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Calcium oxalate (CaOx) crystallization is a common phenomenon that contributes to various kidney disorders and stone formation, as well as the formation of scale in industrial processes. The inhibition of CaOx is an area of intense scientific interest in the field of materials science due to its relevance to biomineralization. The present study investigated the effects of pectin (PE) and sodium alginate (SA), two natural polymers, on the growth of CaOx crystals using a batch crystallization method in aqueous solutions at 37 °C with different concentrations (0.5, 1, 5, and 10 ppm). The results of the study showed that both PE and SA were effective inhibitors of CaOx crystal growth, with the highest inhibition observed at a concentration of 10 ppm, reaching 80 %. PE did not significantly affect the size of the crystals, while SA reduced their size as the concentration increased. These findings contribute to our understanding of the potential of natural polymers as non‐toxic inhibitors of CaOx crystal growth. [ABSTRACT FROM AUTHOR]

In recent years, educational institutions have worked hard to automate their work using more trending technologies that prove the success in supporting decision-making processes. Most of the decisions in educational institutions rely on rating the academic research profiles of their staff. An enormous amount of scholarly data is produced continuously by online libraries that contain data about publications, citations, and research activities. This kind of data can change the accuracy of the academic decisions, if linked with the local data of universities. The linked data technique in this study is applied to generate a link between university semantic data and a scientific knowledge graph, to enrich the local data and improve academic decisions. As a proof of concept, a case study was conducted to allocate the best academic staff to teach a course regarding their profile, including research records. Further, the resulting data are available to be reused in the future for different purposes in the academic domain. Finally, we compared the results of this link with previous work, as evidence of the accuracy of leveraging this technology to improve decisions within universities. [ABSTRACT FROM AUTHOR]

OpenFlow is considered as the most known protocol for Software Defined Networking (SDN). The main drawback of OpenFlow is the lack of support of new header definitions, which is required by network operators to apply new packet encapsulations. While SDN's logically centralized control plane could enhance network security by providing global visibility of the network state, it still has many side effects. The intelligent controllers that orchestrate the dumb switches are overloaded and become prone to failure. Delegating some level of control logic to the edge or, to be precise, the switches can offload the controllers from local state based decisions that do not require global network wide knowledge. Thus, this paper, to the best of our knowledge, is the first to propose the delegation of typical security functions from specialized middleboxes to the data plane. We leverage the opportunities offered by programming protocol-independent packet processors (P4) language to present two authentication techniques to assure that only legitimate nodes are able to access the network. The first technique is the port knocking and the second technique is the One-Time Password. Our experimental results indicate that our proposed techniques improve the network overall availability by offloading the controller as well as reducing the traffic in the network without noticeable negative impact on switches' performance. [ABSTRACT FROM AUTHOR]

Wireless Body Area Network (WBAN) has been a key element in e-health to monitor bodies. This technology enables new applications under the umbrella of different domains, including the medical field, the entertainment and ambient intelligence areas. This survey paper places substantial emphasis on the concept and key features of theWBAN technology. First, the WBAN concept is introduced and a review of key applications facilitated by this networking technology is provided. The study then explores a wide variety of communication standards and methods deployed in this technology. Due to the sensitivity and criticality of the data carried and handled by WBAN, fault tolerance is a critical issue and widely discussed in this paper. Hence, this survey investigates thoroughly the reliability and fault tolerance paradigms suggested for WBANs. Open research and challenging issues pertaining to fault tolerance, coexistence and interference management and power consumption are also discussed along with some suggested trends in these aspects. [ABSTRACT FROM AUTHOR]

Current networking technologies are not perfectly equipped to support Quality of Service (QoS), which is vital for real-time multimedia applications in Wireless Community Mesh Networks (WCNs). Therefore, there is a need to devise innovative routing algorithms to support QoS on top of existing standards. Thus, this paper presents a cross layer relay node selection model for routing protocols in order to offer optimal routes to real-time applications. To the best of our knowledge, our two proposed routing metrics, Packet Priority-Oriented routing metric (PPO) and Packet Priority-oriented QoS routing metric (PP-QoS) , are the first to provide differentiated priorities and service levels to applications with different needs. PPO considers the application priority. Moreover, PP-QoS also considers the channel busy level to improve the performance of path selection. The simulation confirms the superiority of the proposed model against a number of existing counterparts. [ABSTRACT FROM AUTHOR]

