Now showing 1 - 6 of 6
PublicationRoll-out of Giga-bit Copper( 2018)
;Hincapie, Daniel ;Leibiger, MathiasG.fast is the latest digital subscriber line (DSL) technology that provides Giga-bit access from the distribution point (DP). Although it promises to satisfy the short and mid-term requirements of internet-based services, providers are not upgrading instantaneously all legacy systems to G.fast. Instead, the consolidation process is progressive and therefore must minimize the impacts on legacy systems such VDSL2, providing seamless migration and friendly coexistence experience. To achieve this goal, service providers are considering to avoid mutual interference using non-overlapping band-plans. This strategy reduces G.fast data rates and coverage, though. A less harmful approach is to allow partial overlapping, but the benefits and spectrum that must be removed to reduce the impact are unknown. In this work, we analyze the performance impact that G.fast roll-out conveys when VDSL2 systems served from a cabinet are gradually upgraded to G.fast deployed at the DP. We carry out a simulation study to evaluate the mutual performance losses when G.fast is first introduced with a low user share in different fiber-to-the-cabinet (FTTC) scenarios. Based on the obtained results, we select representative access network topologies to determine the expected minimum and maximum losses as the user share progressively increases. In order to establish the benefits and drawbacks of implementing G.fast band-plans that partially overlap with VDSL2, we evaluate G.fast and VDSL2 performance when the operative start frequency of G.fast is set along VDSL2 spectrum. We consider in our study both the current version of G.fast and its recently proposed long reach (LR) extension that aims to achieve longer coverage range by enabling larger bit-constellation size (Bmax = 12bits) and higher maximum aggregate transmit power (MAXATP = 8dBm). The obtained numerical results are intended to help service providers estimate the impact of G.fast on existing VDSL2 systems, as well as its under-performance when they jointly operate indifferent network topologies. So they can evaluate: 1) which FTTC scenarios are eligible for deploying G.fast and how much it impacts non-upgraded users; 2) how much performance degradation to expect during the progressive deployment of G.fast; and 3) the expected data rate loss for G.fast when its spectrum is partially limited, and how much this strategy reduces the impact on VDSL2.
PublicationEnergy saving potential of adaptive, networked, embedded systems( 2016)
;Heinrich, Patrick ;Knorr, RudiThis paper presents and evaluates the energy saving potential of adaptive, networked, embedded systems. The aim is to demonstrate the benefits of modeling the energy demand during the development of such systems. For this purpose, the previous developed energy model is applied within a case study and different allocations of software components are compared. The estimated energy demands of these allocations are presented and discussed. The analyzed system of the case study represents an automotive system which executes two advanced driver assistance applications. The system is adaptive, which means that temporally unnecessary applications will be deactivated. Within the evaluated system this deactivation depends on the vehicle speed, which is derived by the New European Driving Cycle. Two different allocations of software components are evaluated.
PublicationEarly energy estimation of heterogeneous embedded networks within adaptive systems( 2015)
;Heinrich, Patrick ;Gossen, Dietrich ;Knorr, RudiThis paper presents and evaluates a new approach of modeling energy consumption of communication within adaptive networked embedded systems. The objective is to enable energy estimation within early phases of system development, which allows system designers to compare different allocations of software components. As networked embedded systems consist of multiple specialized networks (with different protocols and topologies) and are characterized by a high degree of interaction, existing network-centric approaches have significant disadvantages describing entire systems. To overcome this problem a model was created which is based on individual communication connections between software components. This enables technology-transparent mapping to network topologies (across borders of networks) which significantly simplifies the evaluation of different software placements.
PublicationSelf-learning assessment of communication in distributed embedded systems - a feasibility studyThis paper addresses the problem of evaluating the communication behavior of cyber physical systems. An important problem for the validation of the interaction in the distributed system is missing, wrong or incomplete specification. In this paper, the application of a new approach for assessing the communication behavior based on reference traces is presented and evaluated. The benefit of the approach is that it works automatically, with low additional effort and without using any specification. This paper provides a use case in conjunction with a feasibility study to investigate the applicability of a self-learning anomaly detection methodology. The data of the feasibility study are created by applying the described anomaly detection within a real vehicle network.
PublicationUsing reference traces for validation of communication in embedded systemsThis paper addresses the problem of evaluating the communication behavior of embedded systems. An important problem is missing, wrong or incomplete specification for the interaction in the distributed system. In this paper, a new approach for evaluating the communication behavior based on reference traces is introduced. The benefit of the approach is that it works automatically, with low additional effort and without using any specification. The introduced methodology uses algorithms from the field of machine learning to extract behavior models out of a reference trace. With the presented algorithm, the complexity of the learning problem can be reduced significantly by identifying parallel execution paths. The efficiency of the proposed algorithm is evaluated with real vehicle network data. At this data the self-learning algorithm covers up to 69% of the behavior from the presented trace.
PublicationA self-learning approach for validation of communication in embedded systemsThis paper demonstrates a new approach that addresses the problem of evaluating the communication behavior of embedded systems by applying algorithms from the area of artificial intelligence. An important problem for the validation for the interaction in the distributed system is missing, wrong or incomplete specification. This paper demonstrates the application of a new self-learning approach for assessing the communication behavior based on reference traces. The benefit of the approach is that it works automatically, with low additional effort and without using any specification. The investigated methodology uses algorithms from the field of machine learning and data mining to extract behavior models out of a reference trace. For showing the application, this paper provides a use case and the basic setup for the proposed method. The applicability of this self-learning methodology is evaluated based on real vehicle network data.