Destination Node Research Articles

Secrecy Rate Maximization by Cooperative Jamming for UAV-Enabled Relay System With Mobile Nodes

In recent years, Unmanned Aerial Vehicles (UAVs) have been widely used in wireless communications due to their low cost, small size, flexible deployment and mobile controllability. However, because of the line-of-sight (LoS) communication links, the security threat is always a challenging problem to deal with. In particular, information stolen and leakage may happen in the presence of eavesdroppers. This paper proposes a UAV-enabled system with a relay UAV and a jammer UAV, and certain mobile source and destination nodes in the presence of an eavesdropper to solve the secrecy rate maximization problem. In this system, the relay UAV transmits information between pairs of moving source nodes and moving destination nodes with interrupted communication channels due to blockage or long distance, and the jammer UAV interferes with eavesdropper to reduce the milked information through sending jamming signals. We establish an average secrecy rate maximization problem with trajectory and transmit power optimization under certain constraints for this system. Since this problem is non-convex and reformulated as the Markov decision process (MDP), we use deep reinforcement learning (DRL) method to solve it. In this article, we adopt a proximal policy optimization (PPO) algorithm to find an optimal solution because it can deal with the model of continuous action space. According to our defined states, rewards and actions in this specified MDP, this algorithm can autonomously learn to optimize the trajectory and power allocation of the UAVs to realize our goal. Simulation results demonstrate that the proposed PPO-based average secrecy rate maximization algorithm is valid, effective and scalable.

Outage Performance of Asymmetrical Cognitive Simultaneous Wireless Information and Power Transfer Networks Based on Non-Orthogonal Multiple Access with an Incremental Cooperation Relay and Hardware Impairments

This work aims to investigate an asymmetrical NOMA transmission network based on cognitive radio, where both the source and relay nodes of the secondary user are energy limited, and the energy could be harvested from the transmission signal of the power beacon. Considering some particular hardware impairments and asymmetry in the NOMA transmission, the closed-form expressions of outage probability for relay and destination nodes were derived using incremental relay methods. Furthermore, built on the expressions of the outage probability, the throughput performance was analyzed. Finally, the correctness of our theoretical analysis was verified using simulations.

Dual Protection Routing Trees on Graphs

In IP networks, packet forwarding is destination-based and hop-by-hop, and routes are built as needed. Kwong et al. introduced a protection routing in which packet delivery to the destination node can proceed uninterrupted in the event of any single node or link failure. He then showed that “whether there is a protection routing to the destination” is NP-complete. Tapolcai found that two completely independent spanning trees, abbreviated as CISTs, can be used to configure the protection routing. In this paper, we proposed dual protection routing trees, denoted as dual-PRTs to replace CISTs, which are less restrictive than CISTs. Next, we proposed a transformation algorithm that uses dual-PRTs to configure the protection routing. Taking complete graphs Kn, complete bipartite graphs Km,n, hypercubes Qn, and locally twisted cubes LTQn as examples, we provided a recursive method to construct dual-PRTs on them. This article showed that there are no two CISTs on K3,3, Q3, and LTQ3, but there exist dual-PRTs that can be used to configure the protection routing. As shown in the performance evaluation of simulation results, for both Qn and LTQn, we get the average path length of protection routing configured by dual-PRTs is shorter than that by two CISTs.

Disguised Full-Duplex Covert Communications.

Covert communications have arisen as an effective communications security measure that overcomes some of the limitations of cryptography and physical layer security. The main objective is to completely conceal from external devices the very existence of the link for exchanging confidential messages. In this paper, we take a step further and consider a scenario in which a covert communications node disguises itself as another functional entity for even more covertness. To be specific, we study a system where a source node communicates with a seemingly receive-only destination node which, in fact, is full-duplex (FD) and covertly delivers critical messages to another hidden receiver while evading the surveillance. Our aim is to identify the achievable covert rate at the hidden receiver by optimizing the public data rate and the transmit power of the FD destination node subject to the worst-case detection error probability (DEP) of the warden. Closed-form solutions are provided, and we investigate the effects of various system parameters on the covert rate through numerical results, one of which reveals that applying more (less) destination transmit power achieves a higher covert rate when the source transmit power is low (high). Since our work provides a performance guideline from the information-theoretic point of view, we conclude this paper with a discussion on possible future research such as analyses with practical modulations and imperfect channel state information.

