Impact of the energy-based and location-based LEACH secondary cluster aggregation on WSN lifetime

The improvement of sensor networks’ lifetime has been a major research challenge in recent years. This is because sensor nodes are battery powered and may be difficult to replace when deployed. Low energy adaptive clustering hierarchical (LEACH) routing protocol was proposed to prolong sensor nodes lifetime by dividing the network into clusters. In each cluster, a cluster head (CH) node receives and aggregates data from other nodes. However, CH nodes in LEACH are randomly elected which leads to a rapid loss of network energy. This energy loss occurs when the CH has a low energy level or when it is far from the BS. LEACH with two level cluster head (LEACH-TLCH) protocol deploys a secondary cluster head (2CH) to relieve the cluster head burden in these circumstances. However, in LEACH-TLCH the optimal distance of CH to base station (BS), and the choicest CH energy level for the 2CH to be deployed for achieving an optimal network lifetime was not considered. After a survey of related literature, we improved on LEACH-TLCH by investigating the conditions set to deploy the 2CH for an optimal network lifetime. Experiments were conducted to indicate how the 2CH impacts on the network at different CH energy levels and (or) CH distance to BS. This, is referred to as factor-based LEACH (FLEACH). Investigations in FLEACH show that as CHs gets farther from the BS, the use of a 2CH extends the network lifetime. Similarly, an increased lifetime also results as the CH energy decreases when the 2CH is deployed. We further propose FLEACH-E which uses a deterministic CH selection with the deployment of 2CH from the outset of network operation. Results show an improved performance over existing state-of-the-art homogeneous routing protocols

Machine-to-machine communication: an overview of opportunities

The envisioned capability of machine devices to autonomously communicate in the future Internet of Things (IoT) has brought considerable attention to machine-to-machine (M2M) communication in recent years. This paradigm has applications in homes, safety, transport, health, and industry. As an active focus of research, there are interesting open questions on several of its aspects, which we aim to capture in this paper. Accompanied by an attempted classification of existing surveys on M2M, we propose a followable exposition on the challenges and open research opportunities that embrace the diverse facets of M2M communication

Relay-assisted D2D underlay cellular network analysis using stochastic geometry:overview and future directions

Device-to-Device (D2D) communication is one of the enabling technologies for meeting the capacity requirements of the fifth-generation wireless systems (5G). It has diverse applications in traffic offloading, disaster management and content sharing, to mention a few. The network coverage and capacity further improve when relays are introduced to D2D communication. However, the interference becomes more severe since these devices also share resources with the traditional cellular users in the underlay. To take the benefits and avert the drawbacks of this spectrum sharing scenario, analytical tools capable of revealing the mathematical relationships among pertinent network design parameters are needed. This brings stochastic geometry (SG) into the picture. With SG-based analyses, designers can model concepts to understand, provide insights, and address the problems of spectrum sharing in relay-assisted D2D communication. Some of the key metrics of particular interest to network designers are the transmission capacity and spectral efficiency of D2D communication, as they reveal the performance gains and quantify the level of interference within the network. These enable them to properly correlate relevant cause-and-effect relationships before wealth and time are invested in network implementation. Despite the studies on the analysis of relay-assisted D2D underlay cellular networks using SG in recent years, there is no available survey material where researchers can find models, assumptions, key results and derived lessons to further comprehend this area and open up new research lines. This motivates the presentation of this paper which in addition to the aforementioned, gives elaborate discussions on promising areas for future research with respect to the recent advancements in D2D communication and SG research

A primer on design aspects, recent advances, and challenges in cellular device-to-device communication

Device-to-Device (D2D) communication is one of the technologies on the spotlight for enhancing the cellular network performance towards the fifth generation wireless systems. It has diverse potentials to cater for both critical and non-critical applications. For example, timely information dissemination can be achieved during disasters using D2D communication. Also, content sharing and real-time applications can be effectively facilitated. Recently, new applications and technologies are beginning to embrace D2D to further improve their performance in terms of spectral efficiency, latency, and energy efficiency. However, this is not bereft of technical challenges due to the peculiar limitations of traditional D2D communication such as interference. In this paper, we focus on techniques for managing these challenges with regards to mode selection, power control, and resource allocation. As compared with other contemporary works on this subject, we discuss these issues in line with some of the most recent research trends. In addition, we compile pertinent design considerations of D2D discussed in literature while extracting new patterns to familiarize readers with applications, models, methods and metrics studied lately. Furthermore, we highlight and classify some of the key challenges of D2D communication with respect to current and future generation cellular technologies, giving a comprehensive outlook of new research problems recently identified in this area

Stochastic geometry-based analysis of relay-assisted spectrum sharing future generation wireless networks

