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Recently, cognitive radio sensor networks (CRSN) have evolved as a result of the introduction of cognitive capabilities to conventional wireless sensor networks. In most CRSN designs, secondary users and/or sensor nodes are permitted, under certain constraints, to use the limited resources of a primary network. One major challenge with CRSN is how to optimally appropriate and use the limited resources available in driving their communication demands. To overcome this challenge, in this paper, we develop a resource allocation (RA) model that is capable of achieving a target quality of service (QoS) demand for the heterogeneous CRSN, despite the huge resource constraints imposed on the network. The RA problem developed is a complex optimisation problem. We analyse and solve the complex RA problem using the optimisation approaches of integer linear programming, Lagrangian duality and by a heuristic. We then study the performance of the RA model for the different solution approaches investigated. The results obtained are used to establish the optimality-complexity trade-off, which is a critical criterion for QoS decision-making in practical CRSN applications.

The ever-increasing spectrum demand in wireless communication networks like Sensor Network has routed to the development of Cognitive Radio Sensor Networks (CRSN). Securing the CRSN against the Pri...

Cognitive Radio Sensor Networks (CRSNs) have become an integral portion of the new generation of smart Wireless Sensor Networks (WSNs) technology. Moreover, efficient clustering and routing could enhance the network performance by taking into account the stability and connectivity of the network that expands the network's lifetime. In this paper, we propose a scheme that aims to construct an energy-efficient clustering for CRSNs through saving the intra-communication energy between nodes into the cluster, in addition to the inter-communication energy between Cluster Head (CH) nodes to the Base Station (BS). The scheme utilizes evaluation criteria to define the CH node for each cluster by calculating a weight value for each node, and depending on the maximum weight value for nodes, the CH is picked. Moreover, to establish a route between CHs, we consider common channels between them plus the shortest distance from cluster heads to the sink. In this way, clustering and routing could enhance the network performance and extend the lifetime. To corroborate the proposed scheme, extensive simulations in MATLAB were carried out and the results of the simulation showed the superiority of the proposed technique over other algorithms in terms of the network’s lifetime.

Green communication with emerging future technologies like the Internet of things (IoT), Industry 4.0, and Industrial IoT (IIoT) pushes modern society towards a smarter paradigm. Thus, for its deployment and implementation in the society, the involving Wireless Sensor Networks (WSNs) and its computing technologies should be designed in an energy-efficient way. In this paper, we propose an energy-efficient cooperative technique for Cognitive Radio Sensor Networks (CRSNs) for IoT applications. In this type of applications, there is a constant need for inter and intra-cluster WSNs communication. Also, the active nodes need power based on the application rather than and uniform distributing power to all the nodes or randomly distribution (conventional). The work addresses the issue by proposing a hybrid approach of using Vector Quantization (VQ) and Hierarchical Maximum Likelihood (HML) to allocate power only for the active Secondary User (SU) nodes. The proposed work illustrates a fast computation towards cluster formation and Cluster Head (CH) communication between two clusters for IoT applications with CRSNs. The work is presented with mathematical analysis and simulation results along with the comparison of existing techniques.

A cognitive radio sensor network (CRSN) is a wireless sensor network (WSN) with cognitive radio capabilities that ensures efficient spectrum management. In general, CRSNs facilitate the combined use of unused licensed frequency spectrum and unlicensed frequency spectrum. Prolonging network lifetime is very important in the design of a medium access control (MAC) protocol in CRSNs because additional energy for spectrum sensing and dynamic spectrum access is required, in comparison to conventional WSNs. In this paper, an energy-aware robust MAC (ER-MAC) protocol for prolonging network lifetime in CRSNs is proposed, in which the network lifetime is increased by reducing collisions and adjusting sensing interval. Furthermore, the number of retransmissions is reduced by utilizing more reliable channels. Simulation results show that the proposed ER-MAC outperforms the conventional protocol in terms of network lifetime.

