SAAES 2011 Abstracts


Full Papers
Paper Nr: 1
Title:

HIERARCHICAL AGENT MONITORING DESIGN PLATFORM - Towards Self-aware and Adaptive Embedded Systems

Authors:

Liang Guang, Bo Yang and Juha Plosila

Abstract: Hierarchical agent monitoring design platform (HAM) is presented as a generic design approach for the emerging self-aware and adaptive embedded systems. Such systems, with various existing proposals for different advanced features, call for a concrete, practical and portable design approach. HAM addresses this necessity by providing a scalable and generically applicable design platform. This paper elaborately describes the hierarchical agent monitoring architecture, with extensive reference to the state-of-the-art technology in embedded systems. Two case studies are exemplified to demonstrate the design process and benefits of HAM design platform. One is about hierarchical agent monitored Network-on-Chip with quantitative experiments of hierarchical energy management. The other one is a projectional study of applying HAM on smart house systems, focusing on the design for enhanced dependability.

Paper Nr: 3
Title:

REAL TIME MEASUREMENTS OF HIGH RESOLUTION MIXED-SIGNAL CIRCUITS FOR SELF AWARE EMBEDDED SYSTEM

Authors:

Drago Strle and Janez Trontelj

Abstract: In this paper we discuss a methodology for efficient real-time measurements of high-resolution mixed-signal circuits implemented on the IC. The methodology could be used for real time built-in self-tests of a fail-safe mixed-signal integrated circuits and as a measurement part of a self-aware algorithm and methodology for integrated mixed-signal circuits. We show that a pseudo-random noise signal is a good option for the signal source and that the methodology leads to the efficient and cost-effective measurements in real time. The measurement is running in parallel to the main signal processing. The method is theoretically analyzed and verified using Matlab models and simulations. As an example the response of high precision, high order Σ-Δ ADC with most important non-ideal effects is compared to the response of a bit-true model of a reference digital circuit. The differences are demonstrated using simple area-efficient cross-correlation algorithm that can be implemented in software or in digital hardware.

Paper Nr: 5
Title:

A PARALLEL ONLINE REGULARIZED LEAST-SQUARES MACHINE LEARNING ALGORITHM FOR FUTURE MULTI-CORE PROCESSORS

Authors:

Tapio Pahikkala, Antti Airola, Thomas Canhao Xu and Pasi Liljeberg

Abstract: In this paper we introduce a machine learning system based on parallel online regularized least-squares learning algorithm implemented on a network on chip (NoC) hardware architecture. The system is specifically suitable for use in real-time adaptive systems due to the following properties it fulfills. Firstly, the system is able to learn in online fashion, a property required in almost all real-life applications of embedded machine learning systems. Secondly, in order to guarantee real-time response in embedded multi-core computer architectures, the learning system is parallelized and able to operate with a limited amount of computational and memory resources. Thirdly, the system can learn to predict several labels simultaneously which is beneficial, for example, in multi-class and multi-label classification as well as in more general forms of multi-task learning. We evaluate the performance of our algorithm from 1 thread to 4 threads, in a quad-core platform. A Network-on-Chip platform is chosen to implement the algorithm in 16 threads. The NoC consists of a 4x4 mesh. Results show that the system is able to learn with minimal computational requirements, and that the parallelization of the learning process considerably reduces the required processing time.

Short Papers
Paper Nr: 4
Title:

INSIGHT INTO THE REQUIREMENTS OF SELF-AWARE, ADAPTIVE AND RELIABLE EMBEDDED SUB-SYSTEMS OF SATELLITE SPACECRAFT

Authors:

Rajeev Kumar Kanth, Pasi Liljeberg, Hannu Tenhunen, Qiansu Wan and Waqar Ahmad

Abstract: This position paper gives an insight for self-aware and adaptivity requirements of the sub-systems embedded in a satellite spacecraft. The most significant and considerable issues of self-aware and adaptive systems that are necessary in present and future on-board satellite spacecraft are illustrated in this paper. An attempt has been made to discuss several embedded sub-systems and space environment scenarios of the spacecraft. As a case study, an adaptive sierpinski based dual band antenna has been devised. The adaptive nature of this antenna provides a foundation of longer and more reliable mission life of a spacecraft. Through this paper it will be shown that adaptive, reconfigurable and reliability issues are the most prominent and potential area of research for outer space communication technology.

Paper Nr: 6
Title:

USING ROUTING AGENTS FOR IMPROVING THE QUALITY OF SERVICE IN GENERAL PURPOSE NETWORKS

Authors:

Mohammad Mottaghi and Masoud Daneshtalab

Abstract: In this paper, we have proposed a new routing method for general purpose networks. Each router in this model is a context-aware agent and therefore the whole network of routers forms a community (society) of context-aware agents which are ever learning and adapting the routing network. During routing each agent keeps learning and specializing in routing some specific traffic type (e.g. intermittent audio packets) and makes its neighboring routes optimum for this type of traffic whereas other agents are experts in other traffic types. All agents are aware from their colleagues' expertise and when a new traffic type enters the network all agents try to collaboratively recognize (or detect) its type and route it according to their past experience (which is already learned). If the traffic type is unknown to all agents, one of them tries to learn how to route it such that its QoS constraints are met better. The idea behind the proposed model is to temporarily modify some routes whenever QoS constraints cannot be met in the network. Simulation results show that the proposed model can improve QoS of the network by 12%.