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The purpose of this study is to verify that if applications categories are segmented and resources are allocated based on their specific category, how effective scheduling can be done?.

This paper proposes a scheduling framework for IoT application jobs, based upon the Quality of Service (QoS) parameters, which works at coarse grained level to select a fog environment and at fine grained level to select a fog node. Fog environment is chosen considering availability, physical distance, latency and throughput. At fine grained (node selection) level, a probability triad (C, M, G) is anticipated using Naïve Bayes algorithm which provides probability of newly submitted application job to fall in either of the categories Compute (C) intensive, Memory (M) intensive and GPU (G) intensive.

Experiment results showed that the proposed framework performed better than traditional cloud and fog computing paradigms.

The proposed framework combines types of applications and computation capabilities of Fog computing environment, which is not carried out to the best of knowledge of authors.

The purpose of this paper is to report the design of a lightweight tree-shaped support structure for fused deposition modeling (FDM) three-dimensional (3D) printed models when the printing path is considered as a constraint.

A hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to address the topology optimization of the tree-shaped support structures, where GA optimizes the topologies of the trees and PSO optimizes the geometry of a fixed tree-topology. Creatively, this study transforms each tree into an approximate binary tree such that GA can be applied to evolve its topology efficiently. Unlike FEM-based methods, the growth of tree branches is based on a large set of FDM 3D printing experiments.

The hybrid of GA and PSO is effective in reducing the volume of the tree supports. It is shown that the results of the proposed method lead to up to 46.71% material savings in comparison with the state-of-the-art approaches.

The proposed approach requires a large number of printing experiments to determine the function of the yield length of a branch in terms of a set of critical parameters. For brevity, one can print a small set of tree branches (e.g. 30) on a single platform and evaluate the function, which can be used all the time after that. The steps of GA for topology optimization and those of PSO for geometry optimization are presented in detail.

The proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating complex models using the FDM technique. It can be adapted to the design of support structures for other additive manufacturing techniques such as Stereolithography and selective laser melting.

This paper aims to present an approach for a bio‐inspired decentralization topology control mechanism, called force‐based genetic algorithm (FGA), where a genetic algorithm (GA) is run by each holonomic autonomous vehicle (HAV) in a mobile ad hoc network (MANET) as software agent to achieve a uniform spread of HAVs and to provide a fully connected network over an unknown geographical terrain. An HAV runs its own FGA to decide its next movement direction and speed based on local neighborhood information, such as obstacles and the number of neighbors, without a centralized control unit or global knowledge.

The objective function used in FGA is inspired by the equilibrium of the molecules in physics where each molecule tries to be in the balanced position to spend minimum energy to maintain its position. In this approach, a virtual force is assumed to be applied by the neighboring HAVs to a given HAV. At equilibrium, the aggregate virtual force applied to an HAV by its neighbors should sum up to zero. If the aggregate virtual force is not zero, it is used as a fitness value for the HAV. The value of this virtual force depends on the number of neighbors within the communication range of R_com and the distance among them. Each chromosome in our GA‐based framework is composed of speed and movement direction. The FGA is independently run by each HAV as a topology control mechanism and only utilizes information from neighbors and local terrain to make movement and speed decisions to converge towards a uniform distribution of HAVs. The authors developed an analytical model, simulation software and several testbeds to study the convergence properties of the FGA.

The paper finds that coverage‐centric, bio‐inspired, mobile node deployment algorithm ensures effective sensing coverage for each mobile node after initial deployment. The FGA is also an energy‐aware self‐organization framework since it reduces energy consumption by eliminating unnecessary excessive movements. Fault‐tolerance is another important feature of the GA‐based approach since the FGA is resilient to losses and malfunctions of HAVs. Furthermore, the analytical results show that the authors' bio‐inspired approach is effective in terms of convergence speed and area coverage uniformity. As seen from the experimental results, the FGA delivers promising results for uniform autonomous mobile node distribution over an unknown geographical terrain.

The proposed decentralized and bio‐inspired approach for autonomous mobile nodes can be used as a real‐time topology control mechanism for commercial and military applications since it adapts to local environment rapidly but does not require global network knowledge.

Despite the COVID-19 recession, the collection of zakat (almsgiving) managed by the National Board of Zakat Republic of Indonesia (BAZNAS RI) has increased, especially during Ramaḍān 1441 Hijra. Previous works show a positive relationship between digital zakat campaign and zakat collection. This paper aims to study the means of digital zakat campaign during COVID-19 outbreak. This topic is theoretically and practically important in the emerging debate of Islamic marketing, notably in Islamic social finance field.

