Cooperative Sensor Networks Research Articles

Cooperative Communication Based Protocols for Underwater Wireless Sensors Networks: A Review.

Underwater wireless sensor networks are gaining popularity since supporting a broad range of applications, both military and civilian. Wireless acoustics is the most widespread technology adopted in underwater networks, the realization of which must face several challenges induced by channel propagation like signal attenuation, multipath and latency. In order to address such issues, the attention of researchers has recently focused on the concept of cooperative communication and networking, borrowed from terrestrial systems and to be conveniently recast in the underwater scenario. In this paper, we present a comprehensive literature review about cooperative underwater wireless sensor networks, investigating how nodes cooperation can be exploited at the different levels of the network protocol stack. Specifically, we review the diversity techniques employable at the physical layer, error and medium access control link layer protocols, and routing strategies defined at the network layer. We also provide numerical results and performance comparisons among the most widespread approaches. Finally, we present the current and future trends in cooperative underwater networks, considering the use of machine learning algorithms to efficiently manage the different aspects of nodes cooperation.

Instantaneous received signal strength-based sensor activation for energy-efficient distributed cooperative sensor networks

In this paper, a network-independent distributed relay sensor (RS) activating method is proposed for energy-efficient cooperative communications using RSs. To achieve this, we introduce a novel metric termed the signal contribution-to-noise contribution ratio and design the required instantaneous received signal strength at RS for each RS to independently determine the activation. Therefore, the proposed RS activation (i.e., adaptive cooperation) is readily enabled without significant signaling overhead in the networks. The numerical results indicated that the proposed RS activation strategy can improve the received signal-to-noise ratio at a destination sensor with fewer active RSs, extending the lifetime of the sensor network.

An optimal cooperative relay selection strategy for delay aware image transmission in large scale multi-radio multi-channel multimedia wireless sensor network

High bit-error rates and high transmission rates are required for the Multimedia Wireless Sensor Networks (MWSN) to transmit high-quality pictures through smart devices. To fully utilize the advantages of the technology known as Multiple-Input Multiple-Output, MWSN heavily relies on cooperative communication. Large-scale wireless networks use multi-radio-multi-channel to improve performance by simultaneous broadcasts across symmetrical channels to reduce interference. Expanding cooperative communication in vast networks is subject to severe interference. And, as each node in the network is mobile, routing and transmission delay pose significant problems for cooperative multimedia wireless sensor networks. Mobility increases the MWSNs’ dynamic nature, which reflects in the overhead control traffic. To address above issues, a Cluster-based Delay Aware Cooperative Relay Selection (CDACRS) was proposed by employing mobility and distance metrics and channel assignment (CA) using dynamic Global Table (GT). To minimize the end-to-end transmission latency without compromising aggregate throughput, our approach chooses a relay-node depending on the mobility and the maximum available channel capacity. Further, to improve the end-to-end energy consumption, Power Aware Transmission (PAT) protocol is developed by calculating maximum transmission power required to meet target bit error rate (BER). The proposed method’s performance is evaluated against the Cluster-based Cooperative Multi-Hop Optimal Relay Selection (CCORS); energy efficient and quality aware multi-hop cooperative image transmission; and Energy Aware Cooperative Image Transmission (EACIT) algorithms and observed that our approach improves the transmission delay by 37.5% (approx.) and end-to-end energy consumption by 48.8%.

Energy-efficient data collection over underwater MI-assisted acoustic cooperative MIMO WSNs

Underwater magnetic induction (MI)-assisted acoustic cooperative multiple-input-multiple-output (MIMO) has been recently proposed as a promising technique for underwater wireless sensor networks (UWSNs). For the more, the energy utilization of energy-constrained sensor nodes is one of the key issues in UWSNs, and it relates to the network lifetime. In this paper, we present an energy-efficient data collection for underwater MI-assisted acoustic cooperative MIMO wireless sensor networks (WSNs), including the formation of cooperative MIMO and relay link establishment. Firstly, the cooperative MIMO is formed by considering its expected transmission range and the energy balance of nodes with it. Particularly, from the perspective of the node's energy consumption, the expected cooperative MIMO size and the selection of master node (MN) are proposed. Sequentially, to improve the coverage of the networks and prolong the network lifetime, relay links are established by relay selection algorithm that using matching theory. Finally, the simulation results show that the proposed data collection improves its efficiency, reduces the energy consumption of the master node, improves the networks' coverage, and extends the network lifetime.

