Abstract Mixing the wireless medium with fiber optics can form a new communication system called a radio‐over‐fiber (RoF) network; it is a promising solution that can provide high bandwidth and a reliable connection between numerous sensors in wireless sensor networks (WSN) and the central office (base station) within a particular area. This paper first design and discusses new paradigms of fire detection in the IoT environment using RoF technology. Second, this paper covers the distribution of remote antenna unit (DRAU) architecture within RoF‐IoT. Finally, best remote antennas unit selection (BRAUS) of distributed RAUs architecture protocols utilizing new selection metrics is proposed. Two important metrics have been analysed and mathematically modelled, outage probability and bandwidth efficiency, respectively. Both metrics have been analysed as a function of the distance, number of RAUs, fiber optic attenuation, and path loss factor. Based on the simulation and numerical analysis, the outage probability of proposed protocols is reduced by 65% compared to recent work; in addition, the bandwidth efficiency of the proposed protocol is increased by 34% compared to recent work.

Abstract Scalability is one of the important parameters for mobile communication networks of the present generation and further to the future 5G and beyond networks. When a user is in motion transferring from one cell site to another, then the handover procedure becomes important in the sense that it ensures that a user gets consistent connection without interruption. Nevertheless, the classic handover process in cellular networks has some sort of drawback like causing service interruptions, affecting packet transmission, and increased latency which is highly uncongenial to the evolving applications which have stringent requirement to latency. To overcome these challenges and improve the mobile handover in 5G and future mobile networks, this article puts forth a predictive handover mechanism using reinforcement learning algorithm. The RL algorithm outperforms the ML algorithm in several aspects. Compared to ML, RL has a higher handover success rate (∼95% vs. ∼90%), lower latency (∼30 ms vs. ∼40 ms), reduced failure rate (∼5% vs. ∼10%), and shorter disconnection time (∼50 ms vs. ∼70 ms). This demonstrates the RL algorithm's superior ability to adapt to dynamic network conditions.

Software logs generated by dedicated network testing hardware are often complex and bear minimal similarity to natural language, requiring the expertise of engineers to understand and capture defects recorded in these logs. This manual process is inefficient and expensive for both service providers and their clients. In this study, we demonstrate the transformative potential of Artificial Intelligence (AI), specifically through domain-tailoring of Large Language Models (LLMs) like RoBERTa, BigBird, and Flan-T5, to streamline the process of defect diagnostics. Particularly, we pre-train these models ground up on a real industrial telecommunications log corpus, and perform finetuning on a multi-label classification objective. This facilitates identifying a correct set of log points to be enabled for rapid detection of defects that arise during network testing. Despite encountering several challenges such as intricate text structures, heavily skewed label distribution, and inconsistencies in historical data labelling, our tailored LLMs achieve commendable performance on previously unseen defect cases, significantly reducing the turnaround times. This research not only serves as an exemplar for adapting LLMs in telecommunications industry for automated defect diagnostics, but also has wide implications for software log analysis across various industries.

Abstract As we enter the new age of the Internet of Things (IoT) and wearable gadgets, sensors, and embedded devices are extensively used for data aggregation and its transmission. The extent of the data processed by IoT networks makes it vulnerable to outside attacks. Therefore, it is important to design an intrusion detection system (IDS) that ensures the security, integrity, and confidentiality of IoT networks and their data. State-of-the-art IDSs have poor detection capabilities and incur high communication and device overhead, which is not ideal for IoT applications requiring secured and real-time processing. This research presents a teaching-learning-based optimization enabled intrusion detection system (TLBO-IDS) which effectively protects IoT networks from intrusion attacks and also ensures low overhead at the same time. The proposed TLBO-IDS can detect analysis attacks, fuzzing attacks, shellcode attacks, worms, denial of service (Dos) attacks, exploits, and backdoor intrusion attacks. TLBO-IDS is extensively tested and its performance is compared with state-of-the-art algorithms. In particular, TLBO-IDS outperforms the bat algorithm and genetic algorithm (GA) by 22.2% and 40% respectively.

The Internet of Things (IoT) is considered one of the trending technologies today. IoT affects a variety of industries, including logistics tracking, healthcare, automotive and smart cities. A rising number of cyberattacks and breaches are rapidly targeting networks equipped with IoT devices. Due to the resource-constrained nature of the IoT devices, one of the Internet security issues impacting IoT devices is the Denial-of-Service (DoS). This encourages the development of new techniques for automatically detecting DoS in IoT networks. In this paper, we test the performance of the following Machine Learning (ML) algorithms in detecting IoT DoS attacks using packet analysis at regular time intervals: Neural Networks (NN), Gaussian Naive Bayes (NB), Decision Trees (DT), and Support Vector Machine (SVM). We were able to achieve 98% accuracy in intrusion detection for IoT devices. We have created a novel way of detecting the attacks using only six attributes, which significantly reduces the time to train the ML Models by 58% on average. This research is based on data collected from actual IoT attacks on IoT networks. This paper shows that using the DT or NN; we can detect attacks on IoT devices. Furthermore, it shows that NB and SVM are poor in detecting IoT attacks. In addition, it proves that middle boxes embedded with ML Models can be utilized to detect attacks in places such as houses, manufactures, and plants.