Design and Analysis of Systematic Batched Network Codes.

Systematic codes are of important practical interest for communications. Network coding, however, seems to conflict with systematic codes: although the source node can transmit message packets, network coding at the intermediate network nodes may significantly reduce the number of message packets received by the destination node. Is it possible to obtain the benefit of network coding while preserving some properties of the systematic codes? In this paper, we study the systematic design of batched network coding, which is a general network coding framework that includes random linear network coding as a special case. A batched network code has an outer code and an inner code, where the latter is formed by linear network coding. A systematic batched network code must take both the outer code and the inner code into consideration. Based on the outer code of a BATS code, which is a matrix-generalized fountain code, we propose a general systematic outer code construction that achieves a low encoding/decoding computation cost. To further reduce the number of random trials required to search a code with a close-to-optimal coding overhead, a triangular embedding approach is proposed for the construction of the systematic batches. We introduce new inner codes that provide protection for the systematic batches during transmission and show that it is possible to significantly increase the expected number of message packets in a received batch at the destination node, without harm to the expected rank of the batch transfer matrix generated by network coding.

Multicasting Model for Efficient Data Transmission in VANET

VANETs (Vehicle Ad hoc Networks) are networks made up of a number of vehicular nodes that are free to enter and leave the network. The Location Aided Routing (LAR) protocol is the one that is most frequently utilized among them. Here, the route request packets are flooded across many pathways to the source node using the broadcasting strategy. The vehicles that have a direct path to the destination send the route reply packets back to the source. The least number of hops and the sequence number are used to determine the route from source to destination. This research study has used the multicasting approach to construct a path from the source node to the destination node. Within this multicasting strategy, the root nodes from the network are selected for data routing. The path between the source and the destination is chosen using a root node. The suggested approach is put into practice using the NS2, and some parametric values are computed to produce analytical findings.

Sustainable Next-Generation Network Design using Social Aware and Delay Tolerant Approach

With the ever-growing popularity of smartphones, new services are emerging where the local and positioning aspects become more important. Additionally, new routing algorithms are being developed based on various networking technology such as Delay Tolerance Networks (DTN), Deviceto- Device communication, Opportunistic Network, etc. DTN is categorized as stable and unstable, a continuous path between the source and the destination node. Here, communication is done by carrying the message through the intermediate relay node on the store and carry forward paradigm. In this work, a Sustainable Energy Delay Tolerance Approach (SEDA) considers nodes mobility patterns for energy-efficient data transmission. This routing model is based on the appropriate usage of node information along with node mobility and its contacts for data dissemination. Next step is applying some techniques to predict the most likely position for next encounter. We will design and implement a social relation-aware routing relation-awareness the social relation as a part of the routing matrix. We assume that most of the movement of nodes are included in various numbers of social contacts; therefore, there is a higher probability of message delivery to the destination. Simulation results show that the proposed routing protocol improves the delivery ratio by reducing network size and distance, which also impacts energy saving.

