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Real-time Calculus (RTC) is a non-stochastic queuing theory to the worst-case performance analysis of distributed real-time systems. Workload as well as resources are modelled as piece-wise linear, pseudo-periodic curves and the system under investigation is modelled as a sequence of algebraic operations over these curves. The memory footprint of computed curves increases exponentially with the sequence...
Physical Unclonable Functions (PUFs) are promising security primitives for device authentication and key generation. This paper proposes a two-step methodology to improve the reliability of PUF under noisy conditions. The first step involves acquiring the parameters of PUF models by using machine learning algorithms. The second step then utilizes these obtained parameters to improve the reliability...
In a seminal 1990 paper [9], Martin presents the C-element Theorem which implies, roughly, that the class of purely delay insensitive (DI) circuits is fundamentally limited in the set of functions it can implement. We provide circuit examples, both DI and not DI, that violate assumptions or results from [9], showing that the set of circuits considered by [9] is more limited than one might expect—and...
In this paper we propose a mathematical model of the functioning of network device with virtual routers. This model allows to decrease the mutual influence of the parametric effects of different types of traffic in the network node, as well as to estimate the quality of service by decomposition of a structure of network node and mathematical modeling based on queueing theory. To verify the proposed...
Fog computing provides a decentralized approach to data processing and resource provisioning in the Internet of Things (IoT). Particular challenges of adopting fog-based computational resources are the adherence to geographical distribution of IoT data sources, the delay sensitivity of IoT services, and the potentially very large amounts of data emitted and consumed by IoT devices. Despite existing...
Merging Mobile Edge Computing (MEC), which is an emerging paradigm to meet the increasing computation demands from mobile devices, with the dense deployment of Base Stations (BSs), is foreseen as a key step towards the next generation mobile networks. However, new challenges arise for designing energy efficient networks since radio access resources and computing resources of BSs have to be jointly...
To effectively alleviate the increasingly serious situation of airspace congestion and flight delays in a multi-airport system, we consider a scheduling problem for multi-airport departure flights in this paper. A mathematical model based on two-stage no-wait hybrid flow-shop is presented for sequencing departure flights in different airports within one terminal area. Moreover, some practical issues...
Network Function Virtualization (NFV) is an emergent paradigm that is currently transforming the way network services are provisioned and managed. The main idea of NFV is to decouple network functions from the hardware running them. This allows to reduce deployment costs and further improve the flexibility and the scalability of network services. Despite these benefits, a major challenge cloud providers...
In the paper, the globally stability for Genetic Regulator Networks with mixed time-delays is studied. By using derivative mean value theorem, two sufficient and necessary conditions for globally unformly asymptotic stability and global exponential stability of the trivial solutions of the GRNs with mixed time-delays are proposed. Finally, a simple example is given to demonstrate the correctness of...
Fog computing is seen as a promising approach to perform distributed, low-latency computation for supporting Internet of Things applications. However, due to the unpredictable arrival of available neighboring fog nodes, the dynamic formation of a fog network can be challenging. In essence, a given fog node must smartly select the set of neighboring fog nodes that can provide low-latency computations...
Many real-time applications consist of a cyclic execution of computation activities (jobs) with stochastic computation time. In order to identify the probability that such applications will meet their deadlines, it is crucial to have a model for the random process describing the computation time. In many interesting applications, a Markovian model, in which the system stochastically switches within...
The quality of any control design can be judged by the resulting transient response. When an adaptive control law is used for linear time-invariant systems with unknown parameters, the resulting transients can be rather unsatisfactory. This problem persists when the adaptive controller receives information about the output of the plant through a wireless network. In this paper, we use the multiple...
The reconfigurable mesh (RM) is a powerful model for parallel computations. In spite of this power, the RM has not been realized mainly due to the assumption that the broadcastingcan be done in constant time regardless of the number of switches the broadcast has to pass through. Therefore, attempts were made to develop practical restricted models. We propose the Restricted-Reconfigurable Circuit (RRC)...
This paper proposes a model predictive strategy for air path control turbocharged Spark Ignition (SI) engines with low pressure Exhaust Gas Recirculation (EGR). The proposed Nonlinear Model Predictive Controller (NMPC) is designed to track manifold pressure and EGR concentration reference, by manipulating throttle, EGR valve, continuous surge valve and waste gate. The NMPC is solved in real time using...
Delays are often present in embedded and networked control loops and represent one of the main sources of performance limitations. In this paper, we propose two aperiodic control strategies to optimize closed-loop performance in the presence of stochastic delays: (i) a self-triggered strategy, in which the deadline to drop data is decided on-line based on the current state; (ii) an event-driven strategy,...
We study optimal control for sampled-data systems with stochastic delays. Assuming that the delays can be modeled by a Markov chain and can be measured by controllers, we design a control law that minimizes an infinite-horizon continuous-time quadratic cost function. The resulting optimal control law can be efficiently computed offline by the iteration of a certain Riccati difference equation. We...
Simulation is a fast, controlled, and reproducible way to evaluate new algorithms for distributed computing platforms in a variety of conditions. However, the realism of simulations is rarely assessed, which critically questions the applicability of a whole range of findings. In this paper, we present our efforts to build platform models from application traces, to allow for the accurate simulation...
Video traffic constitutes the majority of traffic in bytes that mobile and fixed line operators deliver to their customer. This type of traffic is both resource consuming and QoE sensitive. Either because of content quality or QoE, a large fraction of users often abandon viewing prematurely. These abandonment phenomena lead to a huge waste of network resources and device batteries. Several strategies...
In this article, a new methodology is presented for identification of finite-impulse-response (FIR) models. The central idea is to use a series of stable models of first-order plus time delays (FOPTD) to approximate the dynamics of the process. A quantitative analysis of the modelling error is provided. Compared to the existing basis model approaches, the advantages of the proposed method lie in the...
Edge Computing, as a solution to leveraging computation capabilities at the edge of the network, is emerging. One key challenge for edge computing is offering its computing service with a low service blocking and low latency that otherwise translate to an inefficient deployment of a Edge computing system. Unlike cloud computing, the computing resources in edge computing are limited. One way to deal...
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