相关论文: A Disk Scheduling Algorithm Based on ANT Colony Op…

Congestion is a problem of paramount importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources. Sensor nodes are prone to failure and…

Ant Colony Optimization algorithm is a magnificent heuristics technique based on the behavior of ants. Parallel computing is a means to achieve the desired results in commensurable execution time. Parallelization of Ant Colony Optimization…

Nowadays swarm intelligence-based algorithms are being used widely to optimize the dynamic traveling salesman problem (DTSP). In this paper, we have used mixed method of Ant Colony Optimization (AOC)and gradient descent to optimize DTSP…

Cloud computing is a concept introduced in the information technology era, with the main components being the grid, distributed, and valuable computing. The cloud is being developed continuously and, naturally, comes up with many…

This paper addresses resource allocation for entanglement distribution in multi-channel quantum networks. A system model is proposed that integrates a multi-channel quantum network architecture with heterogeneous link characteristics and…

Spatio-Temporal Convolutional Neural Networks (ST-CNN) allow extending CNN capabilities from image processing to consecutive temporal-pattern recognition. Generally, state-of-the-art (SotA) ST-CNNs inflate the feature maps and weights from…

The Job Shop Schedule Problem (JSSP) refers to the ability of an agent to allocate tasks that should be executed in a specified time in a machine from a cluster. The task allocation can be achieved from several methods, however, this report…

Advances in diffusion models for generative artificial intelligence have recently propagated to the time series (TS) domain, demonstrating state-of-the-art performance on various tasks. However, prior works on TS diffusion models often…

In this paper we analyze the problem of optimal task scheduling for data centers. Given the available resources and tasks, we propose a fast distributed iterative algorithm which operates over a large scale network of nodes and allows each…

We study the problem of scheduling delay-sensitive jobs over spot and on-demand cloud instances to minimize average cost while meeting an average delay constraint. Jobs arrive as a general stochastic process, and incur different costs based…

Self Organizing Networks (SONs) are considered as vital deployments towards upcoming dense cellular networks. From a mobile carrier point of view, continuous coverage optimization is critical for better user perceptions. The majority of SON…

Ant Colony Optimization (ACO) is a very popular metaheuristic for solving computationally hard combinatorial optimization problems. Runtime analysis of ACO with respect to various pseudo-boolean functions and different graph based…

The objective of this paper is to take some aspects of disk scheduling and scheduling algorithms. The disk scheduling is discussed with a sneak peak in general and selection of algorithm in particular.

The hypothetical global delivery schedule of Santa Claus must follow strict rolling night-time windows that vary with the Earth's rotation and obey an energy budget that depends on payload size and cruising speed. To design this schedule,…

Within modern warehouse scenarios, the rapid expansion of e-commerce and increasingly complex, multi-level storage environments have exposed the limitations of traditional AGV (Automated Guided Vehicle) path planning methods--often reliant…

Our paper presents solutions that can significantly improve the delay performance of putting and retrieving data in and out of cloud storage. We first focus on measuring the delay performance of a very popular cloud storage service Amazon…

Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) are simple, easy to implement, their robustness to control parameters, and their computational efficiency when compared with mathematical algorithms and other heuristic…

In this paper, we present a novel multi-objective ant colony system algorithm for virtual machine (VM) consolidation in cloud data centers. The proposed algorithm builds VM migration plans, which are then used to minimize over-provisioning…

We consider a computation offloading system where jobs are processed sequentially at a local server followed by a higher-capacity cloud server. The system offers two service modes, differing in how the processing is split between the…

Intelligent real-time applications, such as video surveillance, demand intensive computation to extract status information from raw sensing data. This poses a substantial challenge in orchestrating computation and communication resources to…