Abstract The fifth‐generation (5G) technology is seen to be a solution for developing countries to improve their quality of services in terms of transportation, education, health, agriculture, and other fields, thereby holding the promises of economic transformation by improving productivity and the quality of life. The paper considers some of the challenges that face operators, investors, and providers when planning to introduce 5G technology to developing countries. The main focus of this paper is the 5G transport network, in particular, the backhaul network. The 5G transport network architectural options and scenarios are discussed based on several standards and previous studies, the problems of existing infrastructures of developing countries are investigated, and new proposed technologies that may help to address those challenges are considered.

Abstract The fading scenario of many realistic wireless communication transmission systems, such as, multi‐hop communications and spectrum sharing in cognitive radio networks (CRNs), can be modelled by the product and the ratio of the product of the random variables (RVs) of the channel distribution. However, there is no work has been investigated in the literature to provide unified statistics of the product and the ratio of the products that can be used for a wide range of non‐composite and composite fading conditions. Accordingly, in this paper, the statistical properties, namely, probability density function (PDF), cumulative distribution function (CDF), and moment generating function (MGF) of the product and the ratio of the product of independent and non‐identically distributed (i.n.d.) mixture Gamma (MG) RVs are derived. A MG distribution has been widely employed to approximate with high accuracy most of the conventional fading models, for example, Rayleigh, Nakagami‐ m , Nakagami‐ q (Hoyt), and Nakagami‐ n (Rician) as well as the generalised composite fading channels, such as, generalised‐/gamma, /gamma, and /gamma. Hence, the derived PDF, CDF, and MGF are utilized for the Beaulieu–Xie and shadowed fading channels that have not been yet presented by the previous works due to mathematical intractability of their statistics. Thus, the equivalent parameters of a MG distribution for these channels are given. To this end, simple closed‐form mathematically tractable expressions of the performance metrics are obtained. The derived statistics are applied to analyse the outage probability (OP), the average error probability for different modulation schemes, the effective rate (ER) of wireless communication systems and the average area under the receiver operating characteristics (AUC) curve of energy detection over cascaded fading channels. Moreover, the OP of the multi‐hop communications systems with co‐channel interference (CCI), both the lower bound of secure OP (SOP L ) and probability of non‐zero secrecy capacity (PNSC) of the physical layer security (PLS), and the outage and delay‐limited capacities of CRNs are studied via using the statistics of the ratio of the product of MG variates. A comparison between the numerical results and the Monte Carlo simulations is presented to verify the validation of our analysis.

In its early deployment, 5G is expected to be integrated with conventional micro wave (μw) base stations (BSs) in small cells using millimetre wave (mmw) band for access to enhance the traditional system. The main goal of 5G is universal coverage and at a higher rate. In this paper, a scheme for increasing the rate coverage of the conventional macro cell by exploiting the wide mmw band spectrum is proposed. This scheme is inspired by the Soft Frequency Reuse (SFR) technique. Since the cell edge area has a lower coverage rate due to high interference and less received power, it is served by a mmw band. Small mmw Remote Radio Heads (RRHs) are overlaid onto conventional macro cell on cells edges in a Heterogeneous Cloud Radio Access Network (HC-RAN) architecture. The neighbouring RRHs are clustered together based on the suggested clustering algorithm. The RRH clustering problem formulated as a bin packing problem Simulation results show that the HC-RAN system adopting the suggested scheme has significantly higher coverage and rate compared to an HC-RAN system with small cells only deployed in hot spots. Specifically, a gain of 20%-40% is achieved in coverage and rate when compared to the systems applying the SFR technique and HC-RAN architecture with randomly deployed mmw RRHs. This enhancement in rate and coverage is due to a significant reduction in the interference level resulting from the adopting the suggested scheme, which benefits from high path loss, blockage and wide band properties of an mmw channel. Furthermore, the impact of the mmw cell size and density on the system performance is investigated.

In this study, the secrecy performance of physical layer when both the main and wiretap channels undergo shadowed fading conditions is analysed. In particular, the average secrecy capacity, secure outage probability (SOP), the lower bound of SOP (SOP ), and the probability of strictly positive secrecy capacity are derived by using the classic Wyner's wiretap model. Two different scenarios for the fading parameters, namely, and m , which represent the real extension of the number of the multipath clusters and the shadowing index, respectively, have been studied. These parameters are chosen first as arbitrary numbers, thus the performance metrics are given in exact closed‐form in terms of the extended generalised bivariate Fox's H ‐function that has been widely implemented in the open literature using various software packages. In the second scenario, both the fading parameters are assumed to be integer numbers to obtain the derived results in simple exact closed‐form mathematically tractable expressions in terms of some analytic functions. The numerical results of this analysis are verified via the Monte Carlo simulations.

