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Processing huge and complex data to obtain useful information is challenging, even though several big data processing frameworks have been proposed and further enhanced. One of the prominent big data processing frameworks is MapReduce. The main concept of MapReduce framework relies on distributed and parallel processing. However, MapReduce framework is facing serious performance degradations due to the slow execution of certain tasks type called stragglers. Failing to handle stragglers causes delay and affects the overall job execution time. Meanwhile, several straggler reduction techniques have been proposed to improve the MapReduce performance. This study provides a comprehensive and qualitative review of the different existing straggler mitigation solutions. In addition, a taxonomy of the available straggler mitigation solutions is presented. Critical research issues and future research directions are identified and discussed to guide researchers and scholars

Vehicular Ad hoc Networks (VANETs) have drawn incredible interest in both academic and industrial sectors due to their potential applications and services. Vehicles’ position plays a significant role in many location-based applications and services such as public emergency, vehicles tracking, resource discovery, traffic monitoring and position-based routing. A location service is used to keep up-to-date records of current positions of vehicles. However, locating vehicles’ positions and maintaining an accurate view of the entire network are quite challenging tasks due to the high number of nodes, and high and fast nodes mobility which results in rapid topological changes and sudden network disconnections. In the past literature, various location-based services have been proposed to solve the above mentioned issues. Moreover, the cluster-based location service schemes have gained a growing interest due to their advantages over non-cluster-based schemes. The cluster-based schemes improve the network scalability, reduce the communications overhead and resolve the mobility issues within the clusters preventing them from propagating in the whole network. Therefore, this paper presents the taxonomy of the existing location service schemes, inspects the cluster-based location service by highlighting their strengths and limitations, and provides a comparison between location-based clustering and application specific clustering such as the one used in routing, information dissemination, channel access management and security. In addition, the existing clustering schemes, challenges and future directions for efficient cluster-based location service are also discussed.

Blockchain provides a distributed digital ledger platform for not only cryptocurrencies but also many other distributed applications. Blockchain platforms work flow and performance are controlled by the used consensus algorithms. Although many studies evaluated cryptocurrency from the Shariah perspective, they focused only on the cryptocurrency concept and did not consider the underlying blockchain technology. However, designing a Shariah compliant application on top of a non Shariah compliant platform does not fulfil the requirements of Shariah. Therefore, it is necessary to use a Shariah compliant blockchain platform in order to produce Shariah compliant blockchain applications. To support the production of Shariah compliant blockchain applications, this study provides a comparative analysis of the most used consensus algorithms in blockchain platforms. In particular, the considered consensus algorithms are evaluated from a Shariah perspective. In conclusion, based on the conducted evaluation some of the widely used blockchain platforms (e.g. Bitcoin and Ethereum) are found to be not compliant with the Shariah rules due to using a consensus algorithm that is not Shariah compliant.

Cryptocurrency has emerged as the most promising digital asset, which serves as a medium of exchange with distributed control and highly secured financial system. This lead to an increase in stakeholders’ interest in digital currency investment. The cryptocurrencies majorly involve two phases including Initial Coin Offering (ICO) and blockchain creation. These phases have been challenged with criticisms in terms of the Islamic shariah injunctions. These criticisms are based on two fundamental issues including whether cryptocurrency is backed by asset and has a regulatory authority or not. These issues are related to uncertainty, volatility and high speculation of the cryptocurrencies. Although, several cryptocurrencies claimed to have considered the shariah requirements in their proposed cryptocurrency ecosystems. However, a strict analysis of some of the existing cryptocurrencies reveals otherwise. Therefore, this paper presents a review of some shariah-compliant cryptocurrencies focusing on their volatility and speculation. The operations of cryptocurrencies need to follow the Islamic shariah requirements. The proposed review provides an insight regarding the acclaimed shariah-compliant cryptocurrencies to assess whether they comply with the shariah requirements or not.