Cognitive radio sensor network (CRSN) is a new generation of communication systems that wants to solve the overcrowded spectrum utilization of the unlicensed bands. It has combined sensor networks and cognitive radio technology, so it has the challenges of energy restriction of sensors and also dynamic spectrum access of the cognitive radio network. On the other hand, considering both of these challenges in the routing protocol plays a basic role in network performance and we can’t apply the routing protocols that have been proposed for wireless sensor networks and cognitive radio networks, separately, in the CRSN. Therefore, this article has tried to provide a new spectrum and energy-aware routing protocol in which the source is able to choose the most stable route in the aspect of node residual energy or spectrum access probability. Not only can considering the nodal residual energy and spectrum access in the route discovery process avoid repetitive link failure, but it also can increase the network lifetime. This protocol has been compared with ESAC, SCR, ERP, and SER. The result of this comparison has shown that our protocol reduces end-to-end delay, control overhead, throughput, and lifetime in comparison to other protocols, especially in small-scale networks. ABSTRAK: Rangkaian sensor radio kognitif (CRSN) adalah generasi baru sistem telekomunikasi bagi menyelesaikan masalah kesesakan pada pemakaian band spektrum tidak berlesen. Ianya adalah kombinasi rangkaian sensor dan teknologi radio kognitif. Oleh itu, ia mempunyai cabaran sekatan tenaga pada sensor dan kemasukan spektrum secara dinamik pada rangkaian radio kognitif. Pada masa sama, dengan mengambil kira kedua-dua cabaran pada protokol rangkaian ini telah memainkan peranan asas pada prestasi rangkaian dan kami tidak boleh mengguna pakai protokol rangkaian yang telah diguna pakai pada rangkaian sensor tanpa wayar dan rangkaian radio kognitif secara asing dalam CRSN. Oleh itu, artikel ini cuba menyediakan spektrum baru dan pengawasan tenaga pada protokol rangkaian, di mana sumber boleh memilih laluan rangkaian yang stabil dengan mengambil kira pada aspek baki tenaga nod atau kebarangkalian akses spektrum. Selain itu, ianya dapat mengelakkan kegagalan laluan berulang juga menambahkan jangka hayat rangkaian. Protokol ini telah dibandingkan dengan ESAC, SCR, ERP dan SER. Perbandingan keputusan menunjukkan protokol ini mengurangkan kelewatan hujung-ke-hujung, mengawal kesesakan, mambaiki jumlah penghantaran dan menambah tempoh hayat berbanding protokol lain, khususnya pada rangkaian skala kecil.

The large-scale deployment of wireless sensor networks is indispensable to the success of Internet of Things. Considering dynamic spectrum access and the limited spectrum resources in cognitive radio sensor networks, sub-Nyquist spectrum sensing based on the modulated wideband converter is introduced. Since the transmission signals are usually modulated by different carrier frequencies, the interested spectrum can be modeled as the multiband signal. Modulated wideband converter (MWC) is an attractive alternative among several sub-Nyquist sampling systems because it has been implemented in practice and the frequency support reconstruction algorithm is the most important part in MWC. However, most existing reconstruction methods require the sparse information, which is difficult to acquire in practical scenarios. In this paper, we propose a blind multiband signal reconstruction method, referred to as the statistics multiple measurement vectors (MMV) iterative algorithm to bypasses the above problem. By exploiting the jointly sparse property of MMV model, the supports can be obtained by statistical analysis for the reconstruction results. Simulation results show that, without the sparse prior, the statistics MMV iterative algorithm can accurately determine the support of the multiband signal in a wide range of signal-to-noise ratio by using various numbers of sampling channels.

Due to dynamic channel availability in cognitive radio sensor networks (CRSNs), clustering protocols are significantly affected. This letter proposes energy coverage efficiency (ECE) metric specifically for clustering protocols in CRSNs, in which network lifetime and effective surveillance capability are for the first time integrated. Simulation results show that ECE can provide a comprehensive evaluation for clustering protocols in CRSNs.

Several studies have focused on multimedia transmission over wireless sensor networks (WSNs). In this paper, we propose a comprehensive and robust model to transmit images over cognitive radio WSNs (CRWSNs). We estimate the spectrum sensing frequency and evaluate its impact on the peak signal‐to‐noise ratio (PSNR). To enhance the PSNR, we attempt to maximize the number of pixels delivered to the receiver. To increase the probability of successful image transmission within the maximum allowed time, we minimize the average number of packets remaining in the send buffer. We use both single‐ and multi‐channel transmissions by focusing on critical transmission events, namely hand‐off (HO), No‐HO, and timeout events. We deploy our advanced updating method, the dynamic parameter updating procedure, to guarantee the dynamic adaptation of model parameters to the events. In addition, we introduce our ranking method, named minimum remaining packet best channel selection, to enable us to rank and select the best channel to improve the system performance. Finally, we show the capability of our proposed image scrambling and filtering approach to achieve noticeable PSNR improvement.