Advances in the development of low powered sensors has meant they can now provide solutions to Internet of Things (IoT) networks that suffer from restricted power supply and a lack of resource facilities. In this paper, a hybrid time division multiple access (TDMA)-carrier sense multiple access with a collision avoidance mechanism (CSMA/CA) medium access control (MAC) protocol has been proposed that efficiently utilizes the energy of the nodes and dynamically adapts the sleep/wake-up periods according to the variance in the network loads. This hybrid protocol first schedules the TDMA time slots (TDMAslots), and then allocates each slot to a group of devices that compete for the medium using the CSMA/CA. This case is different from the traditional CSMA/CA-TDMA hybrid protocol, in which all the devices compete to access the channel, following which, each successful device is allocated an individual time slot. At the commencement of each superframe, the base station broadcasts a scheduler table, which includes network grouping information that is used by the IoT devices to categorize themselves into wake-up and sleep groups. To reduce the number of collisions or channel access failures, this information permits only one group to compete for each TDMAslot. A 3-D Markov model is used to develop a per user stochastic behavior for the proposed hybrid MAC protocol-based adaptable sleep mode. The simulation results demonstrate the effectiveness of the proposed protocol, which improves the network throughput and enhances energy conservation by 40%-60% more than the IEEE 802.15.4-based MAC protocol.

This paper introduces a proof-of-concept IPv6 over low power wireless personal area network (6LoWPAN) testbed to study the integration of programmable network technologies in relaxed throughput and low-power Internet of Things (IoT) devices. Open source software and hardware platforms are used in the implemented testbed to increase the possibility of future network extension. The proposed architecture offers end-to-end connectivity via the 6LoWPAN gateway to integrate IPv6 hosts and the low data rate devices directly. Nowadays, software-defined networking (SDN) and network function virtualization (NFV) are the most promising technologies for dealing with the massive increase in machine-to-machine devices and achieving agile traffic. The developed approach in this paper is entitled tailored software defined-NFV (SD-NFV), which is aimed at reducing the end-to-end delay and improving the energy depletion in sensor nodes. Experimental scenarios of the implemented testbed are conducted using a simple sensing application and the obtained results indicate that the introduced approach is appropriate for constrained IoT devices. By utilizing SD-NFV scheme in 6LoWPAN network, the data delivery ratio increased by 5%-14%, the node operational time prolonged by 70%, the endto-end latency for gathering sensor data minimized by 160%, and the latency for transmitting control messages to a specified node diminished by 63% when compared to a traditional (non SDN-enabled) 6LoWPAN network.

Due to the flexible deployment, low-cost and management, unmanned aerial vehicles, quadcopters have attracted significant interest lately in expanding wireless communications to areas that lack to cellular coverage network. Currently, software-defined network (SDN) is considered a viable alternative that improves network scalability and management. Earlier in 2018, we designed a novel software-defined quadcopter (SDQ) with a mobile Internet of Things vehicle to measure the best efficient wind power location for effective future wind turbine placement. However, large wind farms require complex and scalable wind measurement platform that consists of multiple quadcopters and ground mobile nodes that operate under a decision-making softwarized protocol. To this end, this paper proposes a novel cognitive routing protocol called SDQ interdomain management (SDQIM) Protocol. The SDQIM structure consists of multiple SDN controllers with failover capability. Our proposed protocol operate with multiple phases as each phase is used to cover a specific scenario that could occur in the interdomain network. The SDQ-main will have a total overview of the network topology and the SDQ-slave will be responsible for communication management with all other local subdomains. However, for large-scale farmland, quadcopter power level is essential for the continuity of the system services. Thus, we additionally propose a decentralized inductive power transfer (DIPT) platform that operates autonomously using software defined controlling approach. In essence, The DIPT platform is considered to be automated and low-cost approach that encompasses a custom-designed SDN controller for all interdomain quadcopters. Our system has been implemented by using an experimental testbed. The experimental results showed that scalability of the SDQ system can be increased to cover large wind farms with uninterrupted power management platform.

In vehicular communications, periodic one-hop broadcast of beacons allows cooperative awareness for vehicles. To avoid congestion in the shared channel used for transmission of beacons, a joint beacon frequency and power control protocol based on game theory is presented in this paper. The existence, uniqueness and stability of the Nash Equilibrium (NE) of the game is proved mathematically. An algorithm is devised to find the equilibrium point in a distributed manner and its stability and convergence has been validated using simulation. The algorithm converges to the NE from any initial frequency and power and it can provide both fairness in power and weighted fairness in frequency. The protocol has per vehicle parameters, hence, every vehicle can control its share of the bandwidth according to its dynamics or safety application requirements while the whole usage of bandwidth is controlled at a desired level.

This paper proposes: 1) a traffic flow management policy, which allocates and organizes machine type communication (MTC) traffic flows network resources sharing within evolved packet system (EPS); 2) an access element as a wireless sensor network gateway for providing an overlaying access channel between the machine type devices and EPS; and 3) it addresses the effect and interaction in the heterogeneity of applications, services and terminal devices, and the related quality of service (QoS) issues among them. This paper overcomes the problems of network resource starvation by preventing deterioration of network performance. The scheme is validated through simulation, which indicates the proposed traffic flow management policy outperforms the current traffic management policy. Specifically, simulation results show that the proposed model achieves an enhancement in QoS performance for the MTC traffic flows, including a decrease of 99.45% in packet loss rate (PLR), a decrease of 99.89% in packet end to end (E2E) delay, a decrease of 99.21% in packet delay variation (PDV). Furthermore, it retains the perceived quality of experience of the real time application users within high satisfaction levels, such as the voice over long term evolution service possessing a mean opinion score (MOS) of 4.349 and enhancing the QoS of a video conference service within the standardized values of a 3GPP body, with a decrease of 85.28% in PLR, a decrease of 85% in packet E2E delay and a decrease of 88.5% in PDV.

