scholarly journals Adaptive Resource Allocation and Provisioning in Multi-Service Cloud Environments

2019 ◽  
pp. 372-381
Author(s):  
Anitha Nithya R ◽  
Saran A ◽  
Vinoth R
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Energy Aware ◽  
Research Issues ◽  
Allocation Policy ◽  
Fine Grained ◽  
Policy Problem ◽  
Machine Allocation

Minimizing the energy consumption and resource usage in cloud computing environment is one of the key research issues. Energy aware resource allocation is used to optimize the power consuming by computer resources and storage in cloud. The proposed system is to improve the utilization of computing resources and reduce energy consumption under workload independent quality of service constraints. Using migration for minimizing the number of active physical nodes the dynamic single threshold VM consolidation leverages fine-grained fluctuations in the workloads and continuously reallocates VMs . A genetic algorithm based power-aware scheduling of resource allocation (G-PARS) has been proposed to solve the dynamic virtual machine allocation policy problem. The experiment results show that strategy that has been proposed has a better performance than other strategies, not only in high Quality Of Service(QoS) but also in less energy consumption.

Quality of Experience (QoE) for Wireless Video Over Critical Communication Systems

2017 ◽  
pp. 132-167
Author(s):  
Emad Danish ◽  
Mazin I. Alshamrani
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Communication Systems ◽  
Quality Of Experience ◽  
Service Providers ◽  
Wireless Video ◽  
User Centric ◽  
Near Future

Video streaming is expected to acquire a massive share of the global internet traffic in the near future. Meanwhile, it is expected that most of the global traffic will be carried over wireless networks. This trend translates into considerable challenges for Service Providers (SP) in terms of maintaining consumers' Quality of Experience (QoE), energy consumption, utilisation of wireless resources, and profitability. However, the majority of Radio Resource Allocation (RRA) algorithms only consider enhancing Quality of Service (QoS) and network parameters. Since this approach may end up with unsatisfied customers in the future, it is essential to develop innovative RRA algorithms that adopt a user-centric approach based on users' QoE. This chapter focus on wireless video over Critical communication systems that are inspired by QoE perceived by end users. This chapter presents a background to introduce the reader to this area, followed by a review of the related up-to-date literature.

scholarly journals Energy Aware and Quality of Service Routing Mechanism for Hybrid Internet of Things Network

Computers ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 93
Author(s):  
Eyassu Dilla Diratie ◽  
Durga Prasad Sharma ◽  
Khaldoun Al Agha
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Ieee 802.11 ◽  
Video Surveillance ◽  
Sensor Nodes ◽  
Energy Aware ◽  
Visual Sensor ◽  
Routing Mechanism

Wireless Multimedia Sensor Networks (WMSNs) based on IEEE 802.11 mesh networks are effective and suitable solutions for video surveillance systems in detecting intrusions in selected monitored areas. The IEEE 802.11-based WMSNs offer high bit rate video transmissions but are challenged by energy inefficiency issues and concerns. To resolve the energy inefficiency challenges, the salient research studies proposed a hybrid architecture. This newly evolved architecture is based on the integration of IEEE 802.11-based mesh WMSNs along with the LoRa network to form an autonomous and high bitrate, energy-efficient video surveillance system. This paper proposes an energy-aware and Quality of Service (QoS) routing mechanism for mesh-connected visual sensor nodes in a hybrid Internet of Things (IoT) network. The routing algorithm allows routing a set of video streams with guaranteed bandwidth and limited delay using as few visual sensor nodes as possible in the network. The remaining idle visual sensor nodes can be turned off completely, and thus it can significantly minimize the overall energy consumption of the network. The proposed algorithm is numerically simulated, and the results show that the proposed approach can help in saving a significant amount of energy consumption while guaranteeing bandwidth and limited delay.

scholarly journals Energy-Efficient IoT Service Brokering with Quality of Service Support

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 693
Author(s):  
Giacomo Tanganelli ◽  
Enzo Mingozzi
Keyword(s):  
Quality Of Service ◽  
Energy Efficient ◽  
Energy Aware ◽  
Allocation Policy ◽  
Service Support ◽  
Service Allocation ◽  
Iot Platforms ◽  
Iot Devices ◽  
The Internet Of Things

The Internet of Things (IoT) is becoming real, and recent studies highlight that the number of IoT devices will significantly grow in the next decade. Such massive IoT deployments are typically made available to applications as a service by means of IoT platforms, which are aware of the characteristics of the connected IoT devices–usually constrained in terms of computation, storage and energy capabilities–and dispatch application’s service requests to appropriate devices based on their capabilities. In this work, we develop an energy-aware allocation policy that aims at maximizing the lifetime of all the connected IoT devices, whilst guaranteeing that applications’ Quality of Service (QoS) requirements are met. To this aim, we formally define an IoT service allocation problem as a non-linear Generalized Assignment Problem (GAP). We then develop a time-efficient heuristic algorithm to solve the problem, which is shown to find near-optimal solutions by exploiting the availability of equivalent IoT services provided by multiple IoT devices, as expected especially in the case of massive IoT deployments.

scholarly journals NSIS-Based Quality of Service and Resource Allocation in Ethernet Networks

2006 ◽  
pp. 132-142
Author(s):  
M. Carmo ◽  
B. Carvalho ◽  
J. Sá Silva ◽  
E. Monteiro ◽  
P. Simões ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Ethernet Networks

Energy and Quality Aware Multi-Objective Resource Allocation Algorithm in Cloud

2021 ◽  
pp. 2150052
Author(s):  
Koné Kigninman Désiré ◽  
Eya Dhib ◽  
Nabil Tabbane ◽  
Olivier Asseu
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Search Algorithm ◽  
Fitness Function ◽  
Video Quality ◽  
Minimum Energy ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Energy Aware ◽  
Resource Allocation Algorithm

Cloud gaming has become the new service provisioning prototype that hosts the video games in the cloud and broadcasts the interactive game streaming to the players through the Internet. Here, the cloud must use massive resources for video representation and its streaming when several simultaneous players reach a particular point. Alternatively, various players may have separate necessities on Quality-of Experience, like low delay, high-video quality, etc. The challenging task is providing better service by the fixed cloud resource. Hence, there is a necessity for an energy-aware multi-resource allocation in the cloud. This paper devises a Fractional Rider-Harmony search algorithm (Fractional Rider-HSA) for resource allocation in the cloud. The Fractional Rider-HSA combines fractional calculus, Rider Optimization algorithm (ROA), and HSA. Moreover, the fitness function, like mean opinion score (MOS), gaming experience loss, fairness, energy consumption, and network parameters, is considered to determine the optimal resource allocation. The proposed model produces the maximal MOS of 0.8961, maximal gaming experience loss (QE) of 0.998, maximal fairness of 0.9991, the minimum energy consumption of 0.3109, and minimal delay 0.2266, respectively.

Sign in / Sign up

Export Citation Format

Share Document