Many technologies are set to revolutionize the efficiency of humans and devices communication. Three of the trending technologies envisaged to provide huge prospects towards the realization of the fifth-generation cellular systems are machine-to-machine (M2M) communication, device-to-device (D2D) communication and cognitive radio networks (CRNs). M2M facilitates the autonomous communication of smart devices while D2D facilitates direct connectivity between devices in proximity. Cognitive radio aids effective utilization of wireless spectrum as cognitive devices could opportunistically access the spectrum of licensed users. Similarly, relays improve the transmission coverage between nodes which in turn reduces the outage probability (OP) and increases the transmission capacity (TC) of the spectrum sharing network. These metrics can be effectively studied using stochastic geometry (SG): a mathematical tool for deriving insights into the performance of wireless networks of different spatial configurations. Motivated by these, this thesis is aimed at addressing three of the research gaps related to spectrum sharing systems (D2D and CRNs) assisted by relays using SG. The coexistence of a massive number of machine-type devices (MTDs) with D2D and cellular users is set to heighten the interference levels within the cellular architecture. On the other hand, D2D devices would require relays whenever they are farther apart to improve the outage performance. However, limited battery or the non-altruistic nature of certain users may deter them from helping other users to relay data. Motivated by the recent specifications of MTD devices, the first contribution in this thesis conceptualizes that MTDs can relay data for D2D devices that are not in proximity. In this context, a probabilistic model is introduced for the availability of M2M devices. Thorough investigations are made on the TC, TC gains and trade-offs involved for both underlay and D2D-overlay modes. Using SG, the successful transmission probabilities for all associated links are derived to determine the TCs in these scenarios and present computable expressions for the TC gains achieved. Furthermore, an exposition is provided on how the density and transmit power of MTDs in the network affect the D2D TC performance. Results show that the deployment of MTD devices as relays improves the TC as compared to when only traditional RNs are used. Similarly, higher peak TCs are achieved at 23dB MTD transmit power. Overall, a lower transmit power (15dB) yields better performance. Thus, high MTD density can be leveraged to improve the D2D TC when so many D2D transmissions occur within the system and when these devices are farther apart. The literature on the performance analysis of energy harvesting cognitive radio networks focused on a dual and multi-hop secondary architecture. Also, the available literature on a multi-hop primary architecture was not studied in the context of radio frequency energy harvesting which makes the impact of a multi-hop primary network on the outage performance of a dual-hop energy harvesting CRN largely unknown. Thus, the second contribution in this thesis exploits SG and the advancements in wireless energy harvesting to develop a framework for the outage probability analysis of energy harvesting underlay CRNs. In this model, #-hop primary users are equipped with constant energy source while secondary users harvest energy from the transmissions of primary devices. The transmit power of secondary users is regulated to ensure it does not violate the target end-to-end OP constraint of the #-hop primary network. Potential relays that have harvested sufficient energy are eligible to relay data for other secondary users within the network. This model reveals the impact of the number of primary hops on the relay selection region and harvested energy (which is generally unknown). Also, an expression for the total outage probability which encapsulates the impact of N-primary hops is derived. The impacts of other relevant parameters on the outage probability are shown in detail. Results show that the multi-hop primary network reduces the secondary outage probability by regulating the number of transmitting energy harvesting relays within the network. Interference cancellation has long been known as an effective approach to reducing the impact of interference in wireless networks. However, the interplay between interference cancellation and energy harvesting and how both can be used within the same architecture to improve the outage performance in cognitive radio networks is unknown. This motivates the third contribution where interference cancellation is incorporated in the outage analysis of a Poisson distributed wireless energy harvesting cognitive relay network. Based on a predefined interference threshold, devices within the primary network are assumed to be able to cancel a fraction of the strongest interferers in the entire network. To achieve this, the coefficient of cancellation is adapted into the SG analysis to reduce the level of interference. The rationale is to further help the secondary network to meet up with the primary outage constraint by reducing some of the interference experienced by primary receivers. Analytical results show that this significantly reduces the secondary OP which in turn improves the network performance based on a set cancellation threshold and residual interference power. However, this is at the cost of reducing the energy harvesting success probability of the relays within the secondary network which depends on the primary density as interference from such devices would be cancelled

Outage minimization of energy harvesting-based relay-assisted random underlay cognitive radio networks with interference cancellation