SWIPT Enabled Cooperative Cognitive Radio Sensor Network With Non-Linear Power Amplifier

In this work, performance of a simultaneous wireless information and power transfer (SWIPT) enabled cooperative cognitive radio sensor network (CRSN) is explored over generalized Nakagami-m faded channels. A time switching (TS) protocol for SWIPT is used and the impact of TS factor on energy harvesting and information transmission phases, and information processing and broadcasting phases are considered. The cooperative CRSN consists of a pair of primary nodes (PNs) and sensor nodes (SNs), where one of the SWIPT enabled SN provides cooperative relaying for PNs communication by utilizing amplify-and-forward protocol. The overlay spectrum sharing protocol is used at the SN, which supports PNs communication along with its own transmission and resolves the spectrum scarcity issue. The impact of a non-linear power amplifier (NLPA) is also considered on the network performance. The analytical expressions of outage probability (OP), asymptotic OP, system throughput, and energy efficiency are obtained over Nakagami-m faded channels for arbitrary m. Further, the analytical expressions of ergodic capacity (EC) and asymptotic EC are obtained. The impact of NLPA and other system parameters on the performance of the considered network are highlighted. Finally, the obtained analytical expressions are validated through Monte-Carlo simulations.

Context-Aware Statistical Dead Reckoning for Localization in IoT Scenarios.

The current trends in 5G and 6G systems anticipate vast communication capabilities and the deployment of massive heterogeneous connectivity with more than a million internet of things (IoT) and other devices per square kilometer and up to ten million gadgets in 6G scenarios. In addition, the new generation of smart industries and the energy of things (EoT) context demand novel, reliable, energy-efficient network protocols involving massive sensor cooperation. Such scenarios impose new demands and opportunities to cope with the ever-growing cooperative dense ad hoc environments. Position location information (PLI) plays a crucial role as an enabler of several location-aware network protocols and applications. In this paper, we have proposed a novel context-aware statistical dead reckoning localization technique suitable for high dense cooperative sensor networks, where direct angle and distance estimations between peers are not required along the route, as in other dead reckoning-based localization approaches, but they are obtainable from the node's context information. Validation of the proposed technique was assessed in several scenarios through simulations, achieving localization errors as low as 0.072 m for the worst case analyzed.

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

In this paper, we propose a joint sensing duration and transmission power allocation scheme to maximize the energy efficiency (EE) of the secondary user (SU) in a cooperative cognitive sensor network (CSN). At the initial time slot of the frame, the secondary transmitter (ST) performs energy harvesting (EH) and spectrum sensing simultaneously using power splitting (PS) protocol. The modified goodness of fit (GoF) spectrum sensing algorithm is employed to detect the licensed spectrum, which is not sensitive to an inaccurate noise power estimate. Based on the imperfect sensing results, the ST will act as an amplify-and-forward (AF) relay and assist in transmission of the primary user (PU) or transmit its own data. The SU’s EE maximization problem is constructed under the constraints of meeting energy causality, sensing reliability, and PU’s quality of service (QoS) requirement. Since the SU’s EE function is a nonconvex problem and difficult to solve, we transform the original problem into a tractable convex one with the aid of Dinkelbach’s method and convex optimization technique by applying a nonlinear fractional programming. The closed-form expression of the ST’s transmission power is also derived through Karush-Kuhn-Tucker (KKT) and gradient method. Simulation results show that our scheme is superior to the existing schemes.

The Internet of Cooperative Agents Architecture (X-IoCA) for Robots, Hybrid Sensor Networks, and MEC Centers in Complex Environments: A Search and Rescue Case Study.