Due to the unprecedented advances in satellite fabrication and deployment, innovative communications and networking technologies, ambitious space projects and programs, and the resurgence of interest in satellite networks, there is a need to redefine space networks (SpaceNets) to incorporate all of these evolutions. This paper introduces a vision for future SpaceNets that considers advances in several related domains. First, we present a reference architecture that captures the various network entities and terminals in a holistic manner. Based on this, space, air, and ground use cases are studied. Then, the architectures and technologies that enable the envisaged SpaceNets are investigated. In so doing, we highlight the activities and projects of different standardization bodies, satellite operators, and national organizations towards the envisioned SpaceNets. Finally, the challenges, potential solutions, and open issues from communications and networking perspectives are discussed., Comment: Accepted for publication as an Invited Paper in IEEE Transactions on Communications

Low Earth Orbit (LEO) Satellite Network (SatNet) with their mega-constellations are expected to play a key role in providing ubiquitous Internet and communications services in the future. LEO SatNets will provide wide-area coverage and support service availability, continuity, and scalability. To support the integration of SatNets and terrestrial Fifth Generation (5G)networks and beyond, the satellite communication industry has become increasingly involved with the 3rd Generation Partnership Project (3GPP) standardization activities for 5G. In this work, we review the 3GPP standardization activities for the integration of SatNets in 5G and beyond. The 3GPP use cases of SatNets are highlighted and potential requirements to realize them are summarized as well. The impacted areas of New Radio(NR) are discussed with some potential solutions. The foreseen requirements for the management and orchestration of SatNets within 5G are described. Future standardization directions are discussed to support the full integration of SatNets in SixthGeneration (6G) with the goal of ubiquitous global connectivity.

In video streaming over vehicular communication, optimal selection of a video packet forwarder is a daunting issue due to the dynamic nature of Vehicular Ad-hoc NETworks (VANETs)and the high data rates of video. In most of the existing studies, extensive considerations of the essential metrics have not been considered. In order to achieve quality video streaming in vehicular network, important metrics for link connectivity and bandwidth efficiency need to be employed to minimize video packet error and losses. In order to address the aforementioned issues, a Road-based Multi-metric Forwarder Evaluation scheme for Multipath Video Streaming (RMF-MVS) has been proposed. The RMF-MVS scheme is adapted to be a Dynamic Self-Weighting score (DSW) (RMF-MVS+DSW) for forwarder vehicle selection. The scheme is based on multipath transmission. The performance of the scheme is evaluated using Peak Signal to Noise Ratio (PSNR), Structural SIMilarity index (SSIM), Packet Loss Ratio (PLR) and End-to-End Delay (E2ED) metrics. The proposed scheme is compared against two baseline schemes including Multipath Solution with Link and Node Disjoint (MSLND) and Multimedia Multi-metric Map-aware Routing Protocol (3MRP) with DSW (3MRP+DSW). The comparative performance assessment results justify the benefit of the proposed scheme based on various video streaming related metrics.

[EN] Todays' Intelligent Transportation System (ITS) applications majorly depend on either limited neighbouring traffic data or crowd sourced stale traffic data. Enabling big traffic data analytics in ITS environments is a step closer towards utilizing significant traffic patterns and trends for making more precise and intelligent decisions particularly in connected autonomous vehicular environments. Towards this end, this paper presents a Traffic Aware Data Offloading (TRADING) approach for big traffic data centric ITS applications in connected autonomous vehicular environments. Specifically, TRADING balances offloading data traffic among gateways focusing on vehicular traffic and network status in the vicinity of gateways. In addition, TRADING mitigates the effect of gateway advertisement overhead to liberate the transmission channels for traffic big data transmission. The performance of TRADING is comparatively evaluated in a realistic simulation environment by considering gateway access overhead, load distribution among gateways, data offloading delay, and data offloading success ratio. The comparative performance evaluation results show some significant developments towards enabling big traffic data centric ITS., This work was financially supported by the Post-doctoral Fellowship Scheme of Universiti Teknologi Malaysia for the project: "Vehicular fog computing resource allocation scheme for real-time big data processing in intelligent transportation systems." The review of this article was coordinated by Prof. J. W. Choi.

