In this paper, we proposed an algorithm for load distribution of workloads among nodes of a cloud by the use of Ant Colony Optimization (ACO). This is a modified approach of ant colony optimization that has been applied from the perspective of cloud or grid network systems with the main aim of load balancing of nodes. This modified algorithm has an edge over the original approach in which each ant build their own individual result set and it is later on built into a complete solution. However, in our approach the ants continuously update a single result set rather than updating their own result set. Further, as we know that a cloud is the collection of many nodes, which can support various types of application that is used by the clients on a basis of pay per use. Therefore, the system, which is incurring a cost for the user should function smoothly and should have algorithms that can continue the proper system functioning even at peak usage hours.

Load Balancing of Nodes in Cloud Using Ant Colony Optimization

The increase of many pillars within the dataset makes it needed to pick the best part of features. The feature selection approach directly influences the performance of the style in terms of integrity and computational information. The wrapper feature choice version deals with the function set to improve the category reliability. In this paper, a new wrapper feature selection binary formula is intended based upon the Sine Cosine Algorithm (SCA) and a modified Whale Optimization Algorithm (MWOA). This algorithm (Binary SC-MWOA) was associated with obtaining unassociated characteristics and selecting the optimum features. The proposed formula’s attractive outcomes reveal the algorithm’s performance for picking the best features. Ten different UCI Repository datasets are checked in the experiments.

A binary Sine Cosine-Modified Whale Optimization Algorithm for Feature Selection

The use of superpixels instead of pixels can significantly improve the speed of the current pixel-based algorithms, and can even produce better results in many applications such as robotics, remote sensing, industrial inspection, and medical diagnosis. Two main tasks related to vision could benefit from superpixels, named object class segmentation and medical image segmentation. In both cases, superpixels can increase performance significantly and also reduce the computational cost. In addition to superpixel applications, various datasets were employed for the evaluation of the superpixel algorithms. This work aims to survey the recent applications and the most common datasets that can be used based on superpixel techniques.

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Applications and Datasets for Superpixel Techniques A Survey

Building a trust model system to avoid cloud services reputation attacks

Cloud data storage is revolutionary because it eliminates the need for additional hardware, which is often costly, inconvenient, and requires additional space. Cloud data storage allows data owners to store large amounts of data in a flexible way and at low cost. The number of online cloud storage services and their consumers has therefore increased dramatically. However, ensuring the privacy and security of data on a digital platform is often a challenge. A cryptographic task-role-based access control (T-RBAC) approach can be used to protect data privacy. This approach ensures the accessibility of data for authorized consumers and keeps it safe from unauthorized consumers. However, this type of cryptographic approach does not address the issue of trust. In this paper, we propose a comprehensive trust model integrated with a cryptographic T-RBAC to enhance the privacy and security of data stored in cloud storage systems, and suggests that trust models involve inheritance and hierarchy in the roles and tasks of trustworthiness evaluation, where this study aims to identify the most feasible solution for the trust issue in T-RBAC approaches. Risk evaluations regarding other possible flaws of the design are also performed. The proposed design can decrease risk by providing high security for cloud storage systems and improve the quality of decisions of cloud operators and data owners.

Integrating a High-Reliability Multicriteria Trust Evaluation Model with Task Role-Based Access Control for Cloud Services

A novel design of metamaterial structure has been developed to reduce the mutual coupling between two microstrip patch antennas. A split rectangular structure loaded between the two microstrip patches is the method used to decrease coupling. The proposed antenna is designed to operate at a frequency of 28 GHz. This construction is suited for use with mm-wave, 5G antenna systems, and mobile applications. The connection between antennas is significantly improved. The maximum isolation achieved is 29.5 dB by etching the split rectangular structure on the ground of the proposed antenna and on a floated ground between the two patches. The distance between the two elements of the antenna, from edge to edge, is 0.4λ. The design is achieved with CST Studio software.

Reham Arnous

Papers

Mutual Coupling Reduction Between MM-Wave Microstrip Antennas Using Split Rectangular Structure