This paper uses a qualitative research approach. A case study is engaged in the selection of BAZNAS RI for a detailed discussion of a zakat organisation. Meanwhile, a netnographic approach is used to analyse the number of 549 posts from BAZNAS RI’s social media, which are Facebook, Instagram, Twitter and YouTube. Furthermore, a qualitative software analysis of NVivo 12 Plus is used in performing the analytical procedures.

This work explains the means of digital zakat campaign during COVID-19 outbreak with a case of BAZNAS RI. It is identified the number of 6 parent nodes and 64 child nodes from the analysis using NVivo 12 Plus. The authors’ parent nodes are “donation”, “infaq” (Islamic spending for charities), “Ramaḍān matters”, “ṣadaqah” (voluntary charity), “virtual events” and “zakat”. These nodes detail digital campaign of BAZNAS RI posted in its social media during COVID-19 period in Ramaḍān. A theoretical implication of inclusive marketing is derived from the analysis. It explains that the inclusiveness of digital contents is practically significant in campaigning zakat as a religious obligation that contributes to social and financial benefits.

This paper does not claim a positivist perspective on the relationship between digital zakat campaign and zakat collection. Instead, this paper explores in-depth the practice of digital zakat campaign, which the previous study confirms its association with a muzakki’s (Muslims who are obliged to pay zakat) decision to pay zakat.

This paper establishes the Islamic marketing theory that is derived from industrial practices. The inclusiveness of digital contents in zakat campaign is critical in activating zakat as a religious obligation that authentically shapes the social and economic processes of a Muslim community. This theory is practically important for 'amils (employees) of zakat institution who work in the marketing division, chiefly to create such contents to post in social media.

The authors’ node of zakat distribution for COVID-19 relief indicates the importance of a formalised zakat institution to actualise zakat’s role in handling socioeconomic problems. Thus, paying zakat formally in an authorised organisation may contribute to a greater social contribution and maṣlaḥah (public interest) than paying it informally without any effective measurement.

This study contributes to the novelty in the Islamic marketing debate within two folds. First, this paper is among the pioneers in studying digital zakat campaign during COVID-19 outbreak by using a netnographic approach. Therefore, a theoretical implication derived from industrial practices is contributed. Second, this paper details the steps in using NVivo 12 Plus to analyse the unstructured data sampled from the internet. The future studies may thus refer to this work to understand the application of netnography and the procedures in analysing data from social media using this software.

The software virtual machine (SVM) concept is described as a methodology to reduce the manpower required to implement and maintain finite element software. A SVM provides the engineering programmer with high‐level languages to facilitate the structuring and management of data, to define and interface process modules, and to manage computer resources. A prototype finite element system has been successfully implemented using the SVM approach. Development effort is significantly reduced compared to a conventional all‐FORTRAN approach. The impact on execution efficiency of the SVM is described along with special procedures developed to minimize overhead in compute‐bound modules. Planned extensions of capabilities in the SVM used by the authors are outlined.

This paper aims to identify the effect of social structure variables on the purchase of virtual goods. Using field data, it also tests whether their effects on a social networking service are dynamic.

To achieve the research objectives, the authors have applied the random effects panel Tobit model with actual time-series corporate data to explain a link between network structure factors and actual behavior on social networking services.

The authors have found that various network structure variables such as in-degree, in-closeness centrality, out-closeness centrality and clustering coefficients are significant predictors of virtual item sales; while the constraint is marginally significant, out-degree is not significant. Furthermore, these variables are time-varying, and the dynamic model performs better in a model fit than the static one.

The findings will help social networking service (SNS) operators realize the importance of understanding network structure variables and personal motivations or the behavior of consumers.

This study provides implications in that it uses various and dynamic network structure variables with panel data.

In the past few decades, the wireless sensor network (WSN) has become the more vital one with the involvement of the conventional WSNs and wireless multimedia sensor networks (WMSNs). The network that is composed of low-power, small-size, low-cost sensors is said to be WSN. Here, the communication information is handled using the multiple hop and offers only a simple sensing data, such as humidity, temperature and so on, whereas WMSNs are referred as the distributed sensing networks that are composed of video cameras, which contain the sector sense area. These WMSNs can send, receive and process the video information data, which is more intensive and complicated by wrapping with wireless transceiver. The WSNs and the WMSNs are varied in terms of their characteristic of turnablity and directivity.

The main intention of this paper is to maximize the lifetime of network with reduced energy consumption by using an advanced optimization algorithm. The optimal transmission radius is achieved by optimizing the system parameter to transmit the sensor information to the consequent sensor nodes, which are contained within the range. For this optimal selection, this paper proposes a new modified lion algorithm (LA), the so-called cub pool-linked lion algorithm (CLA). The next contribution is on the optimal selection of cluster head (CH) by the proposed algorithm. Finally, the performance of proposed model is validated and compared over the other traditional methods in terms of network energy, convergence rate and alive nodes.

