Adaptation to Dynamic Resource Availability in Ad Hoc Grids through a Learning Mechanism

2008 ◽  
Author(s):  
Behnaz Pourebrahimi ◽  
Koen Bertels
Keyword(s):  
Resource Availability ◽  
Ad Hoc ◽  
Learning Mechanism ◽  
Dynamic Resource

scholarly journals Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs

2020 ◽  
Vol 13 (41) ◽  
pp. 4332-4350
Author(s):  
K Shashi Raj ◽  
Keyword(s):  
Resource Allocation ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Dynamic Resource Allocation ◽  
Allocation Strategy ◽  
Secondary Users ◽  
Allocation Model ◽  
Resource Allocation Strategy ◽  
Dynamic Resource ◽  
Mobile Ad Hoc

Background/Objectives: Being dynamic in nature, Mobile Ad-hoc Network (MANET) requires robust resource allocation strategy that can ensure both optimal transmission reliability and resource efficiency to meet Quality of Service (QoS) demands. The objective of this research is to address interference resilience requirement in MANETs which is must due to greedy nature of nodes especially when accessing resource or bandwidth and develop a highly robust stochastic prediction based resource allocation strategy. Methods: The proposed Interference Resilient Stochastic Prediction based Dynamic Resource Allocation model for Cognitive MANET (ISP-DRACM) intends to enable optimal resource allocation under interweave and underlay network setup with instantaneous as well as average interference conditions. It employs a joint power management and resource allocation strategy where it intends to maximize the weighted sum-rate of the secondary users under certain defined conditions like average power and stochastic interference level. Findings/Novelty: Inculcating resource allocation problem as controlled Markov Decision Process using Hidden Markov Model (HMM) and Lagrange relaxation, our proposed model achieves better resource allocation under limited noise or interference condition and hence achieves both costeffectiveness as well as QoS provision. This method has exhibited satisfactory performance towards spectrum allocation to the secondary users without imposing any significant interference for both interweave as well as underlay Cognitive Radio setup. Keywords: Cognitive mobile ad-hoc network; stochastic prediction; interference resilience; channel state information; dynamic resource allocation; underlay and overlay cognitive MANET

Deadline-Aware MapReduce Job Scheduling with Dynamic Resource Availability

2019 ◽  
Vol 30 (4) ◽  
pp. 814-826 ◽  
Author(s):  
Dazhao Cheng ◽  
Xiaobo Zhou ◽  
Yinggen Xu ◽  
Liu Liu ◽  
Changjun Jiang
Keyword(s):  
Resource Availability ◽  
Job Scheduling ◽  
Dynamic Resource

scholarly journals A Review of Dynamic Resource Allocation Framework for Large Amount of Cloud Enterprises

2021 ◽  
Vol 12 (2) ◽  
pp. 1280-1284
Author(s):  
B Vijaya Laxmi, Et. al.
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Ad Hoc ◽  
Service Level ◽  
Dynamic Resource Allocation ◽  
Research Network ◽  
Data Handling ◽  
Parallel Data ◽  
Flexible Resource ◽  
Dynamic Resource

Cloud computing is an on-demand service because it offers dynamic flexible resource allocation for reliable and guaranteed services in pay as-you-use manner. Because of the consistently increasing demands of the clients for services or resources, it gets hard to allocate resources accurately to the client demands to satisfy their solicitations and also to take care of the Service Level Agreements (SLA) gave by the service suppliers. Dynamic resource allocation problem is one of the most challenging problems in the resource management problems. The dynamic resource allocation in cloud computing has attracted attention of the research network in the last couple of years. Many researchers around the world have thought of new ways of facing this challenge. Ad-hoc parallel data handling has arisen to be one of the executioner applications for Infrastructure-as-a-Service (IaaS) cloud. Number of Cloud supplier companies has started to incorporate frameworks for parallel data handling in their item which making it easy for clients to access these services and to convey their programs. The handling frameworks which are at present utilized have been intended for static and homogeneous bunch arrangements. So the allocated resources may be inadequate for large parts of the submitted tasks and unnecessarily increase preparing cost and time. Again because of opaque nature of cloud, static allocation of resources is conceivable, yet the other way around in dynamic situations. The proposed new generic data handling framework is expected to expressly misuse the dynamic resource allocation in cloud for task scheduling and execution.

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