Future integrated terrestrial-aerial-satellite networks will have to exhibit some unprecedented characteristics for the provision of both communications and computation services, and security for a tremendous number of devices with very broad and demanding requirements across multiple networks, operators, and ecosystems. Although 3GPP introduced the concept of self-organizing networks (SONs) in 4G and 5G documents to automate network management, even this progressive concept will face several challenges as it may not be sufficiently agile in coping with the immense levels of complexity, heterogeneity, and mobility in the envisioned beyond-5G integrated networks. In the presented vision, we discuss how future integrated networks can be intelligently and autonomously managed to efficiently utilize resources, reduce operational costs, and achieve the targeted Quality of Experience (QoE). We introduce the novel concept of the “self-evolving networks (SENs)” framework, which utilizes artificial intelligence, enabled by machine learning (ML) algorithms, to make future integrated networks fully automated and intelligently evolve with respect to the provision, adaptation, optimization, and management aspects of networking, communications, computation, and infrastructure nodes' mobility. To envisage the concept of SEN in future integrated networks, we use the Intelligent Vertical Heterogeneous Network (I-VHetNet) architecture as our reference. The article discusses five prominent scenarios where SEN plays the main role in providing automated network management. Numerical results provide an insight into how the SEN framework improves the performance of future integrated networks. The article presents the leading enablers and examines the challenges associated with the application of the SEN concept in future integrated networks.

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks)., Comment: To appear in IEEE Communications Surveys & Tutorials

The intelligent transportation system (ITS) concept was introduced to increase road safety, manage traffic efficiently, and preserve our green environment. Nowadays, ITS applications are becoming more data-intensive and their data are described using the “5Vs of Big Data”. Thus, to fully utilize such data, big data analytics need to be applied. The Internet of vehicles (IoV) connects the ITS devices to cloud computing centres, where data processing is performed. However, transferring huge amount of data from geographically distributed devices creates network overhead and bottlenecks, and it consumes the network resources. In addition, following the centralized approach to process the ITS big data results in high latency which cannot be tolerated by the delay-sensitive ITS applications. Fog computing is considered a promising technology for real-time big data analytics. Basically, the fog technology complements the role of cloud computing and distributes the data processing at the edge of the network, which provides faster responses to ITS application queries and saves the network resources. However, implementing fog computing and the lambda architecture for real-time big data processing is challenging in the IoV dynamic environment. In this regard, a novel architecture for real-time ITS big data analytics in the IoV environment is proposed in this paper. The proposed architecture merges three dimensions including intelligent computing (i.e. cloud and fog computing) dimension, real-time big data analytics dimension, and IoV dimension. Moreover, this paper gives a comprehensive description of the IoV environment, the ITS big data characteristics, the lambda architecture for real-time big data analytics, several intelligent computing technologies. More importantly, this paper discusses the opportunities and challenges that face the implementation of fog computing and real-time big data analytics in the IoV environment. Finally, the critical issues and future research directions section discusses some issues that should be considered in order to efficiently implement the proposed architecture.

Nowadays, providing reliable vehicle to vehicle communications in vehicular ad hoc networks is essential to serve the emerging intelligent transportation systems. Traffic aware routing is considered a promising approach for delivering data packets between geographically separated vehicles. However, most of the existing traffic aware routing protocols greedily select the next-hop based on distance. Consequently, high packet loss ratio occurs especially with the vehicles high speed mobility. Some existing forwarding schemes attempted to improve the next-hop selection by considering inter-vehicle communication quality or neighbours predicted positions. Nevertheless, such schemes depend on the neighbours mobility information received through beacons regardless of its freshness. In addition, the differentiation between road and intersection areas while forwarding packets was neglected. Therefore, a reliable traffic aware routing protocol is proposed, which selects the next-hop based on roads structure, neighbours predicted positions and their received signal strength, and the recentness of the mobility information received from neighbours. The simulation results show significant improvements in terms of packet delivery ratio and end-to-end delays.

Information and Communication Technologies consume about 3% of the worldwide energy. Therefore, developing green communication systems is necessary for all sectors of technologies. In addition, as other wireless devices might inter-communicate with Vehicular Ad hoc Networks (VANETs), power constraints for such devices have to be considered. Moreover, with the introduction of full and hybrid electrical vehicles, efficient energy consumption in vehicles communication is becoming necessary. Although geographical routing is a dominant routing approach in VANETs, packets routing through multi-hop communications consumes most of the communication energy of vehicles’ wireless devices. This paper investigates the advances and challenges in green geographical routing protocols for VANETs, whereas existing protocols are classified to beacon based and beaconless. In particular, this review explored the different methods used by the green geographical routing protocols to reduced their energy consumptions. However, a considerable research work is required to improve VANETs green geographical routing and solve the problems highlighted in the “Challenges and critical issues” section.

