Memory leak

Summary

In computer science, a memory leak is a type of resource leak that occurs when a computer program incorrectly manages memory allocations in a way that memory which is no longer needed is not released. A memory leak may also happen when an object is stored in memory but cannot be accessed by the running code (i.e. unreachable memory). A memory leak has symptoms similar to a number of other problems and generally can only be diagnosed by a programmer with access to the program's source code. A related concept is the "space leak", which is when a program consumes excessive memory but does eventually release it. Because they can exhaust available system memory as an application runs, memory leaks are often the cause of or a contributing factor to software aging. Consequences A memory leak reduces the performance of the computer by reducing the amount of available memory. Eventually, in the worst case, too much of the available memory may become allocated and all or part of th

Official source

https://en.wikipedia.org/wiki/Memory_leak

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Dynamic Programming OPtimization (DPOP) is an algorithm proposed for solving distributed constraint optimization problems. In this algorithm, Hypercubes are used as the format of the messages exchanged between the agents. Then, Hybrid-DPOP (H-DPOP), a hybrid algorithm based on DPOP was proposed as an improved solution. Its main advantage over DPOP lies under the use of Multi-valued Decision Diagrams (MDDs) instead of Hypercubes. Furthermore, MDDs give a more compact representation of the messages. The MDDs were implemented and presented in by Kumar even though it was presented as Constrained Decision Diagrams (CDD) which is a generalization of MDDs. The first part of this project aims at implementing Hypercubes. An Implementation already exists. Therefore, the goal is to propose an implementation which is more efficient in term of speed and memory usage for the already implemented functions (join, project and slice). The solution implemented during this project should also provide new functions (split and re-order) and the possibility of saving Hypercubes in the XML format. The second part of the project consists in proposing and implementing a data structure that is more efficient than the MDDs implemented in H-DPOP. This data structure should also provide more functions, and also provide the possibility of saving data in the XML format.

2008

Multi-Lead Wavelet-Based ECG Delineation on a Wearable Embedded Sensor Platform

David Atienza Alonso, Nicolas Boichat, Nadia Khaled, Francisco Javier Rincon Vallejos

This work is dedicated to the sensible optimization and porting of a multi-lead (ML) wavelet-transform (WT)-based electrocardiogram (ECG) wave delineator to a state-of-the-art commercial wearable embedded sensor platform with limited processing and storage resources. The original offline algorithm was recently proposed and validated in the literature, as an extension of an earlier well-established single-lead (SL) WT-based ECG delineator. Several ML ECG delineation approaches, including SL selection according to various criteria and lead combination into a single root-mean-squared (RMS) curve, are carefully optimized for real-time operation on a state-of-the-art commercial wearable embedded sensor platform. Furthermore, these ML ECG delineation approaches are contrasted in terms of their delineation accuracy, complexity and memory usage, as well as suitability for ambulatory real-time operation. Finally, the robustness and stability of the ML ECG delineation approaches are benchmarked with respect to a validated SL implementation.

2009

Development and Evaluation of Multi-Lead Wavelet-Based ECG Delineation Algorithms for Embedded Wireless Sensor Nodes

David Atienza Alonso, Nadia Khaled, Francisco Javier Rincon Vallejos

This work is devoted to the evaluation of multilead digital wavelet transform (DWT)-based electrocardiogram (ECG) wave delineation algorithms, which were optimized and ported to a commercial wearable sensor platform. More specifically, we investigate the use of root-mean squared (RMS)-based multi-lead followed by a single-lead online delineation algorithm, which is based on a state-of-the-art offline singlelead delineator. The algorithmic transformations and software optimizations necessary to enable embedded ECG delineation notwithstanding the limited processing and storage resources of the target platform are described, and the performance of the resulting implementations are analyzed in terms of delineation accuracy, execution time and memory usage. Interestingly, RMS-based multi-lead delineation is shown to perform equivalently to the best single-lead delineation for the 2-lead QT database (QTDB), within a fraction of a sample duration of the Common Standards for Electrocardiography (CSE) committee tolerances. Finally, a comprehensive evaluation of the energy consumption entailed by the considered algorithms is proposed, which allows very relevant insights into the dominant energy-draining functionalities and which suggests suitable design guidelines for longlasting wearable ECG monitoring systems.

Institute of Electrical and Electronics Engineers2011