Application of Ant Colony Algorithm in Cloud Resource Scheduling Based on Three Constraint Conditions

Yang, Zhen; Aiwan, Fan

doi:10.14257/astl.2016.123.40

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…In this section, results of proposed scheme is compared with ''A Trusted Real-Time Scheduling Model for Wireless Sensor Networks'' (referred as TRTSM scheme in graphs) [31]. Figure 11 indicates that increase in node density w.r.t.…”

Section: Results Analysismentioning

confidence: 99%

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Agent driven resource scheduling in wireless sensor networks: fuzzy approach

Kori¹,

Kakkasageri²

2021

Int. j. inf. tecnol.

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Wireless sensor network (WSN) provides a significant contribution in emerging fields such as ubiquitous computing, ambient intelligence, Internet of Things, etc. WSN is a highly distributed computing network of tiny sensors which are self-conscious and are deployed in different geographical area randomly for multiple applications. These tiny sensor motes are insecure about resources such as bandwidth, battery, and communication range, etc. To increase the life span of WSN, effective utilization of available network resources is very important. Consequently, WSN's efficient and productive resource management is a challenging task involving the identification of resources, scheduling of resources, allocation of resources. In this paper, a type-2 fuzzy logic system (T2FLS) based resource scheduling technique using a software agent approach to resolve the scheduling issues by considering energy, number of neighboring nodes, and available bandwidth of WSN is proposed. Proposed software agent based resource scheduling scheme comprises of node agency (NA) and sink agency (SA). Both agencies comprised of a mobile agent and static agent. SA periodically gathers information related to a node such as available energy, bandwidth, and degree of connectivity collected by NA. Based on these parameters SA makes the suitable resource scheduling decision. Simulation results show that the performance of the proposed type-2 fuzzy with agent based approach is better as compared with the trusted real time scheduling model for wireless sensor networks (TRTSM) scheme in terms of scheduling accuracy, scheduling delay, and bandwidth utilized.

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Section: Results Analysismentioning

confidence: 99%

“…An Ant Colony Algorithm (ACA) based on the three constraint conditions to determine the issue of resource scheduling in edge/fog and cloud computing is presented in [31]. Ant colony algorithm operates in three phases: information elicitation factor, expect inspiration factor, and pheromone update strategy.…”

Section: Literature Surveymentioning

confidence: 99%

Agent driven resource scheduling in wireless sensor networks: fuzzy approach

Kori¹,

Kakkasageri²

2021

Int. j. inf. tecnol.

View full text Add to dashboard Cite

show abstract

“…Ant colony algorithm is a random search algorithm, which has been applied in the research of TSP class problems. It uses natural ants routing way of artificial simulation, the main characteristic is to search for the optimal path through the positive feedback, the distributed cooperation [22][23][24][25].…”

Section: Traditional Ant Colony Algorithmmentioning

confidence: 99%

“…This article is a revised and expanded version of a paper entitled Application of Ant colony Algorithm in Cloud Resource Scheduling Based on Three Constraint Conditions presented at The 5th International Conference on Computer Science and Technology April 22-23, 2016 at Suzhou Youngor Leidisen Hotel, Suzhou, China.…”

Section: Appendixmentioning

confidence: 99%