Usually, Wireless Sensor Network operates in a wide range of untrustworthy environments that are deployed in an ad-hoc approach. Although different cluster-based schemes have been proposed for improving network lifetime, however, most of the existing solutions incur probabilistic methods, which result in non-uniform energy consumption and imbalanced load distribution. In addition, end-to-end route discovery is non-optimized in terms of the limited resources of sensor nodes, which leads to frequent route discoveries and network overheads. In this research paper, we present Weighted Energy-Efficient Clustering with Robust Routing (WECRR) protocol that maintains balanced energy consumption and improves network-wide data delivery performance. The contributions of our proposed WECRR protocol are: Firstly, WECRR initiates a deterministic approach to avoid the uncertainties in Cluster Heads election mechanism and performs bounded clustering mechanism. Secondly, it provides multi-level optimized routing decision by making use of multi-facet attributes. At the end, it provides a route maintenance strategy, upon encounters any faulty or exhausted nodes on primary route, which results in reducing re-transmissions and route breakages. Simulation results reveal improved performance of WECRR protocol than compared to existing work.

Achieving smart and intelligent transportation requires the use of millions of devices which generate a huge volume of data, termed as Big Data. With the flourishing of Big Data analytics, intelligent transportation management and control is now becoming more data driven. Big data can provide ample information obtained from vehicles, traffic infrastructure, smart phones and weather stations. Such data has promising applications in intelligent transportation systems, especially in the road safety sector. In particular, utilizing Big Data analytics assesses accident prevention and detection, thereby reducing causalities, loses and damage. This survey paper explores the role of big data in shaping the intelligent transportation systems with a focus on the road safety sector. In addition, the limitations of existing studies are discussed and future research directions are suggested.

Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and pollute the environment. Emergency messages notify the drivers about road accidents and congestions, and how to avoid the dangerous zones. This paper classifies the emergency messages schemes into three categories based on relay node, clustering and infrastructure. The capabilities and limitations of the emergency messages schemes are investigated in terms of dissemination process, message forward techniques, road awareness and performance metrics. Moreover, it highlights VANET-based challenges and open research problems to provide the solutions for a safer, more efficient and sustainable future ITS.

In recent decades, cluster-based schemes have emerged as viable solutions for energy conservation problem in wireless sensor networks (WSN). However, most of the existing solutions incur imbalanced energy consumption and high network overheads. In addition, existing cluster-based solutions do not optimize route discovery based on the restricted resources of sensor nodes. Moreover, most of the cluster-based solutions perform periodical re-clustering for load balancing, which results in shortening network lifetime. This research paper presents a Dynamic Energy-aware Fault Tolerant Routing (DEFTR) protocol that exploits uniform-sized network partitioning based on network size and utilizes a multi-facet routing mechanism, which takes into consideration the residual energy, and position and link quality of neighbors. Furthermore, DEFTR not only offers reliable and energy efficient data routing but also supports fault tolerance. Simulation results demonstrate that DEFTR improved the network lifetime by 20.9% and throughput by 35%, also it reduced the delay by 29% and transmission cost by 46% in comparison to the existing work.

One of the important characteristics of VANETs is the multi-hop communications, which provides Vehicle-to-Vehicle(V2V) communication for many applications. In order to adapt to mobility in high speeds and limited-time communication links, traffic aware routing was proposed in many research works. As a type of position based routing protocols, traffic aware routing utilizes vehicles' positions and traffic status as two main routing parameters. However, providing real-time measurements for traffic status on each road generates high network overhead. In addition, to make such measurement always updated and available for routing purposes, the measurement process has to be applied frequently. This paper introduces a Lightweight Intersection-based Traffic Aware Routing (LITAR) protocol for V2V communication in urban vehicular networks. LITAR introduces two new algorithms to reduce the network overhead generated by the traffic status measurement process while preserving the accuracy of measurement. Moreover, LITAR make routing decisions based on vehicular directional density, Road Network Connectivity (RNC) and distance towards destination. The evaluation of the proposed LITAR protocol shows significant performance improvements in terms of packet delivery ratio, while reducing communication overhead as compared to existing routing approaches.

