Search Results - (( mobile application cloud algorithm ) OR ( java simulation optimization algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System
Published 2023“…Most times, the approach of relying on cloud infrastructure for IoT application analysis may be inefficient in terms of the limited battery life of the mobile devices, resource allocation algorithm delay, and computational offloading processes that sometimes increases the response time. …”
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Process state synchronization for mobility support in mobile cloud computing / Ejaz Ahmed
Published 2016“…This research addresses the effect of mobility on application execution for mobile cloud-based interactive applications. …”
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Implementing Location-Based Cryptography on Mobile Application Design to Secure Data in Cloud Storage
Published 2024journal::journal article -
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On protecting data storage in mobile cloud computing paradigm
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Secure policies for the distributed virtual machines in mobile cloud computing
Published 2020“…Mobile Cloud Computing (MCC) is a combination of cloud computing and mobile computing through wireless technology in order to overcome mobile devices' resource limitations. …”
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Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider
Published 2011“…Sockets programming is one f the most basic and useful method of achieving any client server connectivity. The approach of the mobile cloud is clearly occurring with web host servers expands thus large number of data around the world stored in huge servers, consumers of mobile devices and small computing devices have high performance expectations usually, therefore mobile cloud computing theorizes that the cloud will soon become a disruptive force in the mobile world, eventually becoming the dominant way in which mobile applications operates. …”
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Energy-Aware Fault Tolerant Task offloading of Mobile Cloud Computing
Published 2023Conference Paper -
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Mobile agent based multi-layer security framework for cloud data centers
Published 2015“…Objective:This paper proposes a new mobile agent based cloud security framework comprising four different security and authentication layers to establish the trust relationship between two entities before using cloud services. …”
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Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions
Published 2023“…Many enterprise companies migrate their services and applications to the cloud to benefit from cloud computing advantages. …”
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Hardware development of autonomous mobile robot based on actuating lidar
Published 2022“…As opposed to a point cloud generated from high-end LiDAR sensors where many algorithms have been developed for object detection, sparse LiDAR point clouds still possess large room for improvement. …”
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Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization
Published 2025“…In recent years, Automated Mobile Robots (AMRs) have gained significant attention in industry and research applications, requiring efficient path-planning algorithms to optimize task performance. …”
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Integrated examination and analysis model for improving mobile cloud forensic investigation
Published 2022“…Advanced forensic techniques become inevitable to investigate the malicious activities in Cloud-based Mobile Applications (CMA). It is challenging to analyse the casespecific evidential artifact from the Mobile Cloud Computing (MCC) environment under forensically sound conditions. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.]
Published 2013“…In a cloud computing environment, a device can be varied from a high-end computing workstation to mobile devices like smart phone or PDA to respond efficiently to such diversified environment, a cloud-based system must possess mechanisms that allow applications requested delivered fit according to the client device's characteristics and capabilities. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…Considering the complexity factors, existing literature proposes static execution models for MDSM applications. The execution models are based on either standalone mobile devices, mobile-to-mobile, mobile-to-edge, or mobile-to-cloud communication models. …”
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Process migration-based computational offloading framework for IOT-supported mobile edge/cloud computing
Published 2019“…Mobile cloud computing and mobile edge computing (MEC) are emerging technologies that can meet the aforementioned requirements using offloading algorithms. …”
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Process Migration-Based Computational Offloading Framework for IoT-Supported Mobile Edge/Cloud Computing
Published 2020“…Mobile cloud computing and mobile edge computing (MEC) are emerging technologies that can meet the aforementioned requirements using offloading algorithms. …”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment
Published 2021“…The system uses a LiDAR-IMU tight coupling odometry method to reconstruct a point cloud map of the area surveyed. After using the RANSAC algorithm to remove the map ground, the European clustering algorithm is used for point cloud segmentation. …”
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