Gerard Memmi

Experimental energy profiling of energy-critical embedded applications

Despite recent advances that have greatly improved the performance of embedded systems, we still face many challenges with regard to energy consumption in energy-constrained embedded and communication platforms. Optimizing applications for energy consumption remains a challenge and thus is a compelling research direction, both on the practical and theoretical sides. This paper presents a new experimental bench for energy profiling of non-performance-critical embedded and mobile applications and reports preliminary results obtained on two embedded boards. The experiments are driven by an online energy monitoring mechanism using National Instruments cDAQ and LabVIEW running on a host machine. The host monitors a target device, which runs a set of benchmarks. We describe the experience gained from using and modding two different target boards, namely an Nvidia Jetson TX1 and a TI AM572x evaluation module. In particular, we confirm, and thus further validate, the existence of the Energy/Frequency Convexity Rule for CPU-bound benchmarks. This rule states that there exists an optimal clock frequency that minimizes the CPU energy consumption for non-performance-critical applications. We also show that the gain of frequency scaling is highly dependent on workload characteristics. Any future energy-management approach should take these behavioral traits into consideration.

Selective All-Or-Nothing Transform: Protecting Outsourced Data Against Key Exposure

This paper presents the selective all-or-nothing transform (SAONT). It addresses the needs of users who would like to use inexpensive cloud storage services, but do not trust their providers. Encrypted data are transformed and separated into a small private fragment kept on the user’s device and a large public fragment which can be securely uploaded to a public cloud since decryption of the public fragment is infeasible without the private fragment. Therefore, outsourced data are protected even in a situation of key exposure. SAONT reduces performance overhead by combining block-wise fragmentation of a ciphertext with an application of an all-or-nothing transform only on a subset of the ciphertext.

A Fast and Scalable Fragmentation Algorithm for Data Protection Using Multi-storage over Independent Locations

Data fragmentation and dispersal over several independent locations enhances protection level of outsourced data. In this paper, we introduce a Fast and Scalable Fragmentation Algorithm (FSFA) that is particularly well adapted to be used in a multi-cloud environment. It transforms data into interdependent fragments that all have to be gathered in order to reconstruct the initial information. A performance comparison with published related works (including data encryption and dispersal) demonstrates it can be more than twice faster than the fastest of the relevant fragmentation techniques, while producing reasonable storage overhead.

Modeling the energy consumption of programs: Thermal aspects and energy/frequency convexity rule (invited paper)

This article summarizes our current studies aiming at a better understanding of the energy consumption of a microprocessor during the execution of an application through a combination of theoretical results and experimental validations, The analysis of the transient thermal behavior and energy gains (ranging from 20 to 40% in some cases) via the adaptation of the clock frequency are of obvious practical interest. A general Passive Cooling Rule (PCR) for an isothermal object subjected to radiation, convection and internal heat generation is proposed. This power-temperature model is observed on an Exynos 5410 processor. Several approximations to this cooling rule are formulated for practical use, particularly online. They are accompanied by general rules for assessing when passive cooling becomes non-negligible compared to active cooling in embedded systems. On another hand, a theoretical framework for the existence of an Energy/Frequency Convexity Rule (EFCR) of program consumption is established. It is validated both by the state of the art and by experimental measurements. Power consumption models are then explained. The novelty of these models is that they take into account certain characteristics of the program execution and that they can be directly reused in any simulation for other processors of similar architecture.

An Efficient Secure Storage Scheme Based on Information Fragmentation

In this paper, an efficient secure storage scheme is presented which aims to provide security to end-users data while mostly storing it to public clouds. This proposed scheme is based on the invertible Discrete Wavelet Transform (DWT) to fragment data into two or three fragments with different levels of importance and protected accordingly. As a matter of fact, the most important fragment takes the smallest amount of storage space and can be stored in a user trusted area while the less important fragments take most of the storage space and are uploaded to public clouds. In order to reduce the required execution time, General Purpose Graphic Processing Unit (GPGPU) is employed for accelerating computation. Additionally, a benchmark was realized to compare between the proposed scheme and AES algorithm applied to the entire data.