In this paper, a self-organizing cloud radio access network (C-RAN) is proposed, which dynamically adapt to varying network capacity demands. A load prediction model is considered for provisioning and allocation of base band units (BBUs) and remote radio heads (RRHs). The density of active BBUs and RRHs is scaled based on the concept of cell differentiation and integration (CDI) aiming efficient resource utilisation without sacrificing the overall quality of service (QoS). A CDI algorithm is proposed in which a semi-static CDI and dynamic BBU-RRH mapping for load balancing are performed jointly. Network load balance is formulated as a linear integer-based optimization problem with constraints. The semistatic part of CDI algorithm selects proper BBUs and RRHs for activation/deactivation after a fixed CDI cycle, and the dynamic part performs proper BBU to RRH mapping for network load balancing aiming maximum QoS with minimum possible handovers. A discrete particle swarm optimization (DPSO) is developed as an evolutionary algorithm to solve network load balancing optimization problem. The performance of DPSO is tested based on two problem scenarios and compared to genetic algorithm (GA) and the exhaustive search (ES) algorithm. The DPSO is observed to deliver optimum performance for small-scale networks and near optimum performance for large-scale networks. The DPSO has less complexity and is much faster than GA and ES algorithms. Computational results of a CDI-enabled C-RAN demonstrate significant throughput improvement compared to a fixed C-RAN, i.e., an average throughput increase of 45.53% and 42.102%, and an average blocked users reduction of 23.149%, and 20.903% is experienced for proportional fair and round Robin schedulers, respectively.

The high speed, low cost, sharing of peripheral devices and central administration features of the Ethernet have led to it being widely trusted as the backbone for recent networks. However, it suffers from many practical limitations leading to a lack of scalability, owing to its broadcast and multicast mechanisms, particularly in relation to the discovery processes. Whilst software-defined networks (SDN) have overcome many legacy network problems, scalability remains a major issue, because broadcasting and multicasting have been inherited. Moreover, the problem is exacerbated with increasing network traffic, which results in higher bandwidth consumption, congestion, and increased probability of a single point of failure. To address this, servers under software-defined network architectures to eliminate discovery messages (SSED) is designed in this paper, and a backbone of floodless packets in an SDN LAN network is introduced. For SSED, flood discovery packets created by the dynamic host configuration protocol in the application layer and the address resolution protocol in the data link layer are considered, respectively. SSED eliminates any broadcast discovery packets with better performance, lowers peak overhead, and introduces an innovative mechanism for defining the relationship between the servers and SDN architecture. Experimental results after constructing and applying an authentic testbed verify that our proposed model has the ability to improve the scalability by removing broadcast packets from the data plane, reduction of control packets in the control plane, lessening peak overhead on the controller, preventing it experiencing failed requests, offering better response time, and providing more efficient performance.

This paper investigates the statistical-queueing constraints and pilot contamination phenomenon in irregular cellular massive multiple-input- multiple-output (MIMO) systems where base stations are Poisson distributed. Specifically, analytical expressions for the asymptotic signal-to- interference-ratio (SIR) coverage, rate-coverage and effective capacity under the quality of service (QoS) statistical-exponent constraint are provided for uplink transmission when each base station deploys a large number of antennas. We show that the QoS constrained capacity is in proportional to the path-loss exponent and inversely proportional to the pilot re-using probability which in turn is a function of cell load. Simulation results prove that pilot reuse impairments can be alleviated by employing a cellular frequency-reuse scheme, e.g., with frequency reuse factor (FRF) of unity, we see that, 40% of the total users have SIR above -10.5dB, whereas, with frequency reuse factor of 7, the same fraction of users has SIR above 20.5dB.

This paper investigates the asymptotic behaviour (error and outage probabilities) of a single cell multiple-input multiple-output (MIMO) system aided by a large scale antenna array. Specifically, the uplink transmission over composite fading channel with power-scaling scheme is considered. Where, most reported studies in this respect discuss the case of downlink scenario for convenience MIMO systems. Two assumptions are addressed: perfect channel information (CSI) and imperfect-CSI. In both cases, closed form expressions for error and outage probabilities in asymptotically large receive antenna environments are derived. Moreover, users' location impact on system performance is introduced. Numerical outcomes, validated by Monte-Carlo simulations, shed light on how different parameters and conditions can affect aforementioned performance metrics.

Millimetre-wave (mm-wave) bands are considered an interesting candidate in the fifth generation (5G) mobile networks due to the high available bandwidth at these bands. Understanding the propagation performance of different mm-wave frequencies is an important issue to enhance the futuristic cellular networks. This paper investigates and compares the propagation performance of different mm-wave bands with the ultra-high frequency (UHF) by evaluating coverage and rate trends. The proposed scenario applied a map-based model for the base stations (BSs) deployment in university campus with a random distribution of users. The path loss models are determined by specifying the actual buildings' locations within the real campus map. Simulation results showed that the dense deployment of BSs will enhance the coverage of all mm-wave frequency bands and will offer limited noise networks. Comparison results showed that although the 73 GHz bands could provide good coverage with the lowest interference effects, it is still limited to small cell size. Also the 73 GHz bands results showed the higher rate achieved due to the large available bandwidth in this band.