Cognitive radio sensor network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such a system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here the concept of dynamic spectrum access defines the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the primary user (PU) has the license to access the spectrum band. On the other hand, the secondary user (SU) tries to access the unused spectrum efficiently, by not disturbing the PU. Considering that issue, this study introduces a fuzzy genetic based dynamic spectrum allocation (FGDSA) system for deciding spectrum allocation in cognitive radio sensor networks. In detail, the primary objective of the FGDSA system is to increase channel use without causing too much interference to the PU. In order to achieve that, some parameters such as signal interference noise ratio (SINR), bit error rate (BER), available channel bandwidth, SU transmission power, and the SU data rate are used as input variables for the fuzzy based inference mechanism taking place in the FGDSA. After development of the system, a performance analysis was done by comparing some metrics such as channel utilization, signal noise interference ratio, and the channel access delay for fuzzy based inference and the fuzzy genetic based inference that are both performing spectrum allocation. It was observed that the hybrid system of FGDSA outperforms fuzzy system by 2% in channel utilization, by also ensuring 16% less SINR, and 41% less channel access delay. The FGDSA was compared with also some existing spectrum allocation techniques such as edge coloring heuristic (ECH) and clique heuristic algorithm (CHA). It was seen that the FGDSA outperforms both ECH and CHA in average channel utilization, with the rates of 6% and 8%, respectively.

Cognitive radio sensor networks offer a promising means of meeting rapidly expanding demand for wireless sensor network applications in new monitoring and objects tracking fields. Several challenges, particularly in terms of quality of service provisioning, arise because of the inherited capability-limitation of end-sensor nodes. In this article, an efficient resource allocation scheme, improved Pliable Cognitive Medium Access Protocol, is proposed to tackle multilevel of heterogeneity in cognitive radio sensor networks. The first level is the network’s application heterogeneity, and the second level is the heterogeneity of the radio environment. The proposed scheme addresses scheduling and radio channel allocation issues. Allocation-decision making is centralized, whereas spectrum sensing is distributed, thereby increasing efficiency and limiting interference. Despite the limited capabilities of the sensor’s networks, the effectiveness of the proposed scheme also includes increasing the opportunity to utilize a wider range of the radio spectrum. improved Pliable Cognitive Medium Access protocol is quite appropriate for critical communications that gain attention in the next 5G of wireless networks. Simulation results and the comparison of the proposed protocol with other protocols indicate the robust performance of the proposed scheme. The results reveal the significant effectiveness, with only a slight trade-off in terms of complexity.

With the increasing usage of wireless sensor network technologies, their unlicensed bands become overcrowded. To address this challenge, cognitive radio technology with the dynamic spectrum access policy has merged with Wireless Sensor Network to overcome spectrum underutilization. The Cognitive Radio Sensor Network (CRSN) has emerged as a promising solution to overcome spectrum scarcity in a resource-constrained wireless sensor network. In CRSN, TCP has to cope with a new type of packet loss due to the primary users (PU) arrival, known here as a secondary user (SU) blocking loss. In this paper SU blocking loss is modelled by a discrete-time Markov chain. The experimental results are verified using the NS2.

With the increasing worldwide trend in population migration into urban centers, we are beginning to see the emergence of the kinds of mega-cities which were once the stuff of science fiction. It is clear to most urban planners and developers that accommodating the needs of the tens of millions of inhabitants of those megalopolises in an orderly and uninterrupted manner will require the seamless integration of and real-time monitoring and response services for public utilities and transportation systems. Part speculative look into the future of the world’s urban centers, part technical blueprint, this visionary book helps lay the groundwork for the communication networks and services on which tomorrow’s “smart cities” will run. Written by a uniquely well-qualified author team, this book provides detailed insights into the technical requirements for the wireless sensor and actuator networks required to make smart cities a reality.