Energy balanced reliable and effective clustering for underwater wireless sensor networks

While sending data from a submerged wireless sensor network, more power is necessary due to the additional distance the signal must travel as well as the higher amount of energy lost along the route. Also, the acoustic medium generated by the shadow and the acoustic animals alters the transmission between the source and destination nodes. Multipath fading, significant path loss, and various interferences are some of the difficulties that come with communication at larger depths. The connection strength was variable, there was a low bandwidth, a high salt content, high pressure, high temperature, a sinkhole, and the route curved. These variables influence a variety of network aspects, including energy efficiency, link quality, and packet delivery ratio (PDR). The Energy Balanced Reliable and Effective Clustering (EBREC) method was created to ensure that data packets reach at their destination intact. This was done in order to avoid the complications caused by these considerations. PDR and transmission loss reduction are other targets of the presented effort. The anticipated EBREC’s performance is assessed by comparing it to many already defined benchmarks. According to the evaluation report, the simulation results reveal that EBREC performs very well when compared to the other methods in terms of Residual Energy of 0.615 J, Consumed Energy of 2.3 mJ, Throughput of 10Mbps, PDR of 97.6 %, Network Lifetime of 1750 sec, Number of Alive Nodes of 91%. Hence, the simulation results reveal that the EBREC technique beats competing approaches.

Integer Linear Programming Model for Multicast Routing to Minimize Link Cost at Wavelengths

Routing is a technique or process carried out in a packet or information delivery system from a source to a destination or a place that requests the information needed from a source. Routing is done in solving a problem and is well-known is unicast routing. Unicast routing can transmit information from a source to a single destination. However, this is ineffective for an infinite number of requests to be served because the unicast routing system only funnels one destination to one source. So that another route is needed that can handle this, this route is called a multicast route. Multicast routing that can serve multiple destinations with only one source so that a collection of destinations to get the same request in the same time and data. This research will discuss multicast routing to minimize link costs at wavelengths using a hierarchical structure. To help provide reduction or savings on the link by offering an integer linear programming model formulation to minimize link costs at wavelengths. An update from previous studies is to use a hierarchical structure with wavelength conversion taking into account the links that are traversed and the requests that will be served by the source to the destination. Using wavelength conversion so that there are no wavelength continuity problems, so that when sending information you get more path choices and you can save on sending information using a link that will be passed from the source to the intermediate node until it reaches the destination node, with this it will find a path more efficiently so that the goal of minimizing link cost at wavelengths on multicast routing is achieved

Low Latency Extended Dijkstra Algorithm with Multiple Linear Regression for Optimal Path Planning of Multiple AGVs Network

Dijkstra algorithms are typically used to find the shortest path from a source node to a destination node. It is widely used in various applications due to its reliability and less complexity. This paper presents the extended Dijkstra Algorithm with lower latency and consumes less computing memory intended for implementation in many AGVs networks for effective decentralized task distribution path planning. This paper proposed linear regression normalization across the node network in Dijkstra architecture to reduce computing time and memory consumption. The issue addressed through this optimization focused on reducing the possibilities of collision between AGVs and deadlock. The extended Dijkstra algorithm significantly reduces computing time compared to the traditional Dijkstra algorithm. In addition, the proposed solutions suggest better AGV routing for collision avoidance and deadlock prevention possibilities.

Usage of task and data parallelism for finding the lower boundary vectors in a stochastic-flow network

In a stochastic-flow network, a minimal system state vector under which the maximum flow of the network from a source node to a destination node is equal to d is called a lower boundary vector (LBV). As the number of LBVs increases exponentially with the size of the network, the available algorithms in the literature could be improved to be more practical for real-world large-sized systems. We employ task and data parallelism to propose an efficient algorithm for determining all the LBVs to tackle this problem. We present an efficient approach for removing duplicate solutions to improve an available algorithm to find all the LBVs. We show the correctness and compute the complexity results of the proposed approach and demonstrate its efficiency. Then, we propose vectorized, parallelized, and vectorized–parallelized versions of the main algorithm. We illustrate the standard version through a benchmark example and discuss the other proposed versions’ correctness. We conduct several experimental results on two known benchmark networks and more than one thousand random problems to demonstrate the practical efficiency of the vectorized–parallelized version. Moreover, Dolan and Moré’s performance profile is used to provide a more intuitive comparison between all four versions.