In vehicle to vehicle communication, every vehicle broadcasts its status information periodically in its beacons to create awareness for surrounding vehicles. However, when the wireless channel is congested due to beaconing activity, many beacons are lost due to packet collision. This paper presents a distributed congestion control algorithm to adapt beacons transmit power. The algorithm is based on game theory, for which the existence of the Nash Equilibrium (NE) is proven and the uniqueness of the NE and stability of the algorithm is verified using simulation. The proposed algorithm is then compared with other congestion control mechanisms using simulation. The results of the simulations indicate that the proposed algorithm performs better than the others in terms of fairness, bandwidth usage, and the ability to meet the application requirements.

In large‐scale computing centres, the advancement of knowledge in regard to the predicted power consumption (PC) and concerns of host servers that run virtual machines (VMs) could improve the capacity planning and networks’ energy efficiency. A parameterised power model is proposed to explore the individual components within the virtualisation‐based cloud radio access network. The model evaluates the PC and trade‐offs of a server undergoing virtualisation. After cooling and total PC for cloud radio access network architecture, with and without virtualisation have been compared using differentiated parameters, such as varying number of bare‐metal base band units, VMs and system's resource blocks (RBs) share/bandwidth. The results show dramatic decrease in the total PC via virtualising the core network. In addition, the degraded performance of each virtualised server is demonstrated via modelling the execution time and overhead costs. These costs have been resulted from increasing the number of hosted VMs and utilised RBs by each VM.

Machine-to-Machine (M2M) communication is the leading technology for realising the Internet-of-Things (IoT). The M2M sensor nodes are characterized by low-power and low-data rates devices which have increased exponentially over the years. IPv6 over low power wireless personal area network (6LoWPAN) is the first protocol that provides IPv6 connectivity to the wireless M2M sensor nodes. Having a tremendous number of M2M sensor nodes execute independent control decision leads to difficulty in network control and management. In addition, these evergrowing devices generate massive traffic and cause energy scarcity, which affects the M2M sensor node lifetime. Recently, software defined-networking (SDN) and network functioning virtualization (NFV) are being used in M2M sensor networks to add programmability and flexibility features in order to adopt the exponential increment in wireless M2M traffic and enable network configuration even after deployment. This paper presents a proof-of-concept implementation which aims to analyze how SDN, NFV, and cloud computing can interact together in the 6LoWPAN gateway to provide simplicity and flexibility in network management. The proposed approach is called customized software defined-NFV (SD-NFV), and has been tested and verified by implementing a real-time 6LoWPAN testbed. The experimental results indicated that the SD-NFV approach reduced the network discovery time by 60% and extended the node's lifetime by 65% in comparison to the traditional 6LoWPAN network. The implemented testbed has one sink which is the M2M 6LoWPAN gateway where the network coordinator and the SDN controller are executed. There are many possible ways to implement 6LoWPAN testbed but limited are based on open standards development boards (e.g., Arduino, Raspberry Pi, and Beagle Bones). In the current testbed, the Arduino board is chosen and the SDN controller is customized and written using C++ language to fit the 6LoWPAN network requirements. Finally, SDN and NFV have been envisioned as the most promising techniques to improve network programmability, simplicity, and management in cloud-based 6LoWPAN gateway.

An inefficient utilization of network resources in a time-varying traffic environment often leads to load imbalances, high call-blocking events and degraded quality of service (QoS). This paper optimizes the QoS of a cloud radio access network (C-RAN) by investigating load balancing solutions. The dynamic re-mapping ability of C-RAN is exploited to configure the remote radio heads (RRHs) to proper base band unit sectors in a time-varying traffic environment. RRH-sector configuration redistributes the network capacity over a given geographical area. A self-optimized cloud radio access network (SOCRAN) is considered to enhance the network QoS by traffic load balancing with minimum possible handovers in the network. QoS is formulated as an optimization problem by defining it as a weighted combination of new key performance indicators for the number of blocked users and handovers in the network subject to RRH sectorization constraint. A genetic algorithm (GA) and discrete particle swarm optimization (DPSO) are proposed as evolutionary algorithms to solve the optimization problem. Computational results based on three benchmark problems demonstrate that GA and DPSO deliver optimum performance for small networks, whereas close-optimum is delivered for large networks. The results of both GA and DPSO are compared to exhaustive search and K-mean clustering algorithms. The percentage of blocked users in a medium sized network scenario is reduced from 10.523% to 0.421% and 0.409% by GA and DPSO, respectively. Also in a vast network scenario, the blocked users are reduced from 5.394% to 0.611% and 0.56% by GA and DPSO, respectively. The DPSO outperforms GA regarding execution, convergence, complexity, and achieving higher levels of QoS with fewer iterations to minimize both handovers and blocked users. Furthermore, a tradeoff between two critical parameters for the SOCRAN algorithm is presented, to achieve performance benefits based on the type of hardware utilized for C-RAN.

Densifying the communications network and integrating innovative technologies leads to increased power consumption (PC), along with increased signalling and degraded scalability. The latter can be mitigated by using software defined networks, while cloud radio access network (C‐RAN) reduces the PC. Since evaluating and improving the PC is an important key success factor for the upcoming fifth generations, a reliable power model (PM) is required. This study proposes a componentised, linear and parameterised PM, and explores the individual components relevant for PC analysis, particularly for software defined C‐RAN (SDC‐RAN) architecture. The model quantifies the energy efficiency (EE) by capturing the PC of individual components, and measures the amount of PC in the network. Cooling and total PC of C‐RAN and SDC‐RAN for different parameters such as varying numbers of antennas and different system's bandwidth share has also been considered. The results show that SDC‐RAN increases the total PC by about 20% compared with C‐RAN. Additionally, the study shows the results of modelling the participating core network's control plane unit's PC along with establishing the accuracy of the components and the parameterised models.