In this paper, we introduce a novel scheduling mechanism for cognitive radio sensor networks. Our approach aims at defining an optimized time slot and channel assignment that exploits spatial reuse with respect to all types of nodes communications interferences. We identify first all types of nodes conflicts, then, we solve the spatial dependencies by the mean of the Maximum Matching graph theory problem. We use after a First-price sealed-bid auction (FPSB) to perform channels and time slots assignment to completely independent cognitive sensor nodes. Our approach outperforms existing solution for scheduling in CRSN, by reducing the total length of communications and maximizing the stability factor.

In order to solve the problem of spectrum scarcity in wireless sensor networks, cognitive radio technology can be introduced into wireless sensor networks, giving rising to cognitive radio sensor networks. Delay-sensitive data applications in cognitive radio sensor networks require efficient real-time communication. Opportunistic pipeline routing is a potential technology to reduce the delay, which can use nodes outside the main forwarding path forward data opportunistically when the transmission fails. However, the energy efficiency of cognitive radio sensor networks with opportunistic pipeline routing is low, and the data transmission delay can be further optimized. In view of this situation, we propose the delay optimal opportunistic pipeline routing scheme named Variable Duty Cycle for Opportunistic Pipeline Routing (VDCOPR). In the Variable Duty Cycle for Opportunistic Pipeline Routing scheme, the nodes employ high duty cycle in the area far from the sink, and low duty cycle in the area near to the sink, which can achieve the balance of energy consumption and reduce the data transmission delay while not affecting network lifetime. The theoretical analysis and experimental results show that, compared with previous opportunistic pipeline routing, energy consumption of network is relatively balanced and the data transmission delay can be reduced by 36.6% in the Variable Duty Cycle for Opportunistic Pipeline Routing scheme.

In recent year, the most emerging and growing field of research and development is “Internet of Things” (IoT). This is due to advancement in wireless sensor network (WSN) which operate in the unlicensed industrial, scientific and medical (ISM) spectrum band. However, many wireless technologies operate in the same unlicensed spectrum, make it overcrowded and hence resulted in spectrum scarcity among those bands, the performance of WSN will degrade as their popularity increases. According to FCC report, most of the licensed spectrum is underutilized, sharing of underutilized licensed spectrum among unlicensed devices is a promising solution to the spectrum scarcity issue. Cognitive Radio (CR) is one of the capable technology that allows sensor nodes (as a Secondary Users (SUs)) to detect and use the underutilized licensed spectrum temporarily when Primary Users (PUs) not using it. With recent advances in Cognitive Radio (CR) technology, possible to apply the Dynamic Spectrum Access (DSA) model in WSNs to get access to underutilized licensed spectrum, possibly with better propagation characteristics, but as the existing protocols and algorithms developed for CRNs and WSNs are not directly applicable to CR-based WSNs and required new protocols. In this paper, we present a survey on the novel design of CR-based MAC, identify the main advantages and challenges of using CR technology, and compare the different method of improving energy efficiency. We believe that CR-WSN is the next-generation WSN. In this paper, we also discussed the open issues to motivate new research interest in this field.

Wireless sensors equipped with cognitive radio, i.e., cognitive radio sensor networks (CRSN), can access the spectrum in an opportunistic manner and coexist with licensed users to mitigate the crowded spectrum problem and provide ubiquitous remote event monitoring and tracking for cyber-physical systems. In this paper, a novel transport layer protocol for CRSN, spectrum-aware energy-adaptive reliable transport protocol is presented to enable energy-adaptive collaborative event sensing in spectrum-scarce cyber-physical systems. To the best of our knowledge, this is the first attempt to specifically devise a reliable event transport scheme for CRSN., Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences Distinguished Young Scientist Award Program

Cognitive radio sensor network (CRSN) is an intelligent and reasonable combination of cognitive radio technology and wireless sensor networks. It poses significant challenges to the design of topology maintenance techniques due to dynamic primary-user activities, which in turn decreases the data delivery performance of the network as well as it's lifetime. This paper aims to provide a solution to the CRSN clustering and routing problem using an energy aware event-driven routing protocol (ERP) for CRSN. Upon detection of an event, the ERP determines eligible nodes for clustering according to local positions of CRSN nodes between the event and the sink and their residual energy levels. Cluster-heads are selected from the eligible nodes according to their residual energy values, available channels, neighbors and distance to the sink. In ERP, cluster formation is based on relative spectrum awareness such that channels with lower primary user appearance probability are selected as common data channels for clusters. For data routing, ERP employs hop-by-hop data forwarding approach through the CHs and primary/secondary gateways towards the sink. Through extensive simulations, we demonstrate that the proposed ERP provides with better network performances compared to those of the state-of-the-art protocols under a dynamic spectrum-aware data transmission environment.