The proposed model's cost function relies in the range of 74–78. From the result, it is clear that at sixth iteration, the proposed model’s performance attains less cost function, that is, 11.14, 9.78, 7.26, 4.49 and 4.13% better than Genetic Algorithm (GA), Dragonfly Algorithm (DA), Particle Swarm Optimization (PSO), Glowworm Swarm Optimization (GSO) and Firefly (FF), correspondingly. The performance of the proposed model at eighth iteration is 14.15, 7.96, 4.36, 7.73, 7.38 and 3.39% superior to GA, DA, PSO, GSO, FF and LA, correspondingly with less convergence rate.

This paper presents a new optimization technique for increasing the network lifetime with reduced energy consumption. This is the first work that utilizes CLA for optimization problems.

Tree pattern is at the core of XML queries. The tree patterns in XML queries typically contain redundancies, especially when broad integrity constraints (ICs) are present and considered. Apparently, tree pattern minimization has great significance for efficient XML query processing. Although various minimization schemes/algorithms have been proposed, none of them can exploit broad ICs for thoroughly minimizing the tree patterns in XML queries. The purpose of this research is to develop an innovative minimization scheme and provide a novel implementation algorithm.

Query augmentation/expansion was taken as a necessary first‐step by most prior approaches to acquire XML query pattern minimization under the presence of certain ICs. The adopted augmentation/expansion is also the course for the typical O(n⁴) time‐complexity of the proposed algorithms. This paper presents an innovative approach called allying to effectively circumvent the otherwise necessary augmentation step and to retain the time complexity of the implementation algorithm within the optimal, i.e. O(n²). Meanwhile, the graph simulation concept is adapted and generalized to a three‐tier definition scheme so that broader ICs are incorporated.

The innovative allying minimization approach is identified and an effective implementation algorithm named AlliedMinimize is developed. This algorithm is both runtime optimal – taking O(n²) time – and most powerful in terms of the broadness of constraints it can exploit for XML query pattern minimization. Experimental study confirms the validity of the proposed approach and algorithm.

Though the algorithm AlliedMinimize is so far the most powerful XML query pattern minimization algorithm, it does not incorporate all potential ICs existing in the context of XML. Effectively integrating this innovative minimization scheme into a fully‐fledged XML query optimizer remains to be investigated in the future.

In practice, Allying and AlliedMinimize can be used to achieve a kind of quick optimization for XML queries via fast minimization of the tree patterns involved in XML queries under broad ICs.

This paper presents a novel scheme and an efficient algorithm for XML query pattern minimization under broad ICs.

Compared to the traditional wireless network, the multi‐hop ad hoc wireless network is self‐configurable, dynamic, and distributed. During the past few years, many routing protocols have been proposed for this particular network environment. While in wired and optical networks, multi‐protocol label switching (MPLS) has clearly shown its advantages in routing and switching such as flexibility, high efficiency, scalability, and low cost. However MPLS is complex and does not consider the mobility issue for wireless networks, especially for ad hoc wireless networks. This paper migrates the label concept into the ad hoc network and provides a framework for the efficient label routing protocol(LRP) in such a network. The MAC layer is also optimized with LRP for shorter delay, power saving, and higher efficiency. The simulation results show that the delay is improved significantly with this cross‐layer routing protocol.

Purpose – The study sets out to explore the use of an iterative approach for designing distribution chain in an agile virtual environment; in an agile virtual environment, quick adaptation to changing market situation and automation of supply chain management processes are essential. Design/methodology/approach – The iterative approach consists of two parts: the strategic model and the tactical model. First, the strategic model (including number of distributors, location of distributors) is determined. Then, based on the output of the strategic model, the tactical model (i.e. the inventory planning at each node, and vehicle routeing between different nodes of the chain) is determined. After determining the tactical model, the operation‐related parameters from the tactical model are input into the strategic model again, and the configuration of distribution chain is re‐optimized. Such iterations proceed until the design result converges. Findings – The proposed iterative design process provides many advantages such as reuse of knowledge, adaptive to changing market conditions, modular design, and optimal results guaranteed by mixed mathematical usage. The proposed approach is also realizable as a supply chain management software tool. Originality/value – An important contribution of this study is the iterative process that uses three different types of mathematics. For determination of the strategic model mixed integer programming is used. Determination of the tactical model is effected using genetic algorithm and probability theory.