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When a mobile wireless sensor is moving along heterogeneous wireless sensor networks, it can be under the coverage of more than one network many times. In these situations, the Vertical Handoff process can happen, where the mobile sensor decides to change its connection from a network to the best network among the available ones according to their...
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... name the algorithm we have developed for the VH decision phase taking into account the QoS characteristics of the networks SEFI (from "Weights Combinations Fast SEarch by Fixed Intervals"). The algorithm explores the entire space of possible combinations of weights, searching those that satisfy the hard restriction imposed by (2), considering a maximum number of possible networks and a determined number of QoS parameters (NQoS) (Figure 4). The generation of these combinations is done from a given precision value (h) and two limits determined by the user, WMIN and WMAX, where WMIN < h < WMAX, WMIN > 0 and WMAX < 1. ...Similar publications
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Citations
... Various other researchers also explored the utilization of FPGA in SNs and mobile communication. A quick evaluation algorithm was proposed for mobile sensing devices incorporated with heterogeneous FPGAs, adjusting weights to improve the Quality of Service in Ref. [96]. Others have proposed an adaptable sensing network utilizing FPGAs for delay-based evaluation, highlighting their flexibility in hardware design for diverse situations [97]. ...
The combination of distributed digital factories (D²Fs) with sustainable practices has been proposed as a revolutionary technique in modern manufacturing. This review paper explores the convergence of D²F with innovative sensor technology, concentrating on the role of Field Programmable Gate Arrays (FPGAs) in promoting this paradigm. A D²F is defined as an integrated framework where digital twins (DTs), sensors, laser additive manufacturing (laser-AM), and subtractive manufacturing (SM) work in synchronization. Here, DTs serve as a virtual replica of physical machines, allowing accurate monitoring and control of a given manufacturing process. These DTs are supplemented by sensors, providing near-real-time data to assure the effectiveness of the manufacturing processes. FPGAs, identified for their re-programmability, reduced power usage, and enhanced processing compared to traditional processors, are increasingly being used to develop near-real-time monitoring systems within manufacturing networks. This review paper identifies the recent expansions in FPGA-based sensors and their exploration within the D²Fs operations. The primary topics incorporate the deployment of eco-efficient data management and near-real-time monitoring, targeted at lowering waste and optimizing resources. The review paper also identifies the future research directions in this field. By incorporating advanced sensors, DTs, laser-AM, and SM processes, this review emphasizes a path toward more sustainable and resilient D²Fs operations.
... ABC algorithm simulating seeking the manner of bees was designed by Karaboga [11]. The Artificial Bee Colony (ABC) algorithm is a famous swarm-based algorithm. ...
Heterogeneous wireless networks are converging towards an all-IP network as part of the so-called next-generation network. In this paradigm, different access technologies need to be interconnected; thus, vertical handovers are necessary for seamless mobility. In this paper, an artificial bee colony (ABC) algorithm for real-time vertical handover using different objective function has been presented to find the optimal network to connect. It can select an optimal set of weights for specified values, and find the optimal network selection solution. Simulation results illustrate that the proposed ABC algorithm has better performances than the existing methods in many evaluating parameters, and the computational time is also minimized.
... • Communication -Communication protocols, such as Wi-Fi and Bluetooth [14], and hand-over protocols [17] are key considerations in a IT system. • Data management -Good data quality [18], efficient exchange [12] and effective data management has been proven to have multiple advantages. ...
Advances in mobile health (mHealth) has been notable in the last few years, but so has the problems associated with the development, implementation and sustained use of mHealth systems. After implementation, various difficulties arise contributing to being considered a failure. The purpose of the study is to create a model by which e-Health systems can be evaluated in order to ensure development for sustained use, with attention focused on aspects identified through literature. The author examines problems identified in previous research to establish difficulties and shortfalls regarding the perceived success of said systems. Patient and healthcare practitioner points-of-view, along with software and hardware considerations are taken into account. The investigation determines that the use of IT in mHealth is still dependent on serious factors influencing the realization of success of well-established as well as newly developed systems. These concerns undermine the effectiveness and usefulness of the improvement and efficiency of healthcare facilities and knowledge as a whole. The author proposes a model against which developed and developing mHealth systems can be measured in order to promote continued usage of implemented systems. This study sheds new light on little recognized issues for bringing concept and practice together in a useful, uninterrupted, and unending manner.