The determination of optimal packet size (OPS) for a cognitive radio-assisted sensor networks (CRSNs) architecture is non-trivial. State of the art in this area describes various complex techniques to determine OPS for CRSNs. However, it is observed that under high interference from the surrounding users, it is not possible to determine a feasible OPS of data transmission under the simple point-to-point CRSN topology. This is contributed primarily to the peak transmit power constraint of the cognitive nodes. To address this specific challenge, this paper proposes a multiple-input multiple output-based CRSNs (MIMO-CRSNs) architecture for futuristic technologies, such as Internet of Things and machine-to-machine communications. A joint optimization problem is formulated, considering network constraints, such as the overall end-to-end latency, interference duration caused to the non-cognitive users, average BER, and transmit power. We propose our Algorithm 1 based on the generic exhaustive search technique to solve the optimization problem. Furthermore, a low complexity suboptimal Algorithm 2 based on solving classical Karush–Kuhn–Tucker conditions is proposed. These algorithms for MIMO-CRSNs are implemented in conjunction with two different channel access schemes. These channel access schemes are time-slotted distributed cognitive medium access control denoted as MIMO-DTS-CMAC and CSMA/CA-assisted centralized common control channel-based cognitive medium access control denoted as MIMO-CC-CMAC. Simulations reveal that the proposed MIMO-CRSN outperforms the conventional point-to-point CRSN in terms of overall energy consumption. Moreover, the proposed Algorithm 1 and Algorithm 2 show a perfect match, and the implementation complexity of Algorithm 2 is less than Algorithm 1 . Algorithm 1 takes almost 680 ms to execute and provides OPS value for a given number of users, whereas Algorithm 2 takes 4–5 ms on average to find the OPS for the proposed MIMO-CRSN framework.

Cognitive radio sensor networks (CRSNs) is the state-of-the-art communication paradigm for power constrained short range data communication. It is one of the potential technologies adopted for Internet of Things (IoT) and other futuristic machine-to-machine-based applications. Many of these applications are power constrained and delay sensitive. Therefore, CRSN architecture must be coupled with different adaptive and robust communication schemes to take care of the delay and energy efficiency at the same time. Considering the tradeoff that exists in terms of energy efficiency and overhead delay for a given data packet length, it is proposed to transmit the physical layer payload with an optimal packet size (OPS) depending on the network condition. Furthermore, due to the cognitive feature of CRSN architecture overhead energy consumption due to channel sensing and channel handoff plays a critical role. Based on the above premises, in this paper, we propose a heuristic exhaustive search-based Algorithm-1 and a computationally efficient suboptimal low complexity Karuh-Kuhn-Tucker (KKT) condition-based Algorithm-2 to determine the OPS in CRSN architecture using variable rate m-QAM modulation. The proposed algorithms are implemented along with two main cognitive radio assisted channel access strategies based on distributed time slotted-cognitive medium access control (DTS-CMAC) and centralized common control channel-based cognitive medium access control (CC-CMAC) and their performances are compared. The simulation results reveal that proposed Algorithm-2 outperforms Algorithm-1 by a significant margin in terms of its implementation time. For the exhaustive search-based Algorithm-1 the average time consumed to determine OPS for a given number of cognitive users is 1.2 s, while for KKT-based Algorithm-2, it is of the order of 5-10 ms. CC-CMAC with OPS is most efficient in terms of overall energy consumption but incurs more delay as compared to DTS-CMAC with OPS scheme.

A smart grid has recently gained significant attention as it is an important direction of power system advancement. The integration of renewable energy (RE) resources to the power system and the reduction of energy losses need an efficient and low-cost communication infrastructure. Cognitive radio sensor networks (CRSN) can be integrated in a smart grid to meet these challenges. CRSN is a new paradigm of research where the best of wireless sensor networks (WSN) and cognitive radios (CR) is combined. The sensor networks monitor a physical parameter and the measures value is transmitted using the cognitive radio. Thus, CRSN can be used for realizing the sensing and communication part in a smart grid network. In this paper, a smart grid network is proposed using CRSN for implementing it in the remote areas of Pakistan. The service coverage map is taken from the Pakistan Telecommunication Authority (PTA) website that regulates the spectrum band in Pakistan. This can be used in developing countries to realize a cost effective smart grid for integrating the renewable resources and for reducing energy losses.