Cloud robotics and advanced communications can foster a step-change in cooperative robots and hybrid wireless sensor networks (H-WSN) for demanding environments (e.g., disaster response, mining, demolition, and nuclear sites) by enabling the timely sharing of data and computational resources between robot and human teams. However, the operational complexity of such multi-agent systems requires defining effective architectures, coping with implementation details, and testing in realistic deployments. This article proposes X-IoCA, an Internet of robotic things (IoRT) and communication architecture consisting of a hybrid and heterogeneous network of wireless transceivers (H2WTN), based on LoRa and BLE technologies, and a robot operating system (ROS) network. The IoRT is connected to a feedback information system (FIS) distributed among multi-access edge computing (MEC) centers. Furthermore, we present SAR-IoCA, an implementation of the architecture for search and rescue (SAR) integrated into a 5G network. The FIS for this application consists of an SAR-FIS (including a path planner for UGVs considering risks detected by a LoRa H-WSN) and an ROS-FIS (for real-time monitoring and processing of information published throughout the ROS network). Moreover, we discuss lessons learned from using SAR-IoCA in a realistic exercise where three UGVs, a UAV, and responders collaborated to rescue victims from a tunnel accessible through rough terrain.

Energy Efficiency Maximization for Energy Harvesting Bidirectional Cooperative Sensor Networks with AF Mode

Energy Efficiency Maximization for Energy Harvesting Bidirectional Cooperative Sensor Networks with AF Mode

Cross-layer energy optimization in cooperative MISO wireless sensor networks

Cooperative multi-input single-output (CMISO) is proved to be higher energy saving in long distance communication than single-input single-output (SISO) based on the physical layer energy consumption model, thus this technique applied in wireless sensor networks for reducing energy consumption has become a hot issue. However, CMISO needs depend on MAC layer protocol to control signals synchronization among all cooperative nodes and pilot symbols transmission for channel gain estimation at receiver, both of which increase additional energy overhead. Meanwhile, all the cooperative nodes which listen to the contention-based channel in the backoff time at the MAC layer also consume a lot of energy. Therefore, the conclusions derived only from the physical layer energy consumption model may be impractical without considering the neighboring nodes’ interference and additional MAC layer overhead. It is unknown whether CMISO is higher energy efficiency than SISO at the MAC layer. In our paper, a MAC protocol for CMISO is designed, and based on this protocol a cross-layer energy consumption model is proposed. This cross-layer model considers not only transmitting power and circuit power, but also additional energy overhead in listening to the channel, transmitting pilot symbols, control frames, etc. With the model, minimum energy consumption is derived at the different parameters such as contention window, number of cooperative nodes, radius of a cluster and constellation size. At the same time, our numerical results prove that CMISO saves about 27% energy consumption compared with SISO at the MAC layer. Since our results run under the heavy traffic environment with the highest transmission collision probability, we reasonably believe that CMISO communication will achieve better energy efficiency than SISO in ordinary traffic scenarios.

Range-Based Coordinate Alignment for Cooperative Mobile Sensor Network Localization

This article studies a coordinate alignment problem for cooperative mobile sensor network localization with range-based measurements. The network consists of target nodes, each of which has only access position information in a local fixed coordinate frame, and anchor nodes with GPS position information. To localize target nodes, we aim to align their coordinate frames, which leads to a nonconvex optimization problem over a rotation group $\text{SO}(3)$ . Then, we reformulate it as an optimization problem with a convex objective function over spherical surfaces. We explicitly design both iterative and recursive algorithms for localizing a target node with an anchor node, and extend to the case with multiple target nodes. Finally, the advantages of our algorithms against the literature are validated via simulations.