Auction-Based Learning for Question Answering over Knowledge Graphs

Knowledge graphs are graph-based data models which can represent real-time data that is constantly growing with the addition of new information. The question-answering systems over knowledge graphs (KGQA) retrieve answers to a natural language question from the knowledge graph. Most existing KGQA systems use static knowledge bases for offline training. After deployment, they fail to learn from unseen new entities added to the graph. There is a need for dynamic algorithms which can adapt to the evolving graphs and give interpretable results. In this research work, we propose using new auction algorithms for question answering over knowledge graphs. These algorithms can adapt to changing environments in real-time, making them suitable for offline and online training. An auction algorithm computes paths connecting an origin node to one or more destination nodes in a directed graph and uses node prices to guide the search for the path. The prices are initially assigned arbitrarily and updated dynamically based on defined rules. The algorithm navigates the graph from the high-price to the low-price nodes. When new nodes and edges are dynamically added or removed in an evolving knowledge graph, the algorithm can adapt by reusing the prices of existing nodes and assigning arbitrary prices to the new nodes. For subsequent related searches, the “learned” prices provide the means to “transfer knowledge” and act as a “guide”: to steer it toward the lower-priced nodes. Our approach reduces the search computational effort by 60% in our experiments, thus making the algorithm computationally efficient. The resulting path given by the algorithm can be mapped to the attributes of entities and relations in knowledge graphs to provide an explainable answer to the query. We discuss some applications for which our method can be used.

Network Topology Inference Based on Timing Meta-Data

A set of low-cost sensors is deployed to infer the network topology of a self-organizing wireless network. The sensors operate in a non-invasive fashion, extracting only the timings of data packets and acknowledgment (ACK) packets from all nodes in a network. The meta-data also reports the source node of each packet, but not the destination nodes or the contents of the packets. A central processor collects the meta-data from the sensors, and the goal is for the processor to infer the network topology based solely on such information. Prior work leveraged causality metrics to identify which links are active. If the data timings and ACK timings of two nodes – say node 1 and node 2, respectively – are causally related, this may be taken as evidence that node 1 is communicating to node 2 (which sends back ACK packets to node 1). This paper starts with the observation that packet losses can weaken the causality relationship between data and ACK timing streams. To obviate this problem, a new Expectation Maximization (EM)-based algorithm is introduced – EM-causality discovery algorithm (EM-CDA) – which treats packet losses as latent variables. EM-CDA iterates between the estimation of packet losses and the evaluation of causality metrics. The method is validated through extensive experiments in wireless sensor networks on the NS-3 simulation platform.

Optimal coefficient selection in Compute and Forward relaying using improved Schnorr–Euchner search algorithm

Physical layer Network Coding with Compute and Forward relaying (CF) is a promising transmission strategy that effectively exploits the natural linear computation of the multiuser wireless channel. In CF relaying, the relay nodes receive a linear combination of transmitted signals with additive noise and each relay node computes an integer linear combination of transmitted codewords which are then forwarded to the destination. After receiving enough independent equations from multiple relay nodes, the destination could decode individual source nodes’ messages. The source nodes use nested lattice codes which have the property that an integer linear combination of codewords is a valid codeword in the codeset. The simulation set up includes a K×K×1 network model with K source nodes, K relay nodes and 1 destination node. Relay nodes are assumed to have perfect channel state information, which is used in computing the linear equation. The success of CF relaying lies in choosing the optimal coefficient in computing the independent linear equation at each relay node. Optimal coefficient selection aims to maximize the computation rate which can be achieved when the equation coefficients are matched with complex-valued channel gains. This paper proposes an iterative algorithm for finding the optimal coefficient vector in the Gaussian integer domain using an improved Schnorr–Euchner search strategy. The performance of the proposed coefficient search algorithm in terms of computation complexity and the achievable rate is compared with other existing algorithms through MATLAB simulation. Simulation is performed for networks with 2, 4, 8 and 16 numbers of source and relay nodes. The proposed coefficient selection algorithm is validated for varying Signal to Noise Power under Rayleigh fading channel environment.