Communication requirements for cognitive radio sensor networks (CRSN) necessitate addressing the problems posed by dynamic spectrum access (DSA) in an inherently resource-constrained sensor networks regime. In this paper, arising challenges for reliability and congestion control due to incorporation of cognitive radio capability into sensor networks are investigated along with the open research issues. Impact of DSA, i.e., activity of licensed users, intermittent spectrum sensing and spectrum handoff functionalities based on spectrum availability, on the performance of the existing transport protocols are inspected. The objective of this paper is to point out the urgent need for a novel reliability and congestion control mechanism for CRSN. To this end. CRSN challenges for transport layer are revealed and simulation experiments are performed to demonstrate the performance of the existing transport protocols in CRSN., Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences (Turkish Academy of Sciences (TÜBA)-GEBIP)

In wireless sensor networks, time synchronization is an important issue for all nodes to have a unified time. The wireless sensor network nodes should cooperatively adjust their local time according to certain distributed synchronization algorithms to achieve global time synchronization. Conventionally, it is assumed that all nodes in the network are cooperative and well-functioned in the synchronization process. However, in cognitive radio wireless sensor networks, the global time synchronization process among secondary users is prone to fail because the communication process for exchanging synchronization reference may be frequently interrupted by the primary users. The anomaly nodes that failed to synchronize will significantly affect the global convergence performance of the synchronization algorithm. This article proposes an anomaly node detection method for distributed time synchronization algorithm in cognitive radio sensor networks. The proposed method adopts the statistical linear correlation analysis approach to detect anomaly nodes through the historical time synchronization information stored in local nodes. Simulation results show that the proposed method can effectively improve the robustness of the synchronization algorithm in distributed cognitive radio sensor networks.

Technological advances have led to the emergence of wireless sensor nodes in wireless networks. Sensor nodes are usually battery powered and hence have strict energy constraints. As a result, energy conservation is very important in the wireless sensor network protocol design and the limited power resources are the biggest challenge in wireless network channels. Link adaptation techniques improve the link quality by adjusting medium access control (MAC) parameters such as frame size, data rate, and sleep time, thereby improving energy efficiency. In this paper we present an adaptive packet size strategy for energy efficient wireless sensor networks. The main goal is to reduce power consumption and extend the whole network life. In order to achieve this goal, the paper introduces the concept of a bounded MAB to find the optimal packet size to transfer by formulating different packet sizes for different arms under the channel condition. At the same time, in achieve fast convergence, we consider the bandwidth evaluation according to ACK. The experiment shows that the packet size is adaptive when the channel quality changes and our algorithm can obtain the optimal packet size. We observe that the MAB packet size adaptation scheme achieves the best energy efficiency across the whole simulation duration in comparison with the fixed frame size scheme, the random packet size and the extended Kalman filter (EKF).

A recent investigation on the medium access control (MAC) layer in cognitive radio networks (CRNs) proposed the primary packet relaying by the secondary node maintaining an extra queue used for this particular addable functionality. Nevertheless, relaying of primary packets may introduce delays on secondary packets called secondary delay and may require an additional power budget to forward the primary packets. Power budget is particularly crucial when a type of sensor network is deployed using devices of limited power resources. In this paper, admission control is employed to efficiently manage this packet-wise relaying process in cognitive radio sensor networks (CRSNs). To be specific, we assume a cognitive packet-relaying scenario with two pairs of primary and secondary users, i.e., transmitter and receiver. We analyze and formulate the secondary delay and the required power budget of the secondary sensor node in relation to the acceptance factor (i.e., admission control parameter) that indicates whether the primary packets are admitted for relaying or not. Having defined the above, we present a tradeoff between the secondary delay and the required power budget by tuning the acceptance factor, which can be tailored to specific chosen values. Based on this behavior, we formulate an optimization problem to minimize the secondary delay over the admission control parameter subject to a limit on the required power budget. Additionally, the constraints related to the stabilities of all individual queues at the primary and secondary networks are taken into account in the proposed optimization problem, due to their interdependence relations. The solution of this problem is provided using iterative decomposition methods, i.e., dual and primal decompositions, using Lagrange multipliers that simplify the original complicated problem and result in a final equivalent dual problem that includes the initial Karush–Kuhn–Tucker (KKT) conditions. We obtain the optimal acceptance factor, while in addition, we highlight the opportunities for extra delay minimization that is provided by relaxing the initial constraints through changing the values of the Lagrange multipliers. Finally, we present the behavior of the secondary delay, assuming infinite and finite queues and assessing thereby the overflow and blocking probabilities, respectively.

