Mobile Grid Research Articles

Task scheduling using glowworm-based optimal heterogeneous earliest finish time algorithm for mobile grid

Task scheduling using glowworm-based optimal heterogeneous earliest finish time algorithm for mobile grid

Artificial Intelligence-based Solution for the Prediction of Power Consumption in Electronics and Software Applications

As new computing paradigms such as mobile grids and clouds become more commonplace, mobile devices are becoming increasingly attractive to scientists and HPC users who need high-performance computing capabilities. There are still many challenges to design software that uses mobile devices, such as their restricted capabilities compared to traditional devices such as PCs and servers. It’s even more critical to remember that batteries are the primary power source for mobile devices. Thus people delete programmes that severely reduce their battery life. The upshot is that it is common for developers to have no idea how much power specific hardware and software components use. So even if they have been trained in software development, they still require specific standards and skills to design energy-efficient apps. This Paper investigates ways to minimize mobile device energy usage by restructuring source code. However, we did not overlook the prospect of applying our findings to other domains, such as recurring demanding computational cores in scientific applications. Specifically, this research contributes to the field of Green Computing and mobile software development.

Модель термомиграции жидкого включения в монокристалле галитов в однородном поле градиента температуры

The paper focuses on an evolution model developed for a liquid inclusion in halites under a temperature gradient field, taking into account surface phenomena. To demonstrate the safety of heat-generating radioactive waste disposal in salt rocks (halites), thermally induced migration of liquid inclusions should be studied. Based on the study, a software package was developed providing numerical implementation of this model. The diffusion equation with initial and boundary conditions was approximated via the finite element method on triangular unstructured mobile grids. In case of weak formulation, the equations were discretized and solved in the FEniCS software. The study showed good agreement between the calculations and the experimental data.

Numerical modeling of the formation of D-T mixture spherical layer in micro-targets of LTS

The article presents a two-dimensional economical computational model of the formation of D-T mixture cryogenic layer in a spherical shell. The model is based on the description of the motion of the gas phase in the Boussinesq approximation. The thermal problem is a Stefan problem with a gas-solid phase transition. The technique is based on the finite volume method, the use of a structured mobile grid, whose movement is associated with the separation of the phase front, implicit approximations and the method of splitting two-dimensional equations in directions into one-dimensional equations. It is numerically shown that, due to natural radioactivity, the target is symmetrized. A calculated estimation of the symmetrization time for one geometry of the target with different filling coefficients is carried out.

Hydrodynamic and energy extraction properties of oscillating hydrofoils with a trailing edge flap

In order to improve the energy extraction efficiency of the oscillating hydrofoil, this research proposes a model of an oscillating hydrofoil with trailing edge flaps. In this study, firstly we established the equation of the flap swing motion equation and that of the effective angle of attack angle, then the model of simple oscillating hydrofoil structure was numerically simulated using the dynamic and moving grid technology of the CFD software. Secondly, the model of oscillating hydrofoil structure was modified with trailing edge flap and the model was numerically simulated with dynamic and mobile grid technology of CFD software with refined the equations of motion and the equation of effective attack angle of flap swinging. The simulation results show that the length, the pitching amplitude and the frequency of the trailing-edge flap significantly affect the efficiency of the energy extraction. There is an optimal range for each of the three main parameters to maximize the energy extraction efficiency and the time average efficiency for specific angle of attack compared to the primary hydrofoil. The use of the trailing-edge flap may increase the time averaged efficiency by 81%. The flap increases the camber angle of the hydrofoil, and improves the lift coefficient of the whole hydrofoil, which leads to the improvement of the energy extraction efficiency of the hydrofoil. With the increase of lift coefficient, the drag coefficient also increases. As for the reliability and stability of the oscillating hydrofoil device, the drag of the oscillating hydrofoil should be within the range that the oscillating hydrofoil device can bear while improving the time average efficiency.

New Heuristics for Scheduling and Distributing Jobs under Hybrid Dew Computing Environments

Mobile grid computing has been a popular topic for researchers due to mobile and IoT devices’ ubiquity and their evergrowing processing potential. While many scheduling algorithms for harnessing these resources exist in the literature for standard grid computing scenarios, surprisingly, there is little insight into this matter in the context of hybrid‐powered computing resources, typically found in Dew and Edge computing environments. This paper proposes new algorithms aware of devices’ power source for scheduling tasks in hybrid environments, i.e., where the battery‐ and non‐battery‐powered devices cooperate. We simulated hybrid Dew/Edge environments by extending DewSim, a simulator that models battery‐driven devices’ battery behavior using battery traces profiled from real mobile devices. We compared the throughput and job completion achieved by algorithms proposed in this paper using as a baseline a previously developed algorithm that considers computing resources but only from battery‐dependent devices called Enhanced Simple Energy‐Aware Schedule (E‐SEAS). The obtained results in the simulation reveal that our proposed algorithms can obtain up to a 90% increment in overall throughput and around 95% of completed jobs in hybrid environments compared to E‐SEAS. Finally, we show that incorporating these characteristics gives more awareness of the type of resources present and can enable the algorithms to manage resources more efficiently in more hybrid environments than other algorithms found in the literature.