Exchange rates and multicommodity international trade: insights from spatial price equilibrium modeling with policy instruments via variational inequalities.

In this paper, we construct a multicommodity international trade spatial price equilibrium model of special relevance to agriculture in which exchange rates are included along with policy instruments in the form of tariffs, subsidies as well as quotas. The model allows for multiple trade routes between country origin nodes and country destination nodes and these trade routes can include different modes of transportation and transport through distinct countries. We capture the impacts of exchange rates through the definition of effective path costs and identify the governing multicommodity international trade spatial price equilibrium conditions, which are then formulated as a variational inequality problem in product path flows. Existence results are established and a computational procedure presented. The illustrative numerical examples and a case study are inspired by the impacts of the war against Ukraine on agricultural trade flows and product prices. The modeling and algorithmic framework allows for the quantification of the impacts of exchange rates and various trade policies, as well as the addition or deletion of supply markets, demand markets and/or routes, on supply and demand market prices in local currencies, and on the volume of product trade flows with implications for food security.

A Rubik's Cube Cryptosystem-based Authentication and Session Key Generation Model Driven in Blockchain Environment for IoT Security

Over the past decade, IoT has gained huge momentum in terms of technological exploration, integration, and its various applications even after having a resource-bound architecture. It is challenging to run any high-end security protocol(s) on Edge devices. These devices are highly vulnerable toward numerous cyber-attacks. IoT network nodes need peer-to-peer security, which is possible if there exists proper mutual authentication among network devices. A secure session key needs to be established among source and destination nodes before sending the sensitive data. To generate these session keys, a strong cryptosystem is required to share parameters securely over a wireless network. In this article, we utilize a Rubik's cube puzzle-based cryptosystem to exchange parameters among peers and generate session key(s). Blockchain technology is incorporated in the proposed model to provide anonymity of token transactions, on the basis of which the network devices exchange services. A session key pool randomizer is used to avoid network probabilistic attacks. Our hybrid model is capable of generating secure session keys that can be used for mutual authentication and reliable data transferring tasks. Cyber-attacks resistance and performance results were verified using standard tools, which gave industry level promising results in terms of efficiency, light weightiness, and practical applications.

Position optimization for mobile relay communications with constrained energy over a whole horizontal plane

This paper concerns the position optimization problem of a mobile relay over a whole horizontal plane. This problem is important because the position of a mobile relay directly affects the end-to-end performance, e.g., reliability, connectivity, and data rate. In this paper, we propose a new position optimization scheme of a mobile relay over a whole horizontal plane based on the one-bit feedback information from the destination node, which improves the performance over the prior scheme whose position of the mobile relay is optimized over a fixed orbit. In the proposed scheme, the mobile relay is equipped with merely one single onboard antenna. Moreover, no prior information about the positions of both the source node and the destination node is required. Thus, the proposed scheme can work at low network resources scenario, which is particularly suitable for mobile relay communication with constrained energy, e.g., the communications in a disaster area where the infrastructure is heavily damaged, volcano monitoring, and wireless powered communication networking. According to the characteristics of the proposed scheme, we further design two heuristic implementations to calculate the optimal position of a mobile relay over a whole horizontal plane. The first implementation has better steady performance whereas the second implementation has better convergence speed. We implement the proposed scheme and conduct an extensive performance comparison between the proposed scheme and prior schemes to verify the advantages of the proposed scheme.

