Neighborhood Search Based Improved Bat Algorithm for Web Service Composition

Dahan, Fadl

doi:10.32604/csse.2023.031142

Cited by 3 publications

(6 citation statements)

References 29 publications

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“…The search for optimal WSs combination to satisfy these needs requires high computation time that increases while the WSC scale increases. In this work, we introduce an extension of our previous works on improving the ABC [5][6][7] and BA [8]. A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search.…”

Section: Figure 1: the Wsc Problem Representative Modelmentioning

confidence: 99%

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Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

Ahanger¹,

Dahan²,

Tariq³

2023

Computer Systems Science and Engineering

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In the Internet of Things (IoT), the users have complex needs, and the Web Service Composition (WSC) was introduced to address these needs. The WSC's main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services (QoS) constraints. The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints. In this paper, we introduce an extension of our previous works on the Artificial Bee Colony (ABC) and Bat Algorithm (BA). A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search. The bat agent is used to improve the solution of exhausted bees after a threshold (limits), and also an Elitist Strategy (ES) is added to BA to increase the convergence rate. The performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria (average fitness values, best fitness values, and execution time) that were measured for 30 different runs. These datasets are created from real-world datasets and artificially to form different scale sizes of WSC datasets. The results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to competitors. The Wilcoxon signed-rank significant test is used where the proposed algorithm results significantly differ from other algorithms on 100% of datasets.

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Section: Figure 1: the Wsc Problem Representative Modelmentioning

confidence: 99%

“…The third one is the investigation of the differences between the flying and resetting mechanisms. Dahan [8] proposed an enhancement to BA based on three strategies: improved the initialization and searching of BA agents. The self-adaptive Doppler with local search is introduced in [23] to enhance the BA search mechanism.…”

Section: Ba Related Workmentioning

confidence: 99%

Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

Ahanger¹,

Dahan²,

Tariq³

2023

Computer Systems Science and Engineering

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“…A new algorithm based on the BA proposed by Dahan [19] uses the neighborhood search mechanism, cooperative population initialization, and the elitist mechanism. Kouicem et al [20] proposed a novel BA based on the self-adaptive local search strat-egy and Doppler effect compensation to enhance the convergence of BA and avoid the stagnation problem.…”

Section: Related Workmentioning

confidence: 99%

“…This strategy introduces a variant of the neighborhood search proposed in our previous works [18,19]. The proposed adaptive search balanced the diversity and concentration of swarm-based algorithms [12].…”

Section: Neighborhood Search Strategymentioning

confidence: 99%

An Improved Whale Optimization Algorithm for Web Service Composition

Dahan

2022

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In the current circumstance, the Web Service Composition (WSC) was introduced to address complex user needs concerning the Quality of Services (QoS). In the WSC problem, the user needs are divided into a set of tasks. The corresponding web services are retrieved from the web services discovery according to the functionality of each task, and have different non-functional constraints, such as QoS. The WSC problem is a multi-objective optimization problem and is classified as an NP-hard problem. The whale optimization algorithm (WOA) is proven to solve complex multi-objective optimization problems, and it has the advantage of easy implementation with few control parameters. In this work, we contribute to improving the WOA algorithm, where different strategies are introduced to enhance its performance and address its shortcomings, namely its slow convergence speed, which produces low solution accuracy for the WSC problem. The proposed algorithm is named Improved Whale Optimization Algorithm (IWOA) and has three different strategies to enhance the performance of the WOA. Firstly, the Sine chaos theory is proposed to initiate the WOA’s population and enhance the initialization diversity. Secondly, a Lévy flight mechanism is proposed to enhance the exploitation and exploration of WOA by maintaining the whales’ diversity. Further, a neighborhood search mechanism is introduced to address the trade-off between exploration and exploitation searching mechanisms. Different experiments are conducted with datasets on 12 different scales (small, medium, and large), and the proposed algorithm is compared with standard WOA and five state-of-the-art swarm-based algorithms on 30 different independent runs. Furthermore, four evaluation criteria are used to validate the comparison: the average fitness value, best fitness values, standard deviation, and average execution time. The results show that the IWOA enhanced the WOA algorithm’s performance, where it got the better average and best fitness values with a low variation on all datasets. However, it ranked second regarding average execution time after the WOA, and sometimes third after the WOA and OABC, which is reasonable because of the proposed strategies.

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“…Therefore, it is necessary to study the evolution of the service network, thus to grasp the development trend of individual services. Moreover, proactive perception of the excellent services based on the evolution of service network is crucial for intelligent service applications, such as service recommendation [10,11], service optimization composition [12][13][14][15], and dynamic reconfiguration of composite services [16][17][18]. Therefore, how to proactively perceive the emergence of premium services based on the evolution of service network has become an critical issue in MEC.…”

Section: Introductionmentioning

confidence: 99%

Perception of Premium Services Based on the Evolution of Hyper-service Network in Mobile Edge Computing

Zhang,

Liu,

Chu

et al. 2024

Preprint

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Recently, massive services from multiple domains are available on the network with the rapid development of Mobile Edge Computing (MEC) technology. These various services construct a service network through services' collaboration, which can provide users with rich resources at anytime and anywhere. However, in MEC, due to the proliferation of services, as well as the dynamics of Quality of Service (QoS), it becomes more and more difficult for users to discover the premium services effectively, which seriously impacts users' satisfaction and the utilization of resources. Therefore, how to proactively perceive the emergence of premium services in the service networks has become an challenge. To tackle this issue, we propose a method for perception of the premium services based on the evolution of hyper-service network (named as PPSHSN). First, based on the hypergraph theory, we construct a hyper-service network with the optimal connection method; Then, we develop the evolution mechanism of the hyper-service network and optimize the hyper-service network with the hyperdegree premium value evolution algorithm, thus to conduct the evolution of the service networks. Next, we devise the evaluation indexes based on the topological characteristics of hypergraphs, which are updated according to the evolution of the hyper-service network. Finally, we complete perception of premium services based on the evolution results of the hyper-service network. The effectiveness and feasibility of our proposed method are verified through extensive simulation experiments.

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Neighborhood Search Based Improved Bat Algorithm for Web Service Composition

Cited by 3 publications

References 29 publications

Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

An Improved Whale Optimization Algorithm for Web Service Composition

Perception of Premium Services Based on the Evolution of Hyper-service Network in Mobile Edge Computing

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