Information Security Terminal Architecture of Power Transportation Mobile Internet of Things Based on Big Data Analysis

The progress of the social economy and the rapid development of the power field have created more favorable conditions for the construction of my country’s power grid. In this network age, how to further realize the connection between the power system and the Internet of Things is the key content of many scholars’ research. In the Internet of Things environment, there have been many excellent results in the collection, storage, and management of electric power big data, but the problem of information security has not been completely solved. Based on big data analysis and Internet of Things technology, this paper studies the architecture design of power information security terminals. In view of the diverse types of power grid mobile information and the large amount of data, this paper designs a power transportation mobile information security management system structure, which improves the effective management of power data by the system through big data, smart sensors, and wireless communication technology. According to the experiment, the power information security terminal constructed in this paper can effectively reduce communication resources and save communication costs in the process of aggregating multidimensional data. In the user satisfaction survey, residents’ satisfaction with the convenience and safety of the intelligent power system is also as high as 9.312 and 9.233. On the whole, the application of big data and Internet of Things technology to the construction of power information security terminals can indeed improve the service efficiency of power companies under the premise of ensuring safety and allow users to have a better experience.

A trust management model based on NSGA-II in mobile grid system

Mobile Grid network connects large number of mobile devices like smartphones, tablets, PDAs, wireless digital medical equipment’s etc for the purpose of sharing their resources and performing the task collaboratively and cooperatively. The mobile nodes participating in the mobile grid are autonomous and open in nature making them more vulnerable to data and control attacks made by malicious or selfish nodes. Preventing these malicious or selfish nodes and identifying the trusted nodes to participate in the network is an NP-hard problem. To recognize trusted nodes in the mobile grid system a novel trust management model is proposed in this paper by applying an elitist multi objective optimization algorithm Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed trust management model assesses the trust index of each mobile node in the network using various evaluation factors or attributes and then obtains the non-dominated set of trusted nodes in each front. Comparative analysis of the proposed trust model shows that the proposed model can be a potential candidate for implementing trust management in mobile grid network.

Mobile Apps Meet the Smart Energy Grid: A Survey on Consumer Engagement and Machine Learning Applications

Consumers lie at the epicenter of smart grids, since their activities account for a large portion of the total energy demand. Therefore, utility companies, governmental agencies, and various other entities with environmental concerns aim at lowering and shaping energy consumption patterns to achieve peak load reduction, load smoothing, and hence carbon emission curtailment. In this survey paper, we present an overview of approaches for engaging smart grid consumers and for providing them with information, motivation, and recommendations for energy efficiency through mobile apps. Our focus is to bring machine learning approaches closer to smart grid mobile apps so as to optimally manage consumer flexibility and enhance energy savings through detailed consumer profiling and modeling, since an increasing amount of energy consumer data is becoming available. A novel survey and analysis of prior work in the area is conducted in order to identify gaps from this perspective. We consider both recent research project outputs and commercial products and we discuss various aspects of the designs, such as state-of-the-art technologies, extrinsic and intrinsic motivation techniques, gamification, consumer profiling, and the role of machine learning and recommender systems in this context. Furthermore, different mobile apps are presented and compared based on the most important features that affect consumer energy efficiency and sustainability, such as data visualization, gamification, flexibility, consumer profiling methods, feedback mechanisms, recommendations, social media, and machine learning integration. The main goal of this work is to identify how mobile apps incorporate these features to engage energy consumers in energy-efficient behavior, assess the current state-of-the-art in the area, and highlight future research directions.

Dynamic Trust Management for Community Based Mobile Grid Application

Mobile Grid is the inter-networking of heterogeneous physical as well as virtualdevices. Each device transfer and share the information with each other. Trust management plays a significant role in network based applications for information collection, data mining, qualified services with context-awareness, upgraded client protection and data security. It assists individuals with beating impression of vulnerability, threat and participates in client acknowledgment to utilization on grid services and applications. In this paper a unique trust management protocol is proposed for network based mobile grid application to manage misbehaving nodes whose status or performance may change dynamically. Trust plays an important role for handling the security in the community based system. Trust management provides facilitate to identify malfunctions and also make legitimate collaboration and enhance the user privacy and information security.