... For that end, R-GRID uses virtualization techniques to decouple the behavior of the hardware resource from the physical implementation level. In addition, the approach presented in [65] describes the implementation of a fast decision algorithm for the connectivity of mobile sensors with heterogeneous wireless networks using FPGAs. The FPGA device is installed and embedded in the mobile terminals and adjusts a set of weights to improve the Quality of Service (QoS). ...
The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.
... We base our intelligent heuristic proposals on SEFI (from ''Weight Combinations SEarch by Fixed Intervals''), an algorithm that we have designed to search solutions for a given precision [30]. SEFI is a non-exhaustive direct search algorithm that finds all the possible solutions for a given search precision. ...
... We programmed SEFI in C language using recursive loops for the uniform generation of all the possible combinations. The code was successfully tested on the embedded low-power microprocessor Microblaze [30]. This processor is based on reconfigurable hardware [33] and FPGA devices [34], and has similar features as some low performance processors in small mobile terminals. ...
... For GAVH and SEFI, statistic is also supplied: number of generated combinations, evaluated solutions, variance and standard deviation. As GAVH is our bet for embedded intelligence for the VH decision phase in mobile terminals, we have tested it in hardware, just like we did previously with SEFI [30]. The test was done by means of the Microblaze embedded low-power and low-performance FPGA microprocessor [44], because it could be considered as a first approach to the low power embedded microprocessors present in many mobile devices, where few hundreds of MHz and limited processing resources are often available. ...
One of the most important aspects of the modern communications deals with the access to wireless networks by mobile devices, looking for a good quality of service under the user’s preferences. Nevertheless, a mobile terminal can discover more than one network of different technology along its trajectory in heterogeneous scenarios, being capable of connecting to other wireless access points according to their quality of service values. This is the case of the vertical handoff decision phase, present in many sceneries such as 3G-LTE access networks. In this context, an efficient resource management of the different networks (a good selection of weights for their quality of service parameters) constitutes an optimization problem, where several heuristic methods using simple rules try to find the best available network. Nevertheless, the characteristics of the current mobile devices advise to use fast and efficient algorithms to provide solutions near to real-time. These constraints have moved us to develop intelligent algorithms that avoid the slow and massive computations associated with direct search techniques, so reducing the computation time. In this paper we propose an evolutionary algorithm capable of computing rapidly in embedded processors, improving the performance of other algorithms designed in order to solve this optimization problem.
When a mobile terminal is moving across heterogeneous wireless networks acting as access points, it must decide the best network to connect to, taking into account the values of the quality of service parameters of the networks. Selecting an optimal set of weights for these values in the terminal is an optimization problem that must be solved in real time for embedded microprocessors that manage the Vertical Handoff decision phase in highly dynamic environments. For this purpose, we have developed an adaptive heuristic inspired on the Simulated Annealing algorithm that improves the performance of a former algorithm designed to solve this optimization problem.
Sensors-based systems are nowadays an extended technology for many markets due to their great potential in the collection of data from the environment and the processing of such data for different purposes. A typical example is the wireless sensor devices, where the outer temperature, humidity, luminosity and many other parameters can be acquired, measured and processed in order to build useful and fascinating applications that contribute to human welfare. In this scenario, the processing architectures of the sensors-based systems play a very important role. The requirements that are necessary for many such applications (real-time processing, low-power consumption, reduced size, reliability, security and many others) means that research on advanced architectures of Microprocessors and System-on-Chips (SoC) is needed to design and implement a successful product. In this sense, there are many challenges and open questions in this area that need to be addressed. [...]