Wireless community networks (WCNs) have emerged as a cost-effective ubiquitous broadband connectivity solution, offering a wide range of services in a given geographical area. QoS-aware multicast over WCNs is among the most challenging issues and has attracted a lot of attention in recent times. The existing multicast schemes in WCNs suffer in terms of several key performance metrics, such as, latency, jitter and throughput, particularly in large-scale networks. Consequently, these schemes cannot accommodate the desired performance levels, especially when dealing with high-bandwidth applications that require efficient gateway-based management. To fill in this gap, a new strategy for supporting QoS-aware multicast in large-scale WCNs is proposed in this paper. Specifically, a new Gateway based Multi-hop Routing algorithm (GMR) is firstly proposed to enhance the routing management capability of the network. Built upon GMR, a new Multicast Gateway Multi-hop Routing algorithm (MGMR) is devised to cope with high-bandwidth applications in WCNs. The MGMR is the first of its kind that considers both the capability of gateway-based management and the requirements of high-bandwidth applications. Extensive simulation experiments and performance results demonstrate the superiority of both GMR and MGMR when compared to other methods under various operating conditions. [ABSTRACT FROM PUBLISHER]

Most existing route discovery schemes in MANETs are based on probabilistic models by which MANETs usually deploy broadcast mechanisms to discover routes between nodes. This is implemented by flooding the network with routing requests (RREQ) packets which usually result in the well-known broadcast storm problem. Due to the high mobility, frequent breakages are more likely to occur, leading to re-discovering the same routes frequently uncontrolled RREQ packets. Thus, the network may incur more channel contention and high packets collision rate. Existing solutions cannot accommodate the desired performance levels, especially in high mobility. Thus, this paper is the first that considers the velocity vector probabilistic route discovery in MANETs. Two new velocity-aware probabilistic route discovery models are presented to exclude unstable nodes while constructing routes between the source and its destination. The simulation experiments confirm the superiority of the proposed schemes in terms of RREQ packet overhead and link stability. [ABSTRACT FROM AUTHOR]

Abstract: The Wireless Mesh Network (WMN) is a highly capable technology that can offer low-cost and easy-deployable network connectivity to both small-size community networks and large-scale metropolitan networks. As a key emerging technology to provide the next generation broadband networking, WMN combines the advantages of both mobile ad hoc network (MANET) and traditional fixed network, attracting significant industrial and academic attentions. In WMN, the load balancing has already shown its key role in enhancing communication quality by providing reduced latency, jitter and error rate as well as improving bandwidth utilisation and allocation polices. Although there are a number of proposals on using load-aware strategy in WMN, the neighbourhood load has not been considered within the context of load balancing and high efficient WMNs. In this paper, we propose a Neighbourhood Load Routing metric to further improve the performance of existing routing protocols such as AODV in WMN. We have conducted extensive simulation experiments and our results confirm the superiority of our proposed scheme over its well-known counterparts, especially in grid topologies. [Copyright &y& Elsevier]

The increasing number of collective communication-based services with a mass interest and the parallel increasing demand for service quality are paving the way toward end-to-end QoS guarantees. Although many multicast algorithms in interconnection networks have been widely reported in the literature, most of them handle the multicast communication within limited performance metrics, i.e., either delay/latency or throughput. In contrast, this study investigates the multicast communication within a group of QoS constrains, namely latency, jitter, throughput, and additional traffic caused. In this paper, we present the Qualified Groups (QGs) as a novel path-based multicast algorithm for interconnection networks. To the best of our knowledge, the QG is the first multicast algorithm that considers the multicast latency at both the network and node levels across different-traffic scenarios in interconnection networks. Our analysis shows that the proposed multicast algorithm exhibits superior performance characteristics over other well-known path-based multicast algorithms under different operating conditions. In addition, our results show that the QG can significantly improve the parallelism of the multicast communication. [ABSTRACT FROM AUTHOR]

The article presents an introduction to articles published in this issue including an article on the average-case performance of eight offline heuristic algorithm, another on the performance of six scientific application codes on four high-speed machines and an article on the performance of collective communications.

