In emergency response operations, the role of autonomous aerial vehicles (AAVs) has become vital for performing tasks such as human detection. However, these tasks are computationally intensive, and AAVs have limited resources. Therefore, fixed-wing AAV mother-ships with edge servers (UMECs), which usually have more speed and payload capacity than rotary-wing AAVs, can be deployed near AAV scouts (generate the tasks) to provide processing services. However, the design of fixed-wing AAVs requires adherence to a minimum turning radius, which limits maneuverability and impacts both energy consumption and task execution time, thus necessitating careful trajectory planning. Furthermore, UMECs may lack the capacity to process all types of tasks due to memory restrictions and require both central processing units and graphics processing units for faster execution of tasks. Therefore, this article aims to minimize the energy consumption in the network and task execution time by jointly optimizing the trajectory of UMECs, task offloading, and resource allocation (TTR) problem while taking into account UMECs movement constraints, task performance limitations, and computational resource budgets. In this regard, we first propose a particle swarm optimization (PSO)-based TTR scheme (P-TTR), where a PSO algorithm finds the trajectory solution, and a block coordinate descent-based method is developed to solve the task offloading and resource allocation problem. Then, for real-time decision-making, a deep-reinforcement-learning-based algorithm, namely soft-actor–critic-based TTR (S-TTR), is introduced to address the problem, which can adapt to dynamic environments and have lower computational overhead. Simulation results confirm that the proposed approaches can outperform the baseline method.

The task of monitoring a moving phenomenon in an unbounded area using a mobile sensor network (MSN) brings out several challenges due to the high movement speed of phenomenon, the limited sensing/communication capabilities of mobile sensor nodes. To address the challenges and achieve a high weighted sensing coverage, in this paper we propose a monitoring algorithm, namely VirFID-MP (Virtual Force (VF)-based Interest-Driven moving phenomenon monitoring with Mobility Prediction). In VirFID-MP, the movement of phenomenon is first predicted based on its previous movements. Then, the predicted information is used to determine a global virtual force, which is utilized to speed up the MSN toward the moving phenomenon. Simulation results show that VirFID-MP outperforms original VirFID in terms of weighted coverage efficiency, when the MSN monitors a moving phenomenon.

Abstract In this paper, we study mobile sensor network (MSN) architectures and algorithms for monitoring a moving phenomenon in an unknown and open area using a group of autonomous mobile sensor (MS) nodes. Monitoring a moving phenomenon involves challenges due to limited communication/sensing ranges of MS nodes, the phenomenon’s unpredictable changes in distribution and position, and the lack of information on the sensing area. To address the challenges and meet the objective of the maximization of weighted sensing coverage, we propose a novel scheme, namely VirFID (Virtual Force (VF)-based Interest-Driven moving phenomenon monitoring). In VirFID, MS nodes move toward the positions where more interesting sensing data can be obtained by utilizing the virtual force, which is calculated based on the distance between MS nodes and sensed values in the area of interest. MS nodes also perform network-wise information sharing to increase the weighted sensing coverage. Depending on the level of information used, three variants of VirFID are evaluated: VirFID-LIB (Local Information-Based), VirFID-GHL (Global Highest and Lowest), and VirFID-IBN (Interests at Boundary Nodes). In addition, an analytical model for estimating MSN speed is designed. Simulations are performed to compare the performance of three VirFID variants with other approaches. Our simulation results show that VirFID algorithms outperform other schemes in terms of the weighted coverage efficiency, and VirFID-IBN achieves the highest weighted coverage efficiency among VirFID variants.

In this study, a concatenated coding scheme based on Reed–Muller (RM) codes and bit‐extension codes is proposed for equivocation of a wiretap channel. RM codes and their cosets are adopted for message encoding, and bit‐extension codes are used to enhance the equivocation capability for a wiretapper's channel. The average equivocation is discussed when only RM codes are used in the system, and the probability causing imperfect secrecy is also determined. Analytical results show that the proposed code can be used for the equivocation capability of wiretap channels and suggest a proper management over a wiretap channel.

Wireless Sensor Networks (WSNs) will play a significant role at the “edge” of the future “Internet of Things.” In particular, WSNs with transmit-only nodes are attracting more attention due to their advantages in supporting applications requiring dense and long-lasting deployment at a very low cost and energy consumption. However, the lack of receivers in transmit-only nodes renders most existing MAC protocols invalid. Based on our previous study on WSNs with pure transmit-only nodes, this work proposes a simple, yet cost effective and powerful single-hop hybrid WSN cluster architecture that contains not only transmit-only nodes but also standard nodes (with transceivers). Along with the hybrid architecture, this work also proposes a new MAC layer protocol framework called Robust Asynchronous Resource Estimation (RARE) that efficiently and reliably manages the densely deployed single-hop hybrid cluster in a self-organized fashion. Through analysis and extensive simulations, the proposed framework is shown to meet or exceed the needs of most applications in terms of the data delivery probability, QoS differentiation, system capacity, energy consumption, and reliability. To the best of our knowledge, this work is the first that brings reliable scheduling to WSNs containing both nonsynchronized transmit-only nodes and standard nodes.

