Tiarrah Computing: The Next Generation of Computing

Pradhananga, Yanish; Rajarajeswari, P.

doi:10.11591/ijict.v6i2.pp129-138

Cited by 1 publication

(3 citation statements)

References 6 publications

(6 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, network load reduction leads to reduce collisions and traffic congestion. As above (1) and (2) demonstrate, throughput is inversely proportional to the total delay, while network load is proportional to the network overall delay. The simulation results in Subsection 5.3 prove that the throughput is influenced by reducing total delay for tuples execution more than network load.…”

Section: ∑ (2)mentioning

confidence: 79%

“…Network load: is the amount of data tuples that travels in the network and occupies it for a certain amount of time. It is evaluated by using (2), where Nd i denotes the total delay of the i th tuple and Nw i denotes the i th tuple size.…”

Section: Performance Metricsmentioning

confidence: 99%

“…Edge computing paradigm (or similar platforms as Mobile Edge Computing (MEC), fog computing or cloudlet) was introduced, due to the fact that the mobile and IoT applications demands and resources requirements have increased, e.g. ; computing platforms [1][2][3][4][5]. Consequently, the necessity of a new platform that supports these applications demands within a close proximity of computational and storage resources, within a geographically distributed area, are really a necessity.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cooperative-hierarchical based edge-computing approach for resources allocation of distributed mobile and IoT applications

Aljarah¹,

Shurman²,

Alnabelsi³

2020

IJECE

View full text Add to dashboard Cite

<span lang="EN-US">Using mobile and Internet of Things (IoT) applications is becoming very popular and obtained researchers’ interest and commercial investment, in order to fulfill future vision and the requirements for smart cities. These applications have common demands such as fast response, distributed nature, and awareness of service location. However, these requirements’ nature cannot be satisfied by central systems services that reside in the clouds. Therefore, edge computing paradigm has emerged to satisfy such demands, by providing an extension for cloud resources at the network edge, and consequently, they become closer to end-user devices. In this paper, exploiting edge resources is studied; therefore, a cooperative-hierarchical approach for executing the pre-partitioned applications’ modules between edges resources is proposed, in order to reduce traffic between the network core and the cloud, where this proposed approach has a polynomial-time complexity. Furthermore, edge computing increases the efficiency of providing services, and improves end-user experience. To validate our proposed cooperative-hierarchical approach for modules placement between edge nodes’ resources, iFogSim toolkit is used. The obtained simulation results show that the proposed approach reduces network’s load and the total delay compared to a baseline approach for modules’ placement, moreover, it increases the network’s overall throughput.</span>

show abstract

Section: ∑ (2)mentioning

confidence: 79%

Section: Performance Metricsmentioning

confidence: 99%