Different studies have recently emphasized the importance of deploying clustering schemes in Vehicular ad hoc Network (VANET) to overcome challenging problems related to scalability, frequent topology changes, scarcity of spectrum resources, maintaining clusters stability, and rational spectrum management. However, most of these studies addressed the clustering problem using conventional performance metrics while spectrum shortage, and the combination of spectrum trading and VANET architecture have not been tackled so far. Thus, this paper presents a new fuzzy logic based clustering control scheme to support scalability, enhance the stability of the network topology, motivate spectrum owners to share spectrum and provide efficient and cost-effective use of spectrum. Unlike existing studies, our context-aware scheme is based on multi-criteria decision making where fuzzy logic is adopted to rank the multi-attribute candidate nodes for optimizing the selection of cluster heads (CH)s. Criteria related to each candidate node include: received signal strength, speed of vehicle, vehicle location, spectrum price, reachability, and stability of node. Our model performs efficiently, exhibits faster recovery in response to topology changes and enhances the network efficiency life time. [ABSTRACT FROM AUTHOR]

For the last twenty years, artificial intelligence (AI) has become a significant technology to influence our daily life with its ability of promoting the quality of living. Hence, they propose a repost network embedding-based diffusion popularity prediction algorithm for achieving the precise prediction. In addition, the paper entitled "LSTM based link quality confidence interval boundary prediction for wireless communication in smart grid" provided by sun et al., studies the link quality prediction of the wireless communication in smart grid. [Extracted from the article]

In the current cloud business environment, the cloud provider (CP) can provide a means for offering the required quality of service (QoS) for multiple classes of clients. We consider the cloud market where various resources such as CPUs, memory, and storage in the form of Virtual Machine (VM) instances can be provisioned and then leased to clients with QoS guarantees. Unlike existing works, we propose a novel Service Level Agreement (SLA) framework for cloud computing, in which a price control parameter is used to meet QoS demands for all classes in the market. The framework uses reinforcement learning (RL) to derive a VM hiring policy that can adapt to changes in the system to guarantee the QoS for all client classes. These changes include: service cost, system capacity, and the demand for service. In exhibiting solutions, when the CP leases more VMs to a class of clients, the QoS is degraded for other classes due to an inadequate number of VMs. However, our approach integrates computing resources adaptation with service admission control based on the RL model. To the best of our knowledge, this study is the first attempt that facilitates this integration to enhance the CP's profit and avoid SLA violation. Numerical analysis stresses the ability of our approach to avoid SLA violation while maximizing the CP's profit under varying cloud environment conditions. [ABSTRACT FROM PUBLISHER]

With the resource-constrained nature of mobile devices and the resource-abundant offerings of the cloud, several promising optimisation techniques have been proposed by the green computing research community. Prominent techniques and unique methods have been developed to offload resource intensive tasks from mobile devices to the cloud. Although these schemes address similar questions within the same domain of mobile cloud application (MCA) optimisation, evaluation is tailored to the scheme and also solely mobile focused, thus making it difficult to clearly compare with other existing counterparts. In this work, we first analyse the existing/commonly adopted evaluation technique, then with the aim to fill the above gap, we propose the behaviour-driven full-tier green evaluation approach, which adopts the behaviour-driven concept for evaluating MCA performance and energy usage-ie, green metrics. To automate the evaluation process, we also present and evaluate the effectiveness of a resultant application program interface and tool driven by the behaviour-driven full-tier green evaluation approach. The application program interface is based on Android and has been validated with Elastic Compute Cloud instance. Experiments show that Beftigre is capable of providing a more distinctive, comparable, and reliable green test results for MCAs. [ABSTRACT FROM AUTHOR]

