Modern society relies on convenience services and mobile communication. Cloud computing is the current trend to make data and applications available at any time on every device. Data centers concentrate computation and storage at central locations, while they claim themselves green due to their optimized maintenance and increased energy efﬁciency. The key enabler for this evolution is the microelectronics industry. The trend to power efﬁcient mobile devices has forced this industry to change its design dogma to: ”keep data locally and reduce data communication whenever possible”. Therefore we ask: is cloud computing repeating the aberrations of its enabling industry?
For many years real-time task models have focused the timing constraints on execution windows defined by earliest start times and deadlines for feasibility.
However, the utility of some application may vary among scenarios which yield correct behavior, and maximizing this utility improves the resource utilization.
For example, target sensitive applications have a target point where execution results in maximized utility, and an execution window for feasibility.
Execution around this point and within the execution window is allowed, albeit at lower utility.
The intensity of the utility decay accounts for the importance of the application.
Examples of such applications include multimedia and control; multimedia application are very popular nowadays and control applications are present in every automated system.
In this thesis, we present a novel real-time task model which provides for easy abstractions to express the timing constraints of target sensitive RT applications: the gravitational task model.
This model uses a simple gravity pendulum (or bob pendulum) system as a visualization model for trade-offs among target sensitive RT applications.
We consider jobs as objects in a pendulum system, and the target points as the central point.
Then, the equilibrium state of the physical problem is equivalent to the best compromise among jobs with conflicting targets.
Analogies with well-known systems are helpful to fill in the gap between application requirements and theoretical abstractions used in task models.
For instance, the so-called nature algorithms use key elements of physical processes to form the basis of an optimization algorithm.
Examples include the knapsack problem, traveling salesman problem, ant colony optimization, and simulated annealing.
We also present a few scheduling algorithms designed for the gravitational task model which fulfill the requirements for on-line adaptivity.
The scheduling of target sensitive RT applications must account for timing constraints, and the trade-off among tasks with conflicting targets.
Our proposed scheduling algorithms use the equilibrium state concept to order the execution sequence of jobs, and compute the deviation of jobs from their target points for increased system utility.
The execution sequence of jobs in the schedule has a significant impact on the equilibrium of jobs, and dominates the complexity of the problem --- the optimum solution is NP-hard.
We show the efficacy of our approach through simulations results and 3 target sensitive RT applications enhanced with the gravitational task model.
At present the standardization of third generation (3G) mobile radio systems is the subject of worldwide research activities. These systems will cope with the market demand for high data rate services and the system requirement for exibility concerning the offered services and the transmission qualities. However, there will be de ciencies with respect to high capacity, if 3G mobile radio systems exclusively use single antennas. Very promising technique developed for increasing the capacity of 3G mobile radio systems the application is adaptive antennas. In this thesis, the benefits of using adaptive antennas are investigated for 3G mobile radio systems based on Time Division CDMA (TD-CDMA), which forms part of the European 3G mobile radio air interface standard adopted by the ETSI, and is intensively studied within the standardization activities towards a worldwide 3G air interface standard directed by the 3GPP (3rd Generation Partnership Project). One of the most important issues related to adaptive antennas is the analysis of the benefits of using adaptive antennas compared to single antennas. In this thesis, these bene ts are explained theoretically and illustrated by computer simulation results for both data detection, which is performed according to the joint detection principle, and channel estimation, which is applied according to the Steiner estimator, in the TD-CDMA uplink. The theoretical explanations are based on well-known solved mathematical problems. The simulation results illustrating the benefits of adaptive antennas are produced by employing a novel simulation concept, which offers a considerable reduction of the simulation time and complexity, as well as increased exibility concerning the use of different system parameters, compared to the existing simulation concepts for TD-CDMA. Furthermore, three novel techniques are presented which can be used in systems with adaptive antennas for additionally improving the system performance compared to single antennas. These techniques concern the problems of code-channel mismatch, of user separation in the spatial domain, and of intercell interference, which, as it is shown in the thesis, play a critical role on the performance of TD-CDMA with adaptive antennas. Finally, a novel approach for illustrating the performance differences between the uplink and downlink of TD-CDMA based mobile radio systems in a straightforward manner is presented. Since a cellular mobile radio system with adaptive antennas is considered, the ultimate goal is the investigation of the overall system efficiency rather than the efficiency of a single link. In this thesis, the efficiency of TD-CDMA is evaluated through its spectrum efficiency and capacity, which are two closely related performance measures for cellular mobile radio systems. Compared to the use of single antennas, the use of adaptive antennas allows impressive improvements of both spectrum efficiency and capacity. Depending on the mobile radio channel model and the user velocity, improvement factors range from six to 10.7 for the spectrum efficiency, and from 6.7 to 12.6 for the spectrum capacity of TD-CDMA. Thus, adaptive antennas constitute a promising technique for capacity increase of future mobile communications systems.
Wireless sensor networks are the driving force behind many popular and interdisciplinary research areas, such as environmental monitoring, building automation, healthcare and assisted living applications. Requirements like compactness, high integration of sensors, flexibility, and power efficiency are often very different and cannot be fulfilled by state-of-the-art node platforms at once. In this paper, we present and analyze AmICA: a flexible, compact, easy-to-program, and low-power node platform. Developed from scratch and including a node, a basic communication protocol, and a debugging toolkit, it assists in an user-friendly rapid application development. The general purpose nature of AmICA was evaluated in two practical applications with diametric requirements. Our analysis shows that AmICA nodes are 67% smaller than BTnodes, have five times more sensors than Mica2Dot and consume 72% less energy than the state-of-the-art TelosB mote in sleep mode.