The fifth generation cellular network performance is measured by its spectral and energy efficiency (EE). Densifying the network might provide a solution. However, this will lead to tremendous network infrastructure and increased power consumption (PC). Cloud radio access network (C‐RAN) has emerged as a solution to curtail the PC and deliver spectrum sharing in a cost‐effective and energy‐efficient way. Since the PC is an important key success for the upcoming generations, and in order to study and evaluate the power reductions achievable by C‐RAN, a reliable power model (PM) is required. This study proposes a component, linear and parameterised PMs to explore the individual components relevant for PC analysis, particularly for C‐RAN architecture. The models quantify the EE by capturing the power consumed by individual components, and the amount of power reduced in the network. The model shows a dramatic reduction in the cooling PC (87.4%), whereas the total PC is reduced to about (33.3%) compared with macro base stations deployment. Finally, accuracy comparison of the component and parameterised models has been presented.

One of the major problems, caused by traffic congestion, owes its existence to the unwanted delay experienced by the priority vehicles. The evaluation of two scheduling algorithms as adaptive traffic control algorithms has been proposed here to reduce this unwanted delay. One of these algorithms is the earliest deadline first (EDF) algorithm, whereas the other is the fixed priority (FP) algorithm. The performance of both algorithms as adaptive traffic light control algorithms is evaluated for isolated traffic intersections. A comparative study is performed here, where the performance of these algorithms is compared against a fixed static traffic light controller. Moreover, their performance is also compared against each other. Conclusive results from the simulation of the algorithms reveal that the number of stops, average delay, and mean trip time of the priority vehicles is significantly reduced by the implementation of these algorithms. Furthermore, it has been shown that the overall performance of EDF is much better than FP in terms of improvement of different performance measures for congestion reduction of priority vehicles.

In wireless ad hoc networks, all nodes have equal right to access the medium. Hence, the performance of this mode is mostly limited by traffic congestion. To alleviate such a problem, Cognitive Radio (CR) technology can be used. Recent researches show that a large amount of licensed spectrum remains unused at a specific time. The contribution of this paper is to investigate a CR-based Medium Access Control (MAC) layer for wireless ad hoc networks. We aim to focus on a Cognitive MAC protocols for a unlicensed user which can be enabled to access the large amount of unused spectrum allocated for a licensed user, in an intelligent way, without causing any harmful interference. We propose a cognitive MAC protocols based on the theory of the Partially Observed Markov Decision Process (POMDP), which sense the radio spectrum, detect the occupancy state of different primary channels, and then opportunistically communicate over unused channels (spectrum holes). The objective is to make efficient decisions on which channels to sense and access, that ensure maximization of the throughput of the secondary user.

Throughout this study, an adaptive competitive second-price pay-to-bid sealed auction game is presented as a solution to the fairness problem of spectrum sharing among a number of users in a cognitive radio environment. First, a comparison among three main spectrum-sharing game models; optimal, cooperative and competitive game models is discussed to highlight the advantages and disadvantages of each model. The results prove that cooperative games aim to achieve Nash equilibrium between primary and secondary players and provide better revenue to them. Also, it proves that cooperative games are best when the number of secondary users changes dynamically, but only when the number is low. As in practical situations, the number of secondary users might increase dramatically and cooperative games will lose their powerful advantage once that happens. As a result, the proposed mechanism creates a competition between the bidders and offers better revenue to all players in terms of fairness. The proposed model ensures that users with better channel quality, higher traffic priority and fairer bids will get a better chance to share the offered spectrum. It is shown by numerical results that the proposed mechanism could reach the maximum total profit for all users with better fairness.

Ontology alignment facilitates exchange of knowledge among heterogeneous data sources. Many approaches to ontology alignment use multiple similarity measures to map entities between ontologies. However, it remains a key challenge in dealing with uncertain entities for which the employed ontology alignment measures produce conflicting results on similarity of the mapped entities. This paper presents OARS, a rough-set based approach to ontology alignment which achieves a high degree of accuracy in situations where uncertainty arises because of the conflicting results generated by different similarity measures. OARS employs a combinational approach and considers both lexical and structural similarity measures. OARS is extensively evaluated with the benchmark ontologies of the ontology alignment evaluation initiative (OAEI) 2010, and performs best in the aspect of recall in comparison with a number of alignment systems while generating a comparable performance in precision.

Radio over fibre (RoF) technology is currently receiving large attention due to its ability to provide simple antenna front ends, increased capacity, and multi radio wireless access coverage. In this paper, an all-photonic Digital Radio over Fibre (DRoF) link is proposed. By using this DRoF system, performance of an integrated transportation system, for transporting multi-types analogue, digital and baseband signals over single mode fibre is investigated. Simulation results proved that bit error rate (BER) of DRoF communication link is remarkably better than the analogue RoF (ARoF).