A Fuzzy Lattice System to Trust Management in Mobile Grid

Mobile Grid is a crossbreed technology formed by amalgamation of the two prominent technologies namely mobile technology and grid technology that enable sharing and collaboration of mobile resources cooperatively, transparently, efficiently, reliably and securely. Mobile Grid considers the mobility issues and overcomes the constraints and deficiencies in both the technologies. However, this heterogeneous, dynamic and open mobile grid network is more prone to malicious and selfish nodes inside and outside the network. Hence, a vigorous security mechanism is needed that considers different security threats and pro-vide different levels of security services. Here, we propose one such preventive security service based on Trust Management. The proposed trust management service uses a novel fuzzy lattice approach for trust estimation of the nodes in the network. A node with high trust value is allowed to participate in the network. A malicious node having low trust value is prevented from performing the task. A fuzzy lattice approach can compute incrementally the same intervals in the training data independent of the order of presentation within a short period. Experimental analysis of the fuzzy lattice approach shows that the proposed approach outperforms most of the existing approaches based on fuzzy logic.

Resource allocation scheme for Dew Computing paradigm using mobile grid

With the widespread availability of smartphones and advancement in communication technologies, Dew Computing paradigm(DCp) has emerged as a state-of-the-art computing paradigm. DCp provides an ecosystem to execute computationally intensive tasks which comprise of several subtasks. Each subtask is allocated for execution to an available and capable mobile device by taking into consideration its features like mobility, processing power, remaining battery, etc. This kind of “on-the-spot” paradigm comprises of mobile devices only which are part of mobile grid and it doesn’t use the fixed infrastructure based computing systems for computational purposes. Being resource constrained, such a paradigm needs an efficient scheme for allocation of resources. Here we propose a scheme called MGRA for allocation of computing nodes which takes into account challenging issues like mobility of users, inefficient resource allocation and handling of failure situations. Experimentation was carried out using a DCp testbed comprising Android devices connected with Wi-Fi Direct protocol. MGRA exhibited significant improvement in terms of time for application completion, amount of battery usage and time required for recovering from failure as compared to present-day approaches.

One-Dimensional Double Wires and Two-Dimensional Mobile Grids: Cobalt/Bipyridine Coordination Networks at the Solid/Liquid Interface.

Various architectures have been generated and observed by STM at a solid/liquid interface resulting from an in situ chemical reaction between the bipyridine terminal groups of a ditopic ligand and Co(II) ions. Large monodomains of one-dimensional (1D) double wires are formed by Co(II)/ligand coordination, with polymer lengths as long as 150 nm. The polymers are organized as parallel wires 8 nm apart, and the voids between wires are occupied by solvent molecules. Two-dimensional (2D) grids, showing high surface mobility, coexist with the wires. The wires are formed from linear chain motifs where each cobalt center is bonded to two bipyridines. 2D grids are generated from a bifurcation node where one cobalt bonds to three bipyridines. Surface reconstruction of the grids and of the 1D wires was observed under the STM tip. As an exciting result, analysis of these movements strongly indicates surface reactions at the solid/liquid interface.

Application Checkpointing Technique for Self-Healing From Failures in Mobile Grid Computing

A mobile grid (MG) consists of interconnected mobile devices which are used for high performance computing. Fault tolerance is an important property of mobile computational grid systems for achieving superior arrangement reliability and faster recovery from failures. Since the failure of the resources affects task execution fatally, fault tolerance service is essential to achieve QoS requirement in MG. The faults which occur in MG are link failure, node failure, task failure, limited bandwidth etc. Detecting these failures can help in better utilisation of the resources and timely notification to the user in a MG environment. These failures result in loss of computational results and data. Many algorithms or techniques were proposed for failure handling in traditional grids. The authors propose a checkpointing based failure handling technique which will improve arrangement reliability and failure recovery time for the MG network. Experimentation was conducted by creating a grid of ubiquitously available Android-based mobile phones.