© 2016, IGI Global. All rights reserved. Sensing coverage of a field of interest and connectivity are two very important performance measures in Wireless Sensor Networks (WSNs). Existing design methodologies and protocols for enhanced field sensing coverage and connectivity in WSNs are not directly applicable to Cognitive Radio Sensor Networks (CRSNs) due to their cognitive nature. In this chapter, the authors first review sensing coverage and connectivity models for traditional WSNs. Then, they propose novel approaches for sensing coverage and connectivity establishment in CRSN, benefiting from useful existing models from WSN and Cognitive Radio Ad Hoc Networks (CRAHNs). Proposed approaches span a wide variety of CRSN requirements and also point out open research problems in the field to guarantee sufficient sensing coverage quality and connectivity in CRSN.

In Cognitive Radio sensor networks, a pair of Cognitive Radio (CR) users wishing to communicate should first agree on a specific channel called control channel. Communication rendezvous is used to establish a control channel between CR users. Channel Hopping (CH) protocol is a sequence-based approach that provides an effective method for implementing rendezvous without relying on a Common Control Channel (CCC). In this approach, all CR users hop to the same rendezvous channel and hence this channel will serve as a control channel between them. In this paper, we propose two Channel Hopping Sequences (CHS) to establish a link in CR sensor networks with and without the assumption of global clock synchronization. Our schemes provide successful communication rendezvous within a bounded time interval. Theoretical analysis and simulation results showed that both schemes outperform the existing schemes used for similar purpose in terms of many performance criteria.

Recently, significant growth in the applications of the wireless sensor networks (WSNs) operating in unlicensed spectrum bands has been made. In the meantime, existing unlicensed bands are becoming congested and overcrowded. On the other hand, Cognitive Radio (CR) technology has been proposed as the key technology for future wireless communication that exploits dynamic spectrum access strategies. Since this offers more flexible way to utilize the wireless spectrum than traditional radio technology based on a fixed spectrum access policy, it is thought that the key feature of cognitive radio i.e. dynamic spectrum access can be applied in WSNs to access the underutilized spectrum bands to transmit their readings in an opportunistic manner to the next hops and finally to the sink. In this paper, we discuss the basic responsibilities of MAC layer and its functionalities in cognitive radio sensor networks (CRSN). We mainly focus on investigating the MAC layer issues while realizing the cognitive capability into wireless sensor networks.

Due to the bursty nature of video traffic, streaming video in traditional Wireless Sensor Networks (WSN) is usually faced with distortion largely as a result of packet loss. Although the bandwidth aggregation characteristic of Cognitive Radio Sensor Networks promises to cushion this effect, this method will not be much different with the strategy of increasing throughput as has been employed in traditional WSN. Thus, the problem is yet to be properly addressed. More so, the fact that the most important of video frames (I-Frames) constitute more than half the streaming data (in low-motion streams) increases the possibility of distortion, which cannot be mitigated by solely increasing throughput. Online Priority Aware (OPRA) Streaming provides a detailed and simple framework for effective streaming that brings the important end-to-end distortion metrics to bear, directly on the in-network processing nodes. The algorithm selectively drops packets in the in-network processing nodes to maximize a defined Local Quality Index in order to protect end-to-end quality of experience (QoE). Preliminary results show its simplicity, its ability to deliver more QoE high priority packets to the sink and the satisfactory effects of the incurred overhead.