This paper derives a simulation based comparison for UWB-OFDM with different multipath channel models. Several multipath channel models such as (AWGN, Rayleigh and Rician) has been simulated and compared with a proposed hybrid combination of Rayleigh, Rician and AWGN to observe a realistic multipath faded environment. These cases are based on no fading and flat Rayleigh- fading, multiple-diversity reception Rayleigh-fading, and flat Ricean-fading. These simulations are used to determine both signal to noise ratio and bit error rate for multi-amplitude constellations. The combination of Rayleigh and AWGN channels give BER and SNR of 0.5025 and 15.25dB respectively in flat fading mode, whereas combination of Rician and AWGN produces BER and SNR upto 0.4999 and 16.63dB. The proposed Hybrid combination of Rayleigh, Rician and AWGN produces a decay in BER and SNR approximately 2% and 3.5% respectively.

A distance based power control scheme is proposed and developed for application-controlled handover (ACH) in wireless personal area network (WPAN). In this paper, a power efficient communications in the wired wireless synergy network environment that consists of 3G (UMTS) + WiMAX + WLAN + WPAN (UWB) and optical network has been developed. This paper presents an enhanced power controlled transmission mechanism, which maintains the channel and the seamless transmission from mobile device to the remote optical fibre network, to provide real time service continuity for multimedia traffic with minimum power consumption. The results have proven the system performance improvements in the network throughput, the average data drop has been reduced 40% and the end-to-end network power consumption is reduced 10% when the proposed approach is applied on ACH based WPAN.

The IEEE 802.11 standard conformant wireless communication stations have multi-rate transmission capability. To achieve greater communication efficiency, multi-rate capable stations use rate-adaptation to select appropriate transmission rate according to variations in the channel quality. This paper proposes a novel rate-adaptation scheme where the decision of rate selection relies on the mutual feedback of a transmitter and receiver pair. As an important feature of a rate-adaptation scheme, our proposed solution is highly responsive when compared with existing rate-adaptation scheme. Using the mutual-feedback, it has been made possible to achieve frame-loss differentiation with just three frames, avoiding the use of RTS/CTS and further delays in this process. Unlike the previous approaches, the feedback is delivered to the transmitter without any changes to the standard frame format. Various performance tests assert the suitability of our proposed solution in different test scenarios over existing rate-adaptation schemes.

Contention-based forwarding (CBF) has proven to achieve a good performance in routing in mobile and vehicular ad hoc networks. CBF's main advantage is that it does not require the knowledge about the local neighborhood, eliminating, therefore, the periodic beacon exchange that causes degradation in the network performance, especially when the density of the neighborhood is high. On the other hand, the main issue that the contention-based forwarding faces is packet duplications, which mainly occurs due to the hidden node problem. This paper introduces a suppression algorithm for contention-based forwarding to eliminate packet duplications, called Sender-based Suppression and referred to as SS-CBF. In addition to the idea of dividing the radio range of the sending node into Reuleaux triangle zones, SS-CBF assigns a time delay to every zone, which aggregates to the timer value, set by the nodes, to form the time required for deferring. Moreover, the Sending node is involved in the suppression process in order to prevent unwanted nodes from transmission. SS-CBF is simulated using OPNET 14.5 modeler and evaluated against area-based suppression scheme in terms of network overhead and effective throughput.

Multi-media applications with demanding throughput requirements often raise issues of capacity limitations in wireless networks. High data rate (HDR) wireless personal area networks (WPANs) can operate in a mesh configuration to extend from the legacy single-hop communication to multiple hops. Although the range of WPANs is increased in a mesh configuration, there are capacity constraints because the superframe time is shared by multiple piconet clusters instead of being dedicated for a single piconet cluster just like in the legacy single-hop case. Furthermore, the distributed superframe sharing can cause fairness issues because there is no mechanism to determine the requirement of each mesh piconet coordinator (MPNC) and monitor a fair allocation to each MPNC. Here, the authors propose a centralised resource allocation approach and define three resource allocation policies for meshed HDR WPANs. The proposed approach is augmented by a traffic estimation strategy to predict a suitable fraction of superframe time for each cluster. Simulation results prove the effectiveness of the proposed resource allocation policies and the fairness index is shown to increase upto 42% with the proposed approach in some cases.

Future generation multi-homed networks are envisioned to be a combination of diverse but complementary access technologies. Internetworking these types of networks will provide mobile users with ubiquitous connectivity across a wide range of networking environments. The integration of existing and emerging heterogeneous wireless networks requires the design of intelligent handovers and location management schemes to enable mobile users to switch network access and experience uninterrupted service continuity anywhere, anytime. Real deployment of such mobility strategies remains a significant challenge. In this paper, we focus on failure detection, locator pair exploration and handover management. This paper presents an employment over the reachability protocol (REAP) behaviour to improve the performance on Transport and Link Layers, which is achieved by specific Shim6 protocol messages. This paper presents a handover technique that aims to reduce the number of handovers the mobile device will face, keeping in mind providing mobility over a wide range of access technologies. Furthermore, this paper also discusses some mechanism aimed to reduce the amount of power needed to keep the interfaces actively scanning for access points in a multi-home Mobile host (mhMH).