Wireless Sensor Networks (WSN) are dynamically-arranged networks typically composed of a large number of arbitrarily-distributed sensor nodes with computing capabilities contributing to –at least– one common application. The main characteristic of these networks is that of being functionally constrained due to a scarce availability of resources and strong dependence on uncontrollable environmental factors. These conditions introduce severe restrictions on the applicability of classic real-time methods aiming at guaranteeing time-bounded communications. Existing real-time solutions tend to apply concepts that were originally not conceived for sensor networks, idealizing realistic application scenarios and overlooking at important design limitations. This results in a number of misleading practices contributing to approaches of restricted validity in real-world scenarios. Amending the confrontation between WSNs and real-time objectives starts with a review of the basic fundamentals of existing approaches. In doing so, this thesis presents an alternative approach based on a generalized timeliness notion suitable to the particularities of WSNs. The new conceptual notion allows the definition of feasible real-time objectives opening a new scope of possibilities not constrained to idealized systems. The core of this thesis is based on the definition and application of Quality of Service (QoS) trade-offs between timeliness and other significant QoS metrics. The analysis of local and global trade-offs provides a step-by-step methodology identifying the correlations between these quality metrics. This association enables the definition of alternative trade-off configurations (set points) influencing the quality performance of the network at selected instants of time. With the basic grounds established, the above concepts are embedded in a simple routing protocol constituting a proof of concept for the validity of the presented analysis. Extensive evaluations under realistic scenarios are driven on simulation environments as well as real testbeds, validating the consistency of this approach.
An interrupter for use in a daisy-chained VME bus interrupt system has beendesigned and implemented as an asynchronous sequential circuit. The concur-rency of the processes posed a design problem that was solved by means of asystematic design procedure that uses Petri nets for specifying system and in-terrupter behaviour, and for deriving a primitive flow table. Classical designand additional measures to cope with non-fundamental mode operation yieldeda coded state-machine representation. This was implemented on a GAL 22V10,chosen for its hazard-preventing structure and for rapid prototyping in studentlaboratories.
Photonic crystals are inhomogeneous dielectric media with periodic variation of the refractive index. A photonic crystal gives us new tools for the manipulation of photons and thus has received great interests in a variety of fields. Photonic crystals are expected to be used in novel optical devices such as thresholdless laser diodes, single-mode light emitting diodes, small waveguides with low-loss sharp bends, small prisms, and small integrated optical circuits. They can be operated in some aspects as "left handed materials" which are capable of focusing transmitted waves into a sub-wavelength spot due to negative refraction. The thesis is focused on the applications of photonic crystals in communications and optical imaging: • Photonic crystal structures for potential dispersion management in optical telecommunication systems • 2D non-uniform photonic crystal waveguides with a square lattice for wide-angle beam refocusing using negative refraction • 2D non-uniform photonic crystal slabs with triangular lattice for all-angle beam refocusing • Compact phase-shifted band-pass transmission filter based on photonic crystals
Hardware prototyping is an essential part in the hardware design flow. Furthermore, hardware prototyping usually relies on system-level design and hardware-in-the-loop simulations in order to develop, test and evaluate intellectual property cores. One common task in this process consist on interfacing cores with different port specifications. Data width conversion is used to overcome this issue. This work presents two open source hardware cores compliant with AXI4-Stream bus protocol, where each core performs upsizing/downsizing data width conversion.
Analog sensor electronics requires special care during design in order to increase the quality and precision of the signal, and the life time of the product. Nevertheless, it can experience static deviations due to the manufacturing tolerances, and dynamic deviations due to operating in non-ideal environment. Therefore, the advanced applications such as MEMS technology employs calibration loop to deal with the deviations, but unfortunately, it is considered only in the digital domain, which cannot cope with all the analog deviations such as saturation of the analog signal, etc. On the other hand, rapid-prototyping is essential to decrease the development time, and the cost of the products for small quantities. Recently, evolvable hardware has been developed with the motivation to cope with the mentioned sensor electronic problems. However the industrial specifications and requirements are not considered in the hardware learning loop. Indeed, it minimizes the error between the required output and the real output generated due to given test signal. The aim of this thesis is to synthesize the generic organic-computing sensor electronics and return hardware with predictable behavior for embedded system applications that gains the industrial acceptance; therefore, the hardware topology is constrained to the standard hardware topologies, the hardware standard specifications are included in the optimization, and hierarchical optimization are abstracted from the synthesis tools to evolve first the building blocks, then evolve the abstract level that employs these optimized blocks. On the other hand, measuring some of the industrial specifications needs expensive equipments and some others are time consuming which is not fortunate for embedded system applications. Therefore, the novel approach "mixtrinsic multi-objective optimization" is proposed that simulates/estimates the set of the specifications that is hard to be measured due to the cost or time requirements, while it measures intrinsically the set of the specifications that has high sensitivity to deviations. These approaches succeed to optimize the hardware to meet the industrial specifications with low cost measurement setup which is essential for embedded system applications.