Improving quality‐of‐service in fog computing through efficient resource allocation

2020 ◽  
Vol 36 (4) ◽  
pp. 1527-1547
Author(s):  
Sathish Kumar Mani ◽  
Iyapparaja Meenakshisundaram
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Fog Computing ◽  
Efficient Resource

scholarly journals Energy Efficient Resource Allocation for M2M Devices in 5G

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1830 ◽  
Author(s):  
Anum Ali ◽  
Ghalib A. Shah ◽  
Junaid Arshad
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Threshold Value ◽  
Second Phase ◽  
Resource Allocation Algorithm ◽  
Power Profile ◽  
5G Network ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation

Resource allocation for machine-type communication (MTC) devices is one of the keys challenges in the 5G network as it affects the lifetime of battery powered devices and also the quality of service of the applications. MTC devices are battery restrained and cannot afford a lot of power consumption due to spectrum usage. In this paper, we propose a novel resource allocation algorithm termed threshold controlled access (TCA) protocol. We propose a novel technique of uplink resource allocation in which the devices make a decision of resource allocation blocks based on their battery status and related application’s power profile that eventually leads to required quality of service (QoS) metric. The first phase of the TCA algorithm selects the number of carriers to be allocated to a certain device for the better lifetime of low power MTC devices. In the second phase, the efficient solution is implemented through inducing a threshold value. A certain value of the threshold is selected through a mapping based on a QoS metric. The threshold enhances the selection of subcarriers for less powered devices, such as small e-health sensors. The algorithm is simulated for the physical layer of the 5G network. Simulation results show that the proposed algorithm is less complex and achieves better performance when compared to existing solutions in the literature.

Simulation and Emulation Tools for Fog Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Simar Preet Singh ◽  
Rajesh Kumar ◽  
Anju Sharma ◽  
S. Raji Reddy ◽  
Priyanka Vashisht
Keyword(s):  
Quality Of Service ◽  
Programming Languages ◽  
Traffic Management ◽  
Fog Computing ◽  
Research Work ◽  
Research Experience ◽  
Computing Paradigm ◽  
Quality Of Service Parameters ◽  
User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

scholarly journals Fog Computing-Assisted Energy-Efficient Resource Allocation for High-Mobility MIMO-OFDMA Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Lingyun Lu ◽  
Tian Wang ◽  
Wei Ni ◽  
Kai Li ◽  
Bo Gao
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
High Speed ◽  
Optimization Problem ◽  
Fog Computing ◽  
High Mobility ◽  
High Speed Train ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation ◽  
System Configurations

This paper presents a suboptimal approach for resource allocation of massive MIMO-OFDMA systems for high-speed train (HST) applications. An optimization problem is formulated to alleviate the severe Doppler effect and maximize the energy efficiency (EE) of the system. We propose to decouple the problem between the allocations of antennas, subcarriers, and transmit powers and solve the problem by carrying out the allocations separately and iteratively in an alternating manner. Fast convergence can be achieved for the proposed approach within only several iterations. Simulation results show that the proposed algorithm is superior to existing techniques in terms of system EE and throughput in different system configurations of HST applications.

Quality of service-aware approaches in fog computing

2020 ◽  
Vol 33 (8) ◽  
pp. e4340 ◽  
Author(s):  
Mostafa Haghi Kashani ◽  
Amir Masoud Rahmani ◽  
Nima Jafari Navimipour
Keyword(s):  
Quality Of Service ◽  
Fog Computing
Sign in / Sign up

Export Citation Format

Share Document