In Mobile Ad Hoc Network (MANET) many routing protocols exist, which are capable of routing data packets from source to destination. Each protocol is designed to fulfill its requirement; the constant network context (i.e. number of nodes, mobility, etc); but network context could be changed during the running time which affects the protocol performance and reduces its efficiency. In this paper, a MANET routing optimizer is presented which is capable of selecting the network context and the routing protocol. The optimizer is capable of choosing the optimum routing protocol according to networkpsilas context and give the optimum network context for the current network situation. It is adaptable of introducing alterations in the network environment by foretelling four important parameters that indicate the changes in the network context.

Current mobile devices are often equipped with several network interfaces, which may be of different access technologies, both wireless and cellular. As a result, many networks are evolving to serve diverse communication needs. These networks are increasingly interoperable and based on IP architectures. Wide area networks, with pervasive coverage in many parts of the world, are forming the basis for many multimode services. Different requirements of different applications can result in a different preference of the interface that should be used. Network connections should be placed in the best possible interface based on these requirements. During communication, changes in the availability or characteristics of an access network behind an interface may result in a situation where already established connections should to be moved from one interface to another. This paper presents an interface selection mechanism for multi-homed mobile hosts, the paper introduce an interface selection mechanism by which the Multi-homed Mobile Node is able to dynamically select the right interface when it is moving from one coverage area to another based on special requirement defined by the user or the application initiated the communication. Thatpsilas lead to maintain ongoing communication while moving around different coverage areas.

The wired-wireless integration network can be categorised as fixed mobile convergence (FMC). FMC means the convergence of the existing wired network and wireless network. Therefore a mobile device needs the function of connection and control to the FMC infrastructure. An application-controlled handover is developed, which keeps channel continuity in the wired-wireless synergy network environment that consists of 3G (UMTS)+WLAN+WPAN (UWB) and optical fibre network. A handover mechanism transmits and receives data by using the proposed application selection criteria. It maintains the channel and the seamless transmission from mobile device to the remote optical fibre network, to provide real-time service continuity for multimedia traffic. The results show that application-controlled handover has a reduction up to 83% in packet drop, 74% reduction in bit error rate, 85% reduction in power consumption and 100% enhancement in application response time (delay) as compared with the network without handover technique.

Routing protocols face many challenges in Mobile Ad Hoc Networks (MANETs) due to the dynamic nature of wireless medium and unpredictable topological changes. This paper proposes On-Demand Link-Weight (ODLW) routing protocol. ODLW selects an optimum route on the basis of link reliability taking in consideration the link bandwidth, delay and node lifetime. The approach is based on Cross- Layer design where Physical Layer parameters are used as inputs for decision making at the routing layer. The simulation results show a significant improvement over AODV in terms of Network load, Route Discovery time and End-to-end delay.

The service discovery is a crucial part of any wireless network because it has a direct effect on the network efficiency and usability. This work proposes a signalling model that could be used for registry and updating of services with a simulation model for service discovery in personal clusters based on WLAN air interface network. The personal cluster is a network that is owned by one user. However, this model is still valid for any trusted network. Simulation model and analysis of the performance for this approach have been presented. Simulation results show that the end-to-end delay is less affected by the number of nodes when this technique is applied. This work is sponsored by a communication EU project named MAGNET BEYOND.

Zone routing protocol (ZRP) is a hybrid MANET protocol. ZRP combines between the proactive routing approach and the reactive approach. The network in ZRP is divided into several zones, where the proactive is applied within each zone. Outside the routing zone, the reactive approach is used. In this paper, a development to ZRP protocol based centralised intra-zone routing is proposed. The proposed concept replaces the proactive protocol in the routing zone by a new technique, where the central node in each zone provides the routing information for the intra-zone traffic. This development enhances the ZRP performance by reducing the overhead traffic control messages and distributing the data traffic in the network evenly

This paper investigates and undertakes simulation-based comparison of on-demand routing protocols in multi ad hoc networks. First, it investigates the factors affecting the performance criteria and working architecture of ad hoc on-demand distance vector (AODV), dynamic source routing (DSR) and temporally ordered routing algorithm (TORA). Second, it considers proposing a scenario of multi ad hoc network domains and their inter-communication using above three routing protocols separately. The simulation results show that throughput for AODV is better than both DSR and TORA by 50%. AODV has 25% lower delay than DSR and 50% lower than TORA for large number of nodes (20 nodes). The simulation is based on the application scenario model implemented on Opnetworks 10.5. It later suggests enhancement to overcome possible shortcomings observe in real life application scenario.

This paper presents a bi-directional optical link for a wireless indoor coverage system operating in the UMTS band, using radio over fibre technology. It shows the feasibility of a dual loop architecture in which only one optical source for both directions and an electroabsorption modulator (EAM) are applied. The EAM is used as a simultaneous receiver as well as transmitter at the remote end of a bi-directional analogue optical fibre link in the UMTS band. On the basis of measurements the distortion performance of the basic dual loop architecture is evaluated A promising alternative problem solution is demonstrated which may also be cost efficient.

In this paper, the performance of the uplink of a WCDMA radio over fibre (RoF) access network during macrodiversity mode is investigated. We propose a novel macrodiversity scheme in the uplink, based on maximum ratio combining (MRC) of the received symbols by different BS receivers of a WCDMA mobile cellular system with RoF. Our simulation results demonstrate that, for a given service, the coverage efficiency increased by 19%-23% (depending on the channel model and the mobile speed) in the case of MRC as compared to selection combining (SC).