相关论文: A Secure and Multi-objective Virtual Machine Place…

The use of containers in cloud architectures has become widespread because of advantages such as limited overhead, easier and faster deployment and higher portability. Moreover, they are a suitable architectural solution for deployment of…

In Cloud Computing, the resource provisioning approach used has a great impact on the processing cost, especially when it is used for Big Data processing. Due to data variety, the performance of virtual machines (VM) may differ based on the…

This paper addresses the impact of Virtual Memory Streaming (VMS) technique in provisioning virtual machines (VMs) in cloud environment. VMS is a scaling virtualization technology that allows different virtual machines rapid scale, high…

Virtual machine consolidation describes the process of reallocation of virtual machines (VMs) on a set of target servers. It can be formulated as a mixed integer linear programming problem which is proven to be an NP-hard problem. In this…

The widespread use of cloud computing services is expected to deteriorate a Quality of Service and toincrease the power consumption of ICT devices, since the distance to a server becomes longer than before. Migration of virtual machines…

One of the major distinguishing features of the dynamic multiobjective optimization problems (DMOPs) is the optimization objectives will change over time, thus tracking the varying Pareto-optimal front becomes a challenge. One of the…

We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with…

Infrastructure-as-a-Service (IaaS) clouds have become more popular enabling users to run applications under virtual machines. Energy efficiency for IaaS clouds is still challenge. This paper investigates the energy-efficient scheduling…

Dynamic Multi-objective Optimization Problems (DMOPs) refer to optimization problems that objective functions will change with time. Solving DMOPs implies that the Pareto Optimal Set (POS) at different moments can be accurately found, and…

In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of OFDMA collaborative mobile cloud (CMC) with simultaneous wireless information and power…

We consider allocation problems that arise in the context of service allocation in Clouds. More specifically, we assume on the one part that each computing resource is associated to a capacity constraint, that can be chosen using Dynamic…

Scheduling virtual machines (VMs) on hosts in cloud data centers dictates efficiency and is an NP-hard problem with incomplete information. Prior work improved VM scheduling with predicted VM lifetimes. Our work further improves…

The ever-increasing complexity of HW/SW systems presents a persistent challenge, particularly in safety-critical domains like automotive, where extensive testing is imperative. However, the availability of hardware often lags behind,…

Traditional memory management suffers from metadata overhead, architectural complexity, and stability degradation, problems intensified in cloud environments. Existing software/hardware optimizations are insufficient for cloud computing's…

Support Vector Machine (SVM) algorithm requires a high computational cost (both in memory and time) to solve a complex quadratic programming (QP) optimization problem during the training process. Consequently, SVM necessitates high…

5G networks are going to support a variety of vertical services, with a diverse set of key performance indicators (KPIs), by using enabling technologies such as software-defined networking and network function virtualization. It is the…

With the rapid development of mobile communication, multimedia services have experienced explosive growth in the last few years. The high quantity of mobile users, both consuming and producing these services to and from the Cloud Computing…

Compared to traditional distributed computing environments such as grids, cloud computing provides a more cost-effective way to deploy scientific workflows. Each task of a scientific workflow requires several large datasets that are located…

This paper proposes a conceptual model for a secure and performance-efficient workload management model in cloud environments. In this model, a resource management unit is employed for energy and performance proficient allocation of virtual…

A current trend in networking and cloud computing is to provide compute resources over widely dispersed places exemplified by initiatives like Network Function Virtualisation. This paves the way for a widespread service deployment and can…