Abstract: Broadcasting is an essential operation in Mobile Ad hoc Networks (MANETs) to transmit a message (data packet) from the sender to the rest of the network nodes. Although flooding is the simplest mechanism for broadcasting, where each node retransmits every uniquely received message exactly once, it is usually costly and results in serious redundancy, contention and collisions in the network. These problems are widely referred to as the broadcast storm problem. In the light of this, this study introduces a new counter-based broadcasting scheme to achieve efficient broadcasting in MANETs. This is achieved by using a counter-based scheme with a dynamic threshold to increase the successful delivery rate of packets and enhance the throughput of the network. Extensive simulation experiments have been conducted. Our results show that the new scheme outperforms the well known exiting schemes, namely the two counter-based broadcasting scheme and blind flooding. [ABSTRACT FROM AUTHOR]

Broadcast is a fundamental operation used in Mobile Ad hoc NETworks (MANETs) for many services, such as route discovery and sending information messages. The direct method to perform broadcast is a simple flooding, which can decrease the performance of MANET. Recently, a probabilistic approach to flooding has been proposed as one of most important suggested solutions to solve the broadcast storm problem, which leads to the collision, contention and duplicated messages. This paper presents the Smart Probabilistic Broadcasting (SPB) as a new probabilistic method to improve the performance of existing on-demand routing protocols by reducing the RREQ overhead during the rout discovery operation. The simulation results show that the combination of AODV and a suitable probabilistic rout discovery can reduce the average end-to-end delay as well as overhead, while achieving low normalized routing load, compared to AODV that uses fixed probability and blind flooding. Simulation experiments have been conducted to examine our proposed scheme. The results show that SPB outperforms its counterparts and opens up a promising framework towards optimal probabilistic broadcasting. [ABSTRACT FROM AUTHOR]

Utilising the mobilisation of a sink node in a wireless sensor network to combat the energy hole, or hotspot issue, is well referenced. However, another issue, that of energy spikes may remain. With the mobile sink node potentially communicating with some nodes more than others. In this study we propose the Mobility Aware Duty Cycling and Dynamic Preambling Algorithm (MADCaDPAL). This algorithm utilises an existing solution where a communication threshold is built between a mobile sink node using predictable mobility and static nodes on its path. MADCaDPAL bases decisions relating to node sleep function, moving to clear channel assessment and the subsequent sending of preambles on the relation between the threshold built by the static node and the position of the mobile sink node. MADCaDPAL achieves a reduction in average energy consumption of up to 80%, this when used in conjunction with a lightweight carrier-sense multiple access based MAC implementation. Maximum energy consumption amongst individual nodes is also brought closer to the average, reducing energy spikes and subsequently improving network lifetime. Additionally, frame delivery to the sink is improved overall. [ABSTRACT FROM AUTHOR]

Nature-inspired computing (NIC) has been widely studied for many optimization scenarios. However, miscellaneous solution space of real-world problem causes it is challenging to guarantee the global optimum. Besides, cumbersome structure and complex parameters setting-up make the existed algorithms hard for most users who are not specializing in NIC, to understand and use. To alleviate these limitations, this paper devises a succinct and efficient optimization algorithm called Nomad Algorithm (NA). It is inspired by the migratory behavior of nomadic tribes on the prairie. Extensive experiments are implemented with respects to accuracy, rate, stability, and cost of optimization. Mathematical proof is given to guarantee the global convergence, and the nonparametric tests are conducted to confirm the significance of experiment results. The statistical results of optimization accuracy denote NA outperforms its rivals for most cases (23/28) by orders of magnitude significantly. It is considered as a promising optimizer with excellent efficiency and adaptability. [ABSTRACT FROM AUTHOR]

A new analytical model is proposed to investigate the delay and throughput in cognitive mesh networks. The validity of the model is demonstrated via extensive simulation experiments. The model is then used to evaluate the effects of the number of licensed channels and channel utilisation on the network performance. [ABSTRACT FROM PUBLISHER]

