between thousands of nodes), as well as significant increase in size (e.g., modern supercomputers consist of hundreds of thousands of nodes). With such changes in architecture and size, the energy consumption by these systems has increased significantly. With the advent of exascale supercomputers in the next few years, power consumption of the HPC systems will surely increase; some systems may even consume hundreds of megawatts of electricity. Demand response programs are designed to help the energy service providers to stabilize the power system by reducing the energy consumption of participating systems during the time periods of high demand power usage or temporary shortage in power supply. This dissertation focuses on developing energy-efficient demand-response models and algorithms to enable HPC system\u27s demand response participation. In the first part, we present interconnection network models for performance prediction of large-scale HPC applications. They are based on interconnected topologies widely used in HPC systems: dragonfly, torus, and fat-tree. Our interconnect models are fully integrated with an implementation of message-passing interface (MPI) that can mimic most of its functions with packet-level accuracy. Extensive experiments show that our integrated models provide good accuracy for predicting the network behavior, while at the same time allowing for good parallel scaling performance. In the second part, we present an energy-efficient demand-response model to reduce HPC systems\u27 energy consumption during demand response periods. We propose HPC job scheduling and resource provisioning schemes to enable HPC system\u27s emergency demand response participation. In the final part, we propose an economic demand-response model to allow both HPC operator and HPC users to jointly reduce HPC system\u27s energy cost. Our proposed model allows the participation of HPC systems in economic demand-response programs through a contract-based rewarding scheme that can incentivize HPC users to participate in demand response

Multi-core architectures with coarse-grained dynamically reconfigurable processors for broadband wireless access technologies

Broadband Wireless Access technologies have significant market potential, especially the WiMAX protocol which can deliver data rates of tens of Mbps. Strong demand for high performance WiMAX solutions is forcing designers to seek help from multi-core processors that offer competitive advantages in terms of all performance metrics, such as speed, power and area. Through the provision of a degree of flexibility similar to that of a DSP and performance and power consumption advantages approaching that of an ASIC, coarse-grained dynamically reconfigurable processors are proving to be strong candidates for processing cores used in future high performance multi-core processor systems. This thesis investigates multi-core architectures with a newly emerging dynamically reconfigurable processor – RICA, targeting WiMAX physical layer applications. A novel master-slave multi-core architecture is proposed, using RICA processing cores. A SystemC based simulator, called MRPSIM, is devised to model this multi-core architecture. This simulator provides fast simulation speed and timing accuracy, offers flexible architectural options to configure the multi-core architecture, and enables the analysis and investigation of multi-core architectures. Meanwhile a profiling-driven mapping methodology is developed to partition the WiMAX application into multiple tasks as well as schedule and map these tasks onto the multi-core architecture, aiming to reduce the overall system execution time. Both the MRPSIM simulator and the mapping methodology are seamlessly integrated with the existing RICA tool flow. Based on the proposed master-slave multi-core architecture, a series of diverse homogeneous and heterogeneous multi-core solutions are designed for different fixed WiMAX physical layer profiles. Implemented in ANSI C and executed on the MRPSIM simulator, these multi-core solutions contain different numbers of cores, combine various memory architectures and task partitioning schemes, and deliver high throughputs at relatively low area costs. Meanwhile a design space exploration methodology is developed to search the design space for multi-core systems to find suitable solutions under certain system constraints. Finally, laying a foundation for future multithreading exploration on the proposed multi-core architecture, this thesis investigates the porting of a real-time operating system – Micro C/OS-II to a single RICA processor. A multitasking version of WiMAX is implemented on a single RICA processor with the operating system support

Performance and Power Characterization of Cellular Networks and Mobile Application Optimizations.

Smartphones with cellular data access have become increasingly popular with the wide variety of mobile applications. However, the performance and power footprint of these mobile applications are not well-understood, and due to the unawareness of the cellular specific characteristics, many of these applications are causing inefficient radio resource and device energy usage. In this dissertation, we aim at providing a suite of systematic methodology and tools to better understand the performance and power characteristics of cellular networks (3G and the new LTE 4G networks) and the mobile applications relying upon, and to optimize the mobile application design based on this understanding. We have built the MobiPerf tool to understand the characteristics of cellular networks. With this knowledge, we make detailed analysis on smartphone application performance via controlled experiments and via a large-scale data set from one major U.S. cellular carrier. To understand the power footprint of mobile applications, we have derived comprehensive power models for different network types and characterize radio energy usage of various smartphone applications via both controlled experiments and 7-month-long traces collected from 20 real users. Specifically, we characterize the radio and energy impact of the network traffic generated when the phone screen is off and propose the screen-aware traffic optimization. In addition to shedding light to the mobile application design throughout our characterization analysis, we further design and implement a real optimization system RadioProphet, which uses historical traffic features to make predictions and intelligently deallocate radio resource for improved radio and energy efficiency.PhDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99905/1/hjx_1.pd

A Survey on Security for Mobile Devices

Nowadays, mobile devices are an important part of our everyday lives since they enable us to access a large variety of ubiquitous services. In recent years, the availability of these ubiquitous and mobile services has signicantly increased due to the dierent form of connectivity provided by mobile devices, such as GSM, GPRS, Bluetooth and Wi-Fi. In the same trend, the number and typologies of vulnerabilities exploiting these services and communication channels have increased as well. Therefore, smartphones may now represent an ideal target for malware writers. As the number of vulnerabilities and, hence, of attacks increase, there has been a corresponding rise of security solutions proposed by researchers. Due to the fact that this research eld is immature and still unexplored in depth, with this paper we aim to provide a structured and comprehensive overview of the research on security solutions for mobile devices. This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011. We focus on high-level attacks, such those to user applications, through SMS/MMS, denial-of-service, overcharging and privacy. We group existing approaches aimed at protecting mobile devices against these classes of attacks into dierent categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach

Haptics Rendering and Applications

There has been significant progress in haptic technologies but the incorporation of haptics into virtual environments is still in its infancy. A wide range of the new society's human activities including communication, education, art, entertainment, commerce and science would forever change if we learned how to capture, manipulate and reproduce haptic sensory stimuli that are nearly indistinguishable from reality. For the field to move forward, many commercial and technological barriers need to be overcome. By rendering how objects feel through haptic technology, we communicate information that might reflect a desire to speak a physically- based language that has never been explored before. Due to constant improvement in haptics technology and increasing levels of research into and development of haptics-related algorithms, protocols and devices, there is a belief that haptics technology has a promising future