This paper studies a novel channel access scheme for delay-sensitive multi-hop cognitive radio sensor networks (CRSNs) with fixed decode-and-forward relaying. We first formulate a two-dimensional spatial-temporal opportunity model wherein free and sharing opportunities are defined, and then propose a joint spatial-temporal access scheme (JSTAS) to achieve successive channel access for continuous data transmission. By spatial sensing and temporal sensing, the cognitive sensors with JSTAS control the transmission powers by fully considering their maximum transmission powers, the interference constraints of multiple primary receivers and the interference from one primary transmitter. To evaluate JSTAS, we derive the closed-form outage probability under Rayleigh fading channels and make comparisons among five different schemes. Simulation results demonstrate that JSTAS has better outage performance than that of pure spatial or temporal access scheme under all considered scenarios.

Spectrum sharing is an important topic in cognitive radio sensor networks (CRSNs). Bio-inspired consensus-based schemes can provide lightweight and efficient solutions to ensure spectrum sharing fairness in CRSNs. In this paper, in order to achieve the defined spectrum sharing fairness, we propose two schemes called the local control scheme for unbiased fairness (LCS-UF) and the local control scheme for max-min fairness (LCS-MMF). With the local observation and control using surrounding spectrum-related information, an individual cognitive sensor node can effectively perform the spectrum sharing with LCS-UF and LCS-MMF. From simulation results, the use of proposed schemes shows low complexity and effectiveness for spectrum sharing processes in randomly deployed CRSNs.

Multimedia and delay-sensitive data applications in cognitive radio sensor networks (CRSN) require efficient real-time communication and dynamic spectrum access (DSA) capabilities. This requirement poses emerging problems to be addressed in inherently resource-constrained sensor networks, and needs investigation of CRSN challenges with real-time communication requirements. In this paper, the main design challenges and principles for multimedia and delay-sensitive data transport in CRSN are introduced. The existing transport protocols and algorithms devised for cognitive radio ad hoc networks and wireless sensor networks (WSN) are explored from the perspective of CRSN paradigm. Specifically, the challenges for real-time transport in CRSN are investigated in different spectrum environments of smart grid, e.g., 500 kV substation, main power room and underground network transformer vaults. Open research issues for the realization of energy-efficient and real-time transport in CRSN are also presented. Overall, the performance evaluations provide valuable insights about real-time transport in CRSN and guide design decisions and trade-offs for CRSN applications in smart electric power grid., European Union FP7 Marie Curie International Reintegration Grant (IRG); Scientific and Technological Research Council of Turkey (TÜBİTAK); Turkish National Academy of Sciences Distinguished Young Scientist Award Program (Turkish Academy of Sciences (TÜBA)-GEBIP)

Properly modeling the aggregated interferences from the entire cognitive radio sensor networks is necessary to effectively protect these incumbent users. In this paper, we present a prominent interference avoiding mechanism based on a mathematical hybrid modeling for the cumulative interference to the primary network as well as the probe link from secondary networks. For the purpose of the paper, we consider the interference temperature constraints and secondary network's Quality-of-Service requirements, as well as obtain the optimal transmitter power for maximizing the system transmission rate.

Traditional wireless sensor networks (WSNs) working in the license-free spectrum suffer from uncontrolled interference as the license-free spectrum becomes increasingly crowded. A WSN based on cognitive radios can potentially provide data transmissions with quality of service, while avoiding the high cost for accessing the licensed spectrum and uncontrolled interference in the license-free spectrum. Our previous works have studied delay performance of constant bit rate traffic in a cognitive radio sensor network (CRSN). In this paper we study the delay performance of random traffic with burst arrivals in the network. We derive the average delay for transmitting the random traffic using different channel sensing mechanisms, and verify the results using computer simulation. Our results show that satisfactory latency performance can be provided in the CRSN.

With the exciting progress of wireless sensor networks (WSN), a major difficulty will be faced in that the limited frequency spectrum, even with the industrial, scientific and medical (ISM) bands, will be extremely crowded. Moreover purchasing spectrum rights with millions or billions of dollars is unreasonable under an emphasis on low-cost to WSN. Thus an alternate method based on the concept of Cognitive Radio is explored to capture spectrum for WSN. A cooperative energy detection technique is introduced. The probabilities of detection of proposed technique are evaluated over some classical fading channels. The quantization case is also considered for practicality. The simulation results show that the quantization case exhibits almost comparable performance with the optimum Neyman-Pearson detector, while it has much less overhead.