The increasing demand for the coverage of high-speed wireless local area networks (WLANs) is driving the installation of a very large number of access points (APs). Wireless mesh networks (WMNs) have emerged as a promising technology in the next generation networks to provide economical and scalable broadband access to wireless interconnection of multiple APs that manage individual WLANs in order to extend the coverage of the conventional single WLANs. In this paper, we develop a new analytical model to investigate the quality-of-service (QoS) performance metrics in WMNs interconnecting multiple WLANs. The model takes the phenomenon of communication locality into consideration. Extensive simulation experiments are conducted to validate the accuracy of the analytical model. The proposed model is then used to obtain the maximum achievable throughput, which is a key performance metrics in wireless networks. Moreover, we utilize the model to evaluate the impact of communication locality on network performance and investigate its effects on the optimization of integrated WLANs and multi-hop mesh networks. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

• Stratified sampling reduces genotype diversify thus reducing exploration time. • Opposition-Based guessing increases initial population fitness. • Path Length diversity is more important during the initialization phase. • The repair function can introduce diversity to population. Initialization is the first and a major step in the implementation of evolutionary algorithms (EAs). Although there are many common general methods to initialize EAs such as the pseudo-random number generator (PRNG), there is no single method that can fit every problem. This study provides a new, flexible, diversity-aware, and easy-to-implement initialization method for a genetic algorithm for the shortest path problem. The proposed algorithm, called stratified opposition-based sampling (SOBS), considers phenotype and genotype diversity while striving to achieve the best fitness for the initialization population. SOBS does not depend on a specific type of sampling, because the main goal is to stratify the sampling space. SOBS aims at an initial population with higher fitness and diversity in the phenotype and genotype. To investigate the performance of SOBS, four network models were used to simulate real-world networks. Compared with the most frequently used initialization method, that is, PRNG, SOBS provides more accurate solutions, better running time with less memory usage, and an initial population with higher fitness. Statistical analysis showed that SOBS yields solutions with higher accuracy in 68–100% of the time. Although this study was focused on the genetic algorithm, it can be applied to other population-based EAs that solve the shortest path problem and use the same direct population representation such as particle swarm optimization (PSO). [ABSTRACT FROM AUTHOR]

Due to limited processing capabilities and other constraints of most wireless networks, many existing security algorithms do not consider the network efficiency. This is because most of these security solutions exhibit intolerable overhead and consider only securing scalar data, which are not suitable for other data types such as digital images, hence affecting the provided security level and network performance. Thus, in this paper, we propose a lightweight and efficient security scheme based on chaotic algorithms to efficiently encrypt digital images. Our proposed algorithm handles digital images in two phases: Firstly, digital images are split into blocks and compressed by processing them in frequency domain instead of Red-Green-Blue (RGB) domain. The ultimate goal is to reduce their sizes to speed up the encryption process and to break the correlation among image pixel values. Secondly, 2D Logistic chaotic map is deployed in key generation, permutation, and substitution stages for image pixel shuffling and transposition. In addition, 2D Henon chaotic map is deployed to change the pixel values in the diffusion stage in order to enhance the required level of security and resist various security attacks. Security performance analysis based on standard test images shows that our proposed scheme overcomes the performance of other existing techniques. [ABSTRACT FROM AUTHOR]

The hotspot issue in wireless sensor networks, with nodes nearest the sink node losing energy fastest and degrading network lifetime, is a well-referenced problem. Mobile sink nodes have been proposed as a solution to this. They do not completely remove the hotspot problem though, with nodes the sink passes most closely still expending more energy than others. This study proposes a lightweight algorithm, located in the media access control (MAC) layer of static nodes and utilising knowledge of predictable sink node mobility. This is in order to create a dynamic communication threshold between static nodes and the sink, within which static nodes awaken, lessening competition for sink communication between nodes. In utilising predictable mobility and factors already known to the static node, such as location and interference range, there is no need for energy-consuming messaging. Analysis and simulation results, tested on a lightweight implementation of a carrier-sense multiple-access-based MAC protocol, show a significant improvement in energy consumption in both controlled and random environments, with frame delivery improved to the point where sink speed is negated. This is when compared to the existing duty cycling approach. [ABSTRACT FROM AUTHOR]