An Energy Optimization Clustering Scheme for Multi-Hop Underwater Acoustic Cooperative Sensor Networks

In this paper, we propose an improved energy optimization clustering algorithm (EOCA) for the multi-hop underwater acoustic cooperative sensor networks (UWA-CSN) due to the limited energy supply of the underwater sensor nodes. The proposed EOCA scheme considers multiple factors, such as the number of neighbor nodes, the residual energy of each node, the motion of the sensor nodes caused by the ocean currents, and the distance between the sink node and each underwater sensor node. All these factors are considered within the framework of the multi-hop cooperative communication. Moreover, in the proposed energy optimization scheme, we define a residual energy based maximum effective communication range (reE-MECR) according to the residual energy of each underwater sensor node, which can adaptively control the energy consumption of data transmission for each hop. Compared with the existing clustering scheme, the experimental results demonstrate that the proposed EOCA scheme can not only prolong the life time of the multi-hop UWA-CSN, but also keep a good communication and networking performance, including the package delivery ratio, the energy consumption efficiency, and the network coverage area. The proposed scheme can obtain both the clustering benefit and the cooperative communication benefit for the multi-hop UWA-SN in terms of energy saving in underwater environments.

Noncoherent Distributed Beamforming in Decentralized Two-Way Relay Networks

Many noncoherent distributed strategies for cooperative sensor networks that do not require channel knowledge at any antenna to overcome the overhead involved in channel estimation are lately suggested; however, these strategies suffer from low system performance in terms of bit error rate (BER) and a comparably high decoding complexity. Differential beamforming strategies have recently been proposed to overcome these problems; however, they are implemented using the four-phase protocol. Thus, we propose a new strategy based on the three-phase protocol to increase the symbol rate. By doing this, a significant improvement can be achieved in the overall system performance. Hence, in this article, a new bidirectional differential beamforming strategy is suggested: 1) to be applied on the three-phase protocol instead of the four-phase protocol; 2) to be applicable for a decentralized wireless sensor network using single-antenna sensors distributed randomly between the communicating base stations; 3) to enjoy low decoding complexity; and 4) to improve the network performance in terms of BER by maximizing the received signal-to-noise ratio at the receiving base station without requiring channel knowledge at any antenna in the whole network. From our simulation results, the proposed strategy shows a substantially improved BER performance compared with the current state-of-the-art ones.

A Geometric Approach for Distributed Multi-Hop Target Localization in Cooperative Networks

This work addresses target localization problem in cooperative distributed sensor networks, in which all sensors are capable of measuring Received Signal Strength (RSS), but only some are appropriately equipped to measure Angle Of Arrival (AOA) of the received signal. A novel approach based on simple geometry and multi-hopping is proposed, which allows for natural conversion of the problem into a Generalized Trust Region Sub-Problem (GTRS). The proposed algorithm comprises three main steps, each of them with linear computational cost in the number of neighbors, making it suitable for real-time applications. Our simulation results validate the performance of the new algorithm, surpassing some significantly more complex ones, and almost achieving a lower bound set by an existing algorithm which uses some (unrealistic) assumptions in its favor.

Energy Efficiency Analysis of Bidirectional Wireless Information and Power Transfer for Cooperative Sensor Networks

In this paper, we study the energy efficiency of bidirectional wireless information and power transfer in cooperative sensor networks, where the relay node can decode and forward information from the sensor node (SN) to base station (BS), and assist the wireless power transfer from the BS to SN. For the power splitting protocol, we propose the joint power allocation scheme to maximize the energy efficiency. For the time switching protocol, the optimal power allocation strategy and the optimal time allocation scheme are derived by studying the derivative of the energy efficiency. Simulation results are provided to verify the performance of our proposed schemes for the cooperative sensor networks.

Reliability-Aware Cooperative Node Sleeping and Clustering in Duty-Cycled Sensors Networks.

