A Pareto optimal multi-objective optimisation for parallel dynamic programming algorithm applied in cognitive radio ad hoc networks

Benmammar, Badr; Benmouna, Youcef; Krief, Francine

doi:10.1504/ijcat.2019.098036

Cited by 6 publications

(5 citation statements)

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“…But, using the Pareto concept, it is possible to avoid the constraint to know in advance the possible solutions. Indeed, this is also one of the reasons for the popularity of these approaches based on the concept of Pareto 47 …”

Section: The Proposed Approachmentioning

confidence: 99%

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Multi‐objective task scheduling in cloud computing

Malti

Hakem

Benmammar

2022

Concurrency and Computation

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Summary Cloud computing services are used to fulfill user requests, often expressed in the form of tasks and their execution in such environments requires efficient scheduling strategies that take into account both algorithmic and architectural characteristics. Unfortunately, this problem is known to be NP‐hard in its general form. Despite the fact that several studies have been published in the literature, there are still interesting and relevant questions to be addressed. Indeed, most of the previous studies focus on a single objective and in the case where they deal with a set of objectives, they use a simple compromise function and do not consider how each of the parameters might influence the others. To this end, we propose an efficient task scheduling algorithm which is based on the pollination behavior of flowers and makes use of both Pareto optimality principle and TOPSIS technique to improve the quality of the obtained solutions. Both single and multiobjective optimization variants are investigated. In the latter case, three optimization criteria are considered, namely, minimizing the time makespan or schedule length, the execution cost, and maximizing the overall reliability of the task mapping. Different test‐bed scenarios and QoS metrics were considered and the obtained results corroborate the merits of the proposed algorithm.

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Section: The Proposed Approachmentioning

confidence: 99%

“…Indeed, this is also one of the reasons for the popularity of these approaches based on the concept of Pareto. 47 In the following, we will define the concepts related to Pareto-based multi-objective optimization.…”

Section: Pareto Optimality Based Approachmentioning

confidence: 99%

Multi‐objective task scheduling in cloud computing

Malti

Hakem

Benmammar

2022

Concurrency and Computation

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“…In this work, the effectiveness of the FPA's solutions is evaluated using two-variants of the compromise function: the Pareto optimality concept [4] based on the TOPSIS algorithm [5], and on the other hand, the weighted sum method, the most popular and well-known in optimization processes due to its simplicity. It merges the different quality of service parameters into a singleobjective.…”

Section: Introductionmentioning

confidence: 99%

Task Scheduling in Cloud Computing Based on FPA Metaheuristic Algorithm

Malti

Benmammar

Hakem

2022

2022 19th International Multi-Conference on Systems, Signals &Amp; Devices (SSD)

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In this paper, we propose to address the multiobjective task scheduling issue in cloud computing system in order to find the best assignment of the user-submitted tasks to the cloud resources provided by the cloud service providers. To achieve a high overall performance for computational cloud resources, a good scheduler algorithm is required to meet customer requirements and ensure efficient QoS. To this end, the Flower Pollination Algorithm metaheuristic has been used to orchestrate the trade-offs relationship between three end-user QoS-based criteria, namely reliability, time makespan and execution cost. The results obtained from the experiment conducted with the CloudSim simulator clearly show the interest of our approach based on FPA.

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“…Saoucha and Benmammar [7] have exploited firefly, bat, and cuckoo search algorithms to optimize the communication quality of the SU. Benmammar et al [8] suggested applying to cognitive radio a parallel dynamic programming algorithm for multi-objective Pareto optimum maximization. The approach is used to choose the most compromising solution of the Pareto front.…”

Section: Introductionmentioning

confidence: 99%

An AHP-TOPSIS Integrated Model for QoS-Aware Energy Efficiency in Green Cognitive Radio Networks

Bendella¹,

Benmammar²,

Krief³

2022

RIA

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The selection of the best spectrum band available to meet the quality of service requirements of secondary users without interfering with the transmission of the primary users is considered as a challenge in cognitive radio networks. On the other side, green network is a recent concept that refers to the processes used to optimize a network in order to make it more energy efficient. In this paper, we propose a new algorithm ensuring the selection of the best available spectrum satisfying the demands of the secondary users based on TOPSIS and AHP in OFDM-based cognitive radio networks. We will assess the need for the secondary users in terms of quality of service and energy efficiency, by analyzing the characteristics of the available channels and taking into account the interference generated with the presence of the primary user. It efficiently manages energy because it allows a significant reduction of the transmission power used by the secondary user and therefore presents an effective solution in green networking.

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A Pareto optimal multi-objective optimisation for parallel dynamic programming algorithm applied in cognitive radio ad hoc networks

Cited by 6 publications

References 0 publications

Multi‐objective task scheduling in cloud computing

Multi‐objective task scheduling in cloud computing

Task Scheduling in Cloud Computing Based on FPA Metaheuristic Algorithm

An AHP-TOPSIS Integrated Model for QoS-Aware Energy Efficiency in Green Cognitive Radio Networks

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