today's desired power managing devices are smart, embeddable, highly energy efficient and with small form factor. the main goal of each design is to find the optimal combination between performance and costs. the ...
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today's desired power managing devices are smart, embeddable, highly energy efficient and with small form factor. the main goal of each design is to find the optimal combination between performance and costs. the performance can be raised with optimized control algorithms implemented on a powerful MCU platform capable of performing even multiple tasks in parallel. A good shaped charging and balancing algorithm could increase overall battery lifetime and performance when backing up critical systemsthat needs to be up all the time, and doing all these at a relative reduced cost. Fast reaction time of the system is critical so that the devices connected to the UPS output remain always powered. Several reconfigurable electrical and environmental parameters and different communication channels withthis smart UPS ensures that it can be embedded in a wide range of electrical systems.
MARTE (Modeling and Analysis of real-time and embeddedsystems) is a UML profile, which has been developed to model concepts specific to real-time and embeddedsystems (RTES). In previous years, we have applied UML/MA...
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On chip integrated inductors and transformers require novel and improved materials and CMOS-compatible Wafer Level Magnetics (WLM) deposition techniques. In this work we are presenting an Fe-Co based amorphous magneti...
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ISBN:
(纸本)9781467316811;9781467316828
On chip integrated inductors and transformers require novel and improved materials and CMOS-compatible Wafer Level Magnetics (WLM) deposition techniques. In this work we are presenting an Fe-Co based amorphous magnetic alloy, called FCA that was specifically designed and developed by Enpirion to be used for the first time in volume production for highly integrated and miniaturized power management electronics. the FCA properties that make it suitable for use in a real product are: stable permeability to frequencies higher than 20MHz, high electrical resistivity rho>120 mu Omega-cm, high magnetic saturation B-s>1.5T, and ultra-low coercivity H-c<1. the fully CMOS-compatible FCA electro-deposition is carried out in JCAP's wafer production fab in China using customized electroplating equipment that was specifically developed for the FCA plating chemistry. A microinductor utilizing an FCA magnetic core is developed, characterized and integrated into a DC-DC converter. this work demonstrates a commercially viable and available to market 1Amp DC-DC switching converter operating at 18MHz with efficiency up to 90% that utilizes electroplated magnetic materials on wafer for the first time in the power management industry.
Linear PID algorithms commonly used in industry might perform insufficiently when controlling nonlinear operating systems. Solutions such as the fuzzy PID controller can exchange the linear PID controller because it d...
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ISBN:
(纸本)9783642293467
Linear PID algorithms commonly used in industry might perform insufficiently when controlling nonlinear operating systems. Solutions such as the fuzzy PID controller can exchange the linear PID controller because it develops a nonlinear control surface. the main advantage of the fuzzy PID controller is the ability to adjust to a controlled plant by the rule based modification, nonlinear membership function application and inference rule selection. However, the tuning process is one of the most difficult steps in the fuzzy PID controller designing and therefore discourages most practical applications. A simplification of the fuzzy PID controller tuning process is described in this article. the presented methodology allows fast transformation from a classic PID algorithm into a fuzzy PID algorithm. A proposed algorithm is tested on a programmable PLC which is a typical industrial implementation platform. A temperature stabilization is chosen as the controlled plant and some experimental results are then described. In conclusion authors suggest directions for similar realtime fuzzy PID algorithm implementations.
the pay-as-you-go economic model of cloud computing leads naturally to an earn-as-you-go profit model for many cloud based services. these applications can benefit from low level analyses for cost optimization and ver...
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the pay-as-you-go economic model of cloud computing leads naturally to an earn-as-you-go profit model for many cloud based services. these applications can benefit from low level analyses for cost optimization and verification. Testing cloud applications to ensure they meet monetary cost objectives has not been well explored in the current literature. We present a static analysis approach for determining which control flow paths in cloud applications can exceed a cost threshold. We build on tools used in Worst Case Execution time analysis that provide a tight bound on processing time, and we implement provisions for adding bandwidth, storage, and service costs. Our approach determines the magnitude of cost excess for nodes in an application's call graph so that cloud developers can better understand where to focus their efforts to lower costs (or deem some excesses acceptable based on business case analysis).
Frequent pattern mining is the field with many practical applications, where large computational power and speed are needed. Many solutions, both software and hardware, are proposed for those applications, but special...
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Frequent pattern mining is the field with many practical applications, where large computational power and speed are needed. Many solutions, both software and hardware, are proposed for those applications, but specialised solutions in form of embeddedsystems are not so common as one could imagine. this is especially true when we consider problems that can be paralleled. Many of the state-of-the-art frequent pattern mining applications are inefficient when used on shared memory systems or multiprocessor systems. To solve this problem both hardware and software solutions are proposed - remapping system architecture, improving memory performance, modifying task allocation. this article proposes modification of classical frequent pattern mining algorithms from Apriori family, illustrated withthe example of popular GSP algorithm. Addition of GPU (Graphics Processing Unit) or multiple GPUs to embedded system is proposed and algorithm is modified in such a way, that it is best suited for solving GPGPU (general-purpose computation on graphics hardware) problems. Boththeoretical and experimental evaluation of modifications are made, the latter with use of setup consisting of NVIDIA Tesla card and CUDA parallel computing platform. It is shown in the article, that for tested data sets modified GSP algorithm finishes finding frequent sequences 50-100 times faster and withthe same accuracy. Such speed-up allows the use of classical pattern mining algorithms for real-time solutions. this also permits broader scope of algorithms to be used in embeddedsystems withreal-time constraints.
Withthe advent of social networking and the appearance of Web 2.0, collaborative applications which allow users to share data online, often in real-time, have gained increasing prominence. Whether for sharing images,...
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the use of multicores is becoming widespread in the field of embeddedsystems, many of which have real-time requirements. Hence, ensuring that real-timeapplications meet their timing constraints is a pre-requisite be...
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ISBN:
(纸本)9781467321648
the use of multicores is becoming widespread in the field of embeddedsystems, many of which have real-time requirements. Hence, ensuring that real-timeapplications meet their timing constraints is a pre-requisite before deploying them on these systems. this necessitates the consideration of the impact of the contention due to shared low-level hardware resources like the front-side bus (FSB) on the Worst-Case Execution time (WCET) of the tasks. Towards this aim, this paper proposes a method to determine an upper bound on the number of bus requests that tasks executing on a core can generate in a given time interval. We show that our method yields tighter upper bounds in comparison withthe state-of-the-art. We then apply our method to compute the extra contention delay incurred by tasks, when they are co-scheduled on different cores and access the shared main memory, using a shared bus, access to which is granted using a round-robin arbitration (RR) protocol.
Scheduling large-scale applications in heterogeneous Grid and Cloud systems is a fundamental NP-complete problem for obtaining good performance and execution costs. We address the problem of scheduling an important cl...
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Scheduling large-scale applications in heterogeneous Grid and Cloud systems is a fundamental NP-complete problem for obtaining good performance and execution costs. We address the problem of scheduling an important class of large-scale Grid applications inspired from real-world, characterised by a large number of homogeneous, concurrent, and computationally-intensive tasks that are the main sources of performance, cost, and storage bottlenecks. We propose a new formulation of this problem based on a cooperative distributed game theoretic method for makespan and cost optimisation of a multiple such applications while fulfilling important storage constraints. We present experimental results using simulation and real-world applicationsthat demonstrate the effectiveness of our method in terms of the solution delivered, algorithm execution time, and fairness compared to other related approaches.
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