On the Physical-Layer Security of a Dual-Hop UAV-Based Network in the Presence of Per-Hop Eavesdropping and Imperfect CSI

In this paper, the physical layer security of a dual-hop unmanned aerial vehicle-based wireless network, subject to imperfect channel state information (CSI) and mobility effects, is analyzed. Specifically, a source node (S) communicates with a destination node (D) through a decode-and-forward relay (R), in the presence of two wiretappers (E1,E2) independently trying to compromise the two hops. Furthermore, the transmit nodes (S,R) have a single transmit antenna, while the receivers (R,D,E1,E2) are equipped with multiple receive antennas. Based on the per-hop signal-to-noise ratios (SNRs) and correlated secrecy capacities’ statistics, a closed-form expression for the secrecy intercept probability (IP) metric is derived, in terms of key system parameters. Additionally, asymptotic expressions are revealed for two scenarios, namely (i) mobile nodes with imperfect CSI and (ii) static nodes with perfect CSI. The results show that a zero secrecy diversity order is manifested for the first scenario, due to the presence of a ceiling value of the average SNR, while the IP drops linearly at high average SNR in the second one, where the achievable diversity order depends on the fading parameters and number of antennas of the legitimate links/nodes. Furthermore, for static nodes, the system can be castigated by a 15 dB secrecy loss at IP=3×10-3, when the CSI imperfection power raises from 0 to 10-3. Lastly, the higher the legitimate nodes’ speed, carrier frequency, delay, and/or relay’s decoding threshold SNR, the worse is the system’s secrecy. Monte Carlo simulations endorse the derived analytical results.

Secure Real-Time Multimedia Data Transmission from Low-Cost UAVs with A Lightweight AES Encryption

In the context of real-time wireless multimedia transmission from Unmanned Aerial Vehicles (UAVs), equipped with microphone arrays and cameras, data security is crucial. Data security should be guaranteed from the acquisition onboard the drones to its delivery to the destination node or ground station. A real-time light-weight application-level Advanced Encryption Standard (AES) encryption algorithm has been considered to be applied to multimedia data and supported by the single-board-computers mounted onboard the drones, with low computational power. The study shows that the main advances are related to the design of a streaming application in a transmission architecture for military counter-UAV scenarios that is effective, secure, quick, and trustworthy for audio and video data. A multiple synchronous key management is also newly experimented. The thorough experiments have confirmed the effective validity of the encryption and decryption processes, even in the presence of adverse radio spectrum conditions.

IMPLEMENTASI KOMUNIKASI DATA MENGGUNAKAN PROTOKOL RF24NETWORK PADA SISTEM PEMANTAUAN KONDISI RUANGAN BERBASIS JARINGAN SENSOR NIRKABEL

Wireless Sensor Network (WSN) is an infrastructure consisting of a number of sensor nodes that are distributed in certain environments and coordinated using a wireless network. WSN can be implemented using the nRF24L01 module. One protocol that supports the nRF24L01 module is the RF24 protocol. But for the implementation of monitoring the vast room conditions this protocol has the disadvantage of using a single-hop mechanism. So that for a large area range, multi-hop mechanism is needed. The RF24Network protocol is a protocol designed to meet the needs of RF24-based multi-hop mechanisms, users simply build a header that contains the correct destination address and the network will forward it to the destination node. In accordance with the above problems, the authors implement sensor nodes using Arduino Nano as Microcontroller, nRF24L01 for communication media and DHT11 to acquire sensor data. From the implementation results obtained network performance for monitoring the condition of the room with the level of accuracy of data transmission and delay as follows. Single-hop data transmission mechanism without barrier distance 3-12 meters 100% accuracy, 15 meters 70%, 18 meters 40%, 21 meters 0% with a total average delay of 145 ms, with a distance barrier of 3-9 meters 100% accuracy , 12 meters 60%, 15 meters 30%, 18 meters 0% with a total average delay of 276 ms. The multi-hop mechanism of data transmission accuracy reaches 100% with average delay (1 hop without barrier 110 ms with a total distance of 24 meters, with a barrier of 270 ms with a total distance of 18 meters. 2 hops without barrier 270 ms with a total distance of 36 meters , with a 350 ms barrier with a total distance of 27 meters, 3 hops without a 280 ms barrier with a total distance of 48 meters, with a barrier of 260 ms with a total distance of 36 meters)..