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

Data prioritization of heterogeneous data in wireless sensor networks gives meaning to mission-critical data that are time-sensitive as this may be a matter of life and death. However, the standard IEEE 802.15.4 does not consider the prioritization of data. Prioritization schemes proffered in the literature have not adequately addressed this issue as proposed schemes either uses a single or complex backoff algorithm to estimate backoff time-slots for prioritized data. Subsequently, the carrier sense multiple access with collision avoidance scheme exhibits an exponentially increasing range of backoff times. These approaches are not only inefficient but result in high latency and increased power consumption. In this article, the concept of class of service (CS) was adopted to prioritize heterogeneous data (real-time and non-real-time), resulting in an optimized prioritized backoff MAC scheme called Class of Service Traffic Priority-based Medium Access Control (CSTP-MAC). This scheme classifies data into high priority data (HPD) and low priority data (LPD) by computing backoff times with expressions peculiar to the data priority class. The improved scheme grants nodes the opportunity to access the shared medium in a timely and power-efficient manner. Benchmarked against contemporary schemes, CSTP-MAC attained a 99% packet delivery ratio with improved power saving capability, which translates to a longer operational lifetime.

Vehicular ad hoc networks (VANETs) are gaining tremendous interest among researchers and industries. Although the main reason for developing VANETs is traffic safety, many applications such as traffic status monitoring, road traffic management, routing and distribution of data, have emerged. VANETs exploit multi-hop communications among vehicles to deliver data packets. However, with fast mobility and intermittent link connectivity between vehicles, efficient and reliable routing in VANETs is becoming a challenging task. In order to make routing protocols robust to frequent communication disruptions and aware of unstable traffic and network conditions, several new routing metrics have been integrated with routing protocols. Such protocols are called traffic aware routing (TAR) protocols as their routing decisions are influenced by traffic and network status. The goal of this paper is to review the most recent traffic aware routing protocols while emphasising on traffic and network conditions awareness issues. In addition, this review investigated TAR protocols capabilities and limitations in terms of routing process, routing metrics measurement, forwarding mechanisms and recovery techniques. Moreover, challenges, critical issues and open research problems were discussed in the "Challenges and issues to consider" sections.

Nowadays, vehicular Ad hoc Networks (VANETs) are gaining enormous research interest. Even though the leading reason for developing VANETs is traffic safety, many applications such as traffic status monitoring, road traffic management, routing and distribution of data, have been considered. Road traffic density estimation provides important information for such applications. Various infrastructure-based mechanisms were proposed to estimate traffic density relying on vehicle detection devices that require pre-deployment. However, as utilizing wireless communication capabilities in vehicles is developing rapidly, more accurate and real-time infrastructure-free density estimation methods are emerging day-to-day. Some of the infrastructure-free methods depend mainly on statistical estimations, while others are based on VANET communications and traffic flow information. In addition, clustering and group members counting are the main characteristic of a third type of infrastructure-free methods. This review paper explored different techniques and algorithms used in both infrastructure-based and infrastructure-free density estimation methods. Furthermore, the main features, limitations and critical issues for each density estimation method are depicted.

Wireless sensor network (WSN) consists of several tiny devices that are dispersed randomly for gathering network field. Clustering mechanism divides the WSN into different sub-regions called clusters. Individual cluster is consisting of cluster head (CH) and member nodes. The main research challenges behind clustering mechanism are to optimize network overheads with efficient data delivery. Sensor nodes are operated by batteries and practically it is not feasible to replace them during sensing the environment so energy should be effectively utilized among sensors for improving overall network performance. This research paper presents an improved energy aware cluster based data routing (i-ECBR) scheme, by dividing the network regions into uniform sized square partitions and localized CH election mechanism. In addition, consistent end-to-end data routing is performed for improving data dissemination. Simulation results illustrate that our proposed scheme outperforms than existing work in terms of different performance metrics.