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In the present work, we focus on developing an in-house parallel meshless local Petrov-Galerkin (MLPG) code for the analysis of heat conduction in two-dimensional and three-dimensional regular as well as complex geometries.

The parallel MLPG code has been implemented using open multi-processing (OpenMP) application programming interface (API) on the shared memory multicore CPU architecture. Numerical simulations have been performed to find the critical regions of the serial code, and an OpenMP-based parallel MLPG code is developed, considering the critical regions of the sequential code.

Based on performance parameters such as speed-up and parallel efficiency, the credibility of the parallelization procedure has been established. Maximum speed-up and parallel efficiency are 10.94 and 0.92 for regular three-dimensional geometry (343,000 nodes). Results demonstrate the suitability of parallelization for larger nodes as parallel efficiency and speed-up are more for the larger nodes.

Few attempts have been made in parallel implementation of the MLPG method for solving large-scale industrial problems. Although the literature suggests that message-passing interface (MPI) based parallel MLPG codes have been developed, the OpenMP model has rarely been touched. This work is an attempt at the development of OpenMP-based parallel MLPG code for the very first time.

Recent wireless communication and electronics technology has enabled the development of low‐cost, low‐power, and multi‐functional sensor nodes. However, the fact that sensor nodes are severely energy‐constrained has been an issue and many energy‐efficient routing protocols have been proposed to resolve it. Cluster‐based routing protocol is one of them. To achieve longer lifetime, some cluster‐based routing protocols use information on GPS‐based location of each sensor node. However, because of high cost, not all sensor nodes can be GPS‐enabled. The purpose of this paper is to propose a simple dynamic clustering approach to achieve energy efficiency for wireless sensor networks (WSN).

Instead of using location information of each sensor node, this approach utilizes information of remaining energy of each sensor node and changes in the number of cluster head nodes dependent on the number of sensor nodes alive. Performance results are presented and compared with some related protocols.

The simulations described in the paper show that both residual energy of each sensor node and changing cluster head nodes depending on the number of sensor nodes alive are very critical factors to obtain performance enhancement in terms of lifetime and data transmission. Especially, in some special environment, the proposal has better performance than GPS‐enabled protocol.

The paper is of value in proposing a simple dynamic clustering approach to achieve energy efficiency for WSN.

This research can contribute to design and develop wireless sensor network (WSN) routing algorithm based on the comparison data. The paper aims to discuss these issues.

This research is a tree-based routing algorithm in order to reduce routing cost on WSNs.

The approach is more efficient than other cluster-based approach.

Originality is high because there is no other paper about cost effect and energy saving both considering at the same time.

The centralized processes of today’s power trading systems are complex and pose a risk of price tampering and hacking. The decentralized and unmodifiable nature of the blockchain technology that has recently been highlighted offers the potential to improve this power trading process. The purpose of this study is to implement a system to apply the blockchain technology to the problem of power trading.

The authors modeled the power trading problem as the interaction between admin, producer and consumer nodes. And a power trading scenario has been created for this model using a blockchain platform called Multichain which is both fast and highly scalable. To verify this scenario, they implemented a trading system using Savoir, a Python-based JsonRPC module.

Experimental results show that all processes, such as blockchain creation, node connectivity, asset issuance and exchange transactions have been correctly handled according to the scenario.

In this study, the authors have proposed and implemented a power trading method that determines price according to the pure market principle and cannot be manipulated or hacked. It is based on the nature of blockchain technology that is decentralized and cannot be tampered.

Application environments of wireless sensor networks (WSNs) include heterogeneous nodes with different packet sizes, transmission abilities and tolerable delay times. This study aims to design a reasonable network topology and transmission timing for these heterogeneous nodes to improve the quality of service (QoS) of networks.

In this paper, the authors treat node urgency and data packets as the basis of network clustering and to extend the network lifetime. The flow, energy consumption and residual energy of a node are included in the cluster head election. We also propose a delay evaluation function.

All the nodes in the network are guaranteed to transmit to the sink nodes efficiently by planning the transmission order in each cluster.

The simulation results show that the proposed method can balance node urgency and data packets path planning, which not only extends the lifetime of the network but also decreases network delay and improves the overall efficiency.

For the solution of equations with sparse matrices, the problem of bandwidth reduction is an important issue. Though graph theoretical algorithms are available, the purpose of this paper is to examine the feasibility of ant systems (AS).

For band optimization an ant colony algorithm based on AS is utilized. In this algorithm a local search procedure is also included to improve the solution.

AS algorithms are found to be suitable for bandwidth optimization.

Application of AS to the bandwidth reduction is the main purpose of this paper, which is successfully performed. The results are compared to those of a graph theoretical bandwidth optimization algorithm.

This paper proposes to identify a new model of the fixed voltage nodes (PV nodes) for medium voltage distribution systems analysis. The model is used within backward/forward (b/f) analysis method applied to solve radial and weakly meshed systems.

The model is based on the compensation currents method for multi‐port systems which has been extensively used, within b/f analysis methods, to take into account the presence of meshes and PV nodes.

Test results prove the approach to be more efficient and precise than previous methodologies and put into evidence the good performance of the proposed model in terms of speed and convergence properties.

The model is developed to be used within b/f methodology.

Utilities are quite interested in such items, since the deregulation electricity market in last years has determined an evolution of the medium voltage distribution networks, due to the presence of distributed generation. So it is necessary to take into account and to model in an opportune way the nodes with distributed generators (PV nodes), also in weakly meshed networks, for the load flow analysis.

The paper presents a new model to treat the fixed voltage nodes (PV nodes) for medium voltage distribution networks analysis.

The accuracy of sensor location estimation influences directly the quality and reliability of services provided by a wireless sensor network (WSN). However, current localization methods may require additional hardware, like global positioning system (GPS), or suffer from inaccuracy like detecting radio signals. It is not proper to add extra hardware in tiny sensors, so the aim is to improve the accuracy of localization algorithms.

The original signal propagation‐based localization algorithm adopts a static attenuation factor model and cannot adjust its modeling parameters in accordance with the local environment. In this paper an adaptive localization algorithm for WSNs that can dynamically adjust ranging function to calculate the distance between two sensors is presented. By adjusting the ranging function dynamically, the location of a sensor node can be estimated more accurately.

The NCTUNs simulator is used to verify the accuracy and analyze the performance of the algorithm. Simulation results show that the algorithm can indeed achieve more accurate localization using just a small number of reference nodes in a WSN.

There is a need to have accurate location information of reference nodes.

This is an effective low‐cost solution for the localization of sensor nodes.

An adaptive localization algorithm that can dynamically adjust ranging function to calculate the distance between two sensors for sensor network deployment and providing location services is described.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.