Duty-cycled sensor networks provide a new perspective for improvement of energy efficiency and reliability assurance of multi-hop cooperative sensor networks. In this paper, we consider the energy-efficient cooperative node sleeping and clustering problems in cooperative sensor networks where clusters of relay nodes jointly transmit sensory data to the next hop. Our key idea for guaranteeing reliability is to exploit the on-demand number of cooperative nodes, facilitating the prediction of personalized end-to-end (ETE) reliability. Namely, a novel reliability-aware cooperative routing (RCR) scheme is proposed to select k-cooperative nodes at every hop (RCR-selection). After selecting k cooperative nodes at every hop, all of the non-cooperative nodes will go into sleep status. In order to solve the cooperative node clustering problem, we propose the RCR-based optimal relay assignment and cooperative data delivery (RCR-delivery) scheme to provide a low-communication-overhead data transmission and an optimal duty cycle for a given number of cooperative nodes when the network is dynamic, which enables part of cooperative nodes to switch into idle status for further energy saving. Through the extensive OPNET-based simulations, we show that the proposed scheme significantly outperforms the existing geographic routing schemes and beaconless geographic routings in wireless sensor networks with a highly dynamic wireless channel and controls energy consumption, while ETE reliability is effectively guaranteed.

Performance Analysis of DF/AF Cooperative MISO Wireless Sensor Networks With NOMA and SWIPT Over Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math> </inline-formula> Fading

In this paper, we investigate downlink cooperative multiple-input single-output wireless sensor networks with the nonorthogonal multiple access technique and simultaneous wireless information and power transfer over Nakagami- $m$ fading. Specifically, the considered network includes a multiantenna sink node, an energy-limited relay cluster, a high-priority sensor node (SN) cluster, and a low-priority SN cluster. Prior to transmission, a transmit antenna, a relay, a high-priority SN, and a low-priority SN are selected. In this paper, we propose three antenna-relay-destination selection schemes, i.e., sink node-high-priority, sink node-relay, and sink node-low-priority. In each proposed scheme, we consider two relaying strategies, i.e., decode-and-forward and amplify-and-forward, and then, we derive the corresponding closed-form expressions of outage probability at the selected SNs. In addition, we introduce two algorithms: 1) the power-splitting ratio optimization algorithm and 2) the best antenna-relay-destination selection determination algorithm. Finally, we utilize the Monte Carlo simulations to verify our analytical results.

An Intelligent Cooperative Visual Sensor Network for Urban Mobility.

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

CRWSNP: cooperative range-free wireless sensor network positioning algorithm

Sensing events occur in an area without knowing the events locations, is meaningless. Since there is no priorly knowledge about the locations of most of the sensors which scattered randomly in an area, wireless sensor network localization methods try to find out where sensors are located. A new cooperative and distributed range-free localization algorithm, based on only connectivity information is proposed in this paper. The method first uses convex optimization techniques to find primitive target nodes locations estimation, then nodes cooperate with each other in several iterations to improve the whole network location estimation. CRWSNP converges after a finite number of iterations because of applying two novel heuristic location correction techniques. As well as, results of the algorithm have been compared with six range-free based methods like CPE, DV-hop, APIT; and CRWSNP algorithm provides more accurate results over 50 random topologies for the network, in mean error and maximum error metrics.

Fuzzy Power Allocation for Opportunistic Relay in Energy Harvesting Wireless Sensor Networks

Compared with line powered wireless sensor nodes, power allocation, and rate adaption in energy harvesting (EH) nodes are challenging problems, due to the intermittent nature of the energy arrival process and data causality constraints. To address this problem, in this paper we propose an online fuzzy logic-based power allocation (FPA) scheme for a cooperative and delay constraint EH wireless sensor network (EHWSN) using opportunistic relaying. An EHWSN model is developed with finite energy and data buffer constraints at the relay node. The performance of FPA scheme is evaluated in terms of throughput, fairness, delay, transmission time, and energy consumption. The performance of FPA is also compared with one offline policy and two online policies. It is observed that the delay and the energy consumption of FPA scheme for a given throughput are very close to the offline power allocation policy. The results show that for a given EH profile tradeoff exists between data buffer capacity and throughput for a given payload in all the schemes. In addition, the opportunistic behavior of relay can be controlled by increasing buffer size, however, that may compromise the throughput beyond a certain buffer size. Furthermore, the performance of FPA scheme is also evaluated under Uniform, Rayleigh and Beta distributed energy arrivals.