This paper incorporates interference cancellation in the outage analysis of a wireless energy harvesting cognitive relay network. Based on an interference threshold, primary receivers are assumed to be able to cancel a fraction of the strongest interferers in the primary network which often dominates the total interference. To achieve this, the coefficient of cancellation is adapted into the analysis to reduce the level of interference. The rationale is to improve the successful transmission probability of the primary network by cancelling interference at its receivers. Interestingly, this reduces the overhead incurred by the secondary network to guarantee the primary outage constraint. In this work, the optimal relay selection range is derived and deployed to minimize the secondary outage probability. Analytical results show that this approach can be used to significantly reduce the secondary outage probability which in turn improves the network performance. However, this is at the cost of reducing the energy harvesting success probability of the relays within the secondary network

A Survey of Sybil Attack Countermeasures in Underwater Sensor and Acoustic Networks

Underwater sensor and acoustic networks have several unique applications including water quality and ocean life monitoring, as well as ocean navigation and exploration. They also have peculiar physical layer characteristics with respect to operating frequency and attenuation which makes them different from terrestrial wireless sensor communication. Thus, coupled with their large cost of deployment and sensitivity, they are highly vulnerable to security attacks. For instance, a Sybil node could pretend to be at several other locations in the sparse network simultaneously, thereby deceiving legitimate nodes and infringing on the security of transmitted information. Over the last few years, researchers have studied means of preventing, detecting, and mitigating Sybil attacks for safe underwater communication under different assumptions and architectural setups. However, to our knowledge, these efforts have been scattered in the literature and concrete lessons have not been drawn from these efforts via a survey/review on this subject towards achieving safe underwater communication. This motivates the presentation of this paper that provides an exposition of the academic discussion on the solutions for addressing Sybil attacks in underwater wireless communication, with respect to attack prevention, detection and mitigation while identifying some of their limitations. Similarly, proposed methods and technical aspects peculiar to these works are identified, and a wide range of challenges, opportunities, and recommendations are provided

A primer on design aspects and recent advances in shufï‚e exchange multistage interconnection networks

Interconnection networks provide an effective means by which components of a system such as processors and memory modules communicate to provide reliable connectivity. This facilitates the realization of a highly efficient network design suitable for computational-intensive applications. Particularly, the use of multistage interconnection networks has unique advantages as the addition of extra stages helps to improve the network performance. However, this comes with challenges and trade-offs, which motivates researchers to explore various design options and architectural models to improve on its performance. A particular class of these networks is shuffle exchange network (SEN) which involves a symmetric N-input and N-output architecture built in stages of N/2 switching elements each. This paper presents recent advances in multistage interconnection networks with emphasis on SENs while discussing pertinent issues related to its design aspects, and taking lessons from the past and current literature. To achieve this objective, applications, motivating factors, architectures, shuffle exchange networks, and some of the performance evaluation techniques as well as their merits and demerits are discussed. Then, to capture the latest research trends in this area not covered in contemporary literature, this paper reviews very recent advancements in shuffle exchange multistage interconnection networks within the last few years and provides design guidelines as well as recommendations for future consideration

Age of Information minimization in UAV-aided data collection for WSN and IoT applications: A systematic review

The use of unmanned aerial vehicles (UAVs) for data gathering in wireless sensor networks (WSNs) and Internet of Things (IoT) applications has significantly gained interest in recent years. This shift is mainly attributed to the fast mobility and manoeuvrability of UAVs to deliver sensed data (by sensors and/or IoT devices) in remote, rural, or urban areas to the required destination (such as base stations or data centers). Age of Information (AoI) is a recent metric that measures the degree of freshness of information collected in data gathering applications, and in this context, data sensed by terrestrial sensing devices and transported by the UAV. Many researchers have thus focused on techniques to minimize AoI, mainly using machine learning and optimization methods. The research in this area is fast-growing, and some of the models studied are becoming more fine-grained, thus increasing the need for a comprehensive review of the proposed solutions, peculiar aspects, and diverse assumptions to draw lessons, identify challenges, and map out future considerations. This motivates the comprehensive study conducted in this paper, whereby 45 articles were meticulously selected from the Scopus database and systematically filtered to the 20 most relevant articles on AoI minimization for UAV-assisted data gathering in WSN and IoT applications. This paper provides a comprehensive review of problems and problem-solving solutions, detailed assumptions, algorithms, constraints, joint optimization objectives, metrics, and influencing factors on information freshness in UAV-assisted WSN/IoT. Optimal design of UAV trajectory, efficient UAV and sensor node/IoT device scheduling, and improved UAV energy source acquisition were also identified as some of the most preponderant themes surrounding AoI minimization. Consequently, a comprehensive discussion on AoI-optimal trajectory designs in different WSN/IoT architectural setups, namely clustered and non-clustered environments, has been presented. The outcomes of this systematic review include the categorization of the issues and proposed solutions, as well as tools and methods, joint optimization approaches, metrics, and UAV/SN-related assumptions from the reviewed articles. Finally, lessons learned, design considerations, challenges, and future directions have also been discussed