On the Application of a Mobile Grid Technology to Computational Fluid Dynamics

On the Application of a Mobile Grid Technology to Computational Fluid Dynamics

Efficient resource allocation scheme for on-the-fly computing based mobile grids

Mobile grid (MG) is emergi ng as a new computing paradigm due to the ubiquitous availability of mobile devices. With the advancement in the capability of these devices, computationally intensive tasks can be executed using a peer-to-peer grid of such devices. MG can provide an edifice to execute parallel computationally intensive tasks. Key challenges that crop up while computing on a MG are resource constrained environment, inefficient resource allocation, high failure probability, etc. As a result, selection of appropriate nodes for task execution becomes critical for successful execution of the application. In this paper, we propose an efficient resource allocation model (ERAM) which provides resource allocation with failure handling. We created a MG comprising of Wi-Fi Direct connected Android smartphones. Different scenarios are considered for the purpose of experimentation. Our approach performs well with respect to application completion time, % battery consumption and recovery time from failure in comparison with existing techniques.

Simple Energy Aware Scheduler: An Empirical Evaluation

Mobile devices have evolved from single purpose devices, such as mobile phone, into general purpose multi-core computers with considerable unused capabilities. Therefore, several researchers have considered harnessing the power of these battery-powered devices for distributed computing. Despite their ever-growing capabilities, using battery as power source for mobile devices represents a major challenge for applying traditional distributed computing techniques. Particularly, researchers aimed at using mobile devices as resources for executing computationally intensive task. Different job scheduling algorithms were proposed with this aim, but many of them require information that is unavailable or difficult to obtain in real-life environments, such as how much energy would require a job to be finished. In this context, Simple Energy Aware Scheduler (SEAS) is a scheduling technique for computational intensive Mobile Grids that only require easily accessible information. It was proposed in 2010 and it has been the base for a range of research work. Despite being described as easily implementable in real-life scenarios, SEAS and other SEAS-improvements works have always been evaluated using simulations. In this work, we present a distributed computing platform for mobile devices that support SEAS and empirical evaluation of the SEAS scheduler. This evaluation followed the methodology of the original SEAS evaluation, in which Random and Round Robin schedulers were used as baselines. Although the original evaluation was performed by simulation using notebooks profile instead of smartphones and tablets, results confirms that SEAS outperforms the baseline schedulers.

SaW: Video Analysis in Social Media with Web-Based Mobile Grid Computing

The burgeoning capabilities of Web browsers to exploit full-featured devices can turn the huge pool of social connected users into a powerful network of processing assets. HTML5 and JavaScript stacks support the deployment of social client-side processing infrastructure, while WebGL and WebCL fill the gap to gain full GPU and multi-CPU performance. Mobile Grid and Mobile Cloud Computing solutions leverage smart devices to relieve the processing tasks to be performed by the service infrastructure. Motivated to gain cost-efficiency, a social network service provider can outsource the video analysis to elements of a mobile grid as an infrastructure to complement an elastic cloud service. As long as users access to videos, batch image analysis tasks are dispatched from the server, executed in the background of the client-side hardware, and finally, results are consolidated by the server. This paper presents SaW (Social at Work) to provide a pure Web-based solution as a mobile grid to complement a cloud media service for image analysis on videos.

Parallel Processing of Images in Mobile Devices using BOINC

AbstractMedical image processing helps health professionals make decisions for the diagnosis and treatment of patients. Since some algorithms for processing images require substantial amounts of resources, one could take advantage of distributed or parallel computing. A mobile grid can be an adequate computing infrastructure for this problem. A mobile grid is a grid that includes mobile devices as resource providers. In a previous step of this research, we selected BOINC as the infrastructure to build our mobile grid. However, parallel processing of images in mobile devices poses at least two important challenges: the execution of standard libraries for processing images and obtaining adequate performance when compared to desktop computers grids. By the time we started our research, the use of BOINC in mobile devices also involved two issues: a) the execution of programs in mobile devices required to modify the code to insert calls to the BOINC API, and b) the division of the image among the mobile devices as well as its merging required additional code in some BOINC components. This article presents answers to these four challenges.

Outlook of Coordinated Transmission Control in 5G Networks for IoTs

The sum of wireless nodes are forecasted to ascent sharply from about ten billion in year 2018 to twenty-five billion by 2020. Consequently, the data packet capacity response is anticipated to increase in future. The projected 5th generation (5G) of cellular grids is anticipated to be a blend of grid mechanisms with diverse magnitudes, transfer energy, backhaul networks and wireless access equipment. Although there are several fascinating complications comprised by the 5G context, we highlighted the problems of communication mechanism with the potential of Internet of Things (IoT). We offer a charter to discover required method constraints strategy that deal with the preeminent advances in terms of possible output for device-todevice inspired mobile grids. We explore the working and breakdown of immediate data and energy handover in IoT and assess individually about communication outage likelihood and energy outage possibility.