In ad hoc networks, wireless links are subject to a low quality due to time-varying channel properties, node mobility, and obstacles. Such low quality wireless links lead to the degraded performance of the end-to-end data transfer service, which also result in less applicability of ad hoc networks to practical deployment. In order to address the problem of low quality wireless links and provide a required quality for end-to-end data transfer services, we propose a novel routing and relaying architecture that exploits controllable mobility of robotic relays, namely RoCoMAR (Robots' Controllable Mobility Aided Routing), which repeatedly reinforces wireless links with the main objective of maximizing the network throughput. RoCoMAR first identifies the lowest quality link and replaces it with high quality links that are created by re-locating a robotic relay in an optimal position. The simulation results show that RoCoMAR outperforms existing ad hoc routing protocols in terms of network throughput and end-to-end delay.

Simple yet cost effective hybrid Wireless Sensor Networks (WSN) with both standard nodes and transmit-only nodes are promising for their great potential as the "edge" of the "Internet of Things". However the lack of receivers at many transmit-only nodes in the hybrid network renders most existing MAC protocols invalid. Our previous efforts showed the benefits of this hybrid architecture for building single-hop efficient and reliable hybrid WSN cluster for QoS aware applications. This work explores the capability of building multi-hop communications in a hybrid WSN with multiple clusters (where each cluster consists of a sink as well as a certain number of standard nodes and transmit-only nodes) via a cross-layer protocol design. The proposed M-QoMoR protocol and HPAssist scheme are built based on the resource information from the underlying MAC layer. Through the analysis and extensive simulations, we showed that the hybrid WSN architecture can efficiently support multi-hop communications across multiple hybrid clusters. It also achieves certain performance boost that is not viable in the previous single hybrid WSN clusters.

In this work, we study algorithms for cooperative search and survey using a fleet of Autonomous Underwater Vehicles (AUVs). Due to the limited energy, communication range/bandwidth, and sensing range of the AUVs, underwater search and survey with multiple AUVs brings about several new challenges since a large amount of data needs to be collected by each AUV, and any AUV may fail unexpectedly. To address the challenges and meet our objectives of minimizing the total survey time and traveled distance of AUVs, we propose a cooperative rendezvous scheme called Synchronization-Based Survey (SBS) to facilitate cooperation among a large number of AUVs when surveying a large area. In SBS, AUVs form an intermittently connected network (ICN) in that they periodically meet each other for data aggregation, control signal dissemination, and AUV failure detection/recovery. Numerical analysis and simulations have been performed to compare the performance of three variants of SBS schemes, namely, Alternating Column Synchronization (ACS), Strict Line Synchronization (SLS), and X Synchronization (XS). The results show that XS can outperform other SBS schemes in terms of the survey time and the traveled distance of AUVs. We also compare XS with nonsynchronization-based survey and the lower bound on the survey time and traveled distance. The results show that XS achieves a close to optimal performance.

Stationary wireless sensor networks (WSNs) fail to scale when the area to be monitored is unbounded and the physical phenomenon to be monitored may migrate through a large region. Deploying mobile sensor networks (MSNs) alleviates this problem, as the self-configuring MSN can relocate to follow the phenomenon of interest. However, a major challenge here is to maximize the sensing coverage in an unknown, noisy, and dynamically changing environment with nodes having limited sensing range and energy, and moving under distributed control. To address these challenges, we propose a new distributed algorithm, Causataxis, which enables the MSN to relocate toward the interesting regions and adjust its shape and position as the sensing environment changes. (In Latin, causa means motive/interest. A taxis (plural taxes) is an innate behavioral response by an organism to a directional stimulus. We use Causataxis to refer to an interest driven relocation behavior.) Unlike conventional cluster-based systems with backbone networks, a unique feature of our proposed approach is its biosystem inspired growing and rotting behaviors with coordinated locomotion. We compare Causataxis with a swarm-based algorithm, which uses the concept of virtual spring forces to relocate mobile nodes based on local neighborhood information. Our simulation results show that Causataxis outperforms the swarm-based algorithm in terms of the sensing coverage, the energy consumption, and the noise tolerance with a slightly high communication overhead.

Low cost and low power consumption are two major design criteria in wireless sensor networks (WSN). To meet the increasing demand for localized fine-grained sensing with densely deployed WSNs, this paper proposes the use of a hybrid WSN that consists of nodes with standard transceivers and nodes with only transmitters. A two-phase Constrained-Scheduling based MAC protocol is proposed, which employs the "Automatic Resource Estimation (ARE)" method. Through analysis and extensive simulations, the proposed protocol is shown to achieve a significant performance improvement in terms of data delivery probability, QoS differentiation and energy minimization over existing MAC protocols for such networks. To the best of our knowledge, this work is the first effort to bring scheduling to WSNs that contains asynchronous and uncoordinated transmit-only nodes.

This paper presents practical design and hardware implementation issues of self-configuring swarms of autonomous mobile robots. For the purpose, we develop a new low-cost position detection system that we call dual rotating infrared (DRIr) sensor. The DRIr sensor can provide robots with advanced sensing capabilities that give reliable information about the position and surface geometry of neighboring robots and obstacles. Special focus is placed on how to realize the observation and object identification of mobile robots through the use of DRIr sensors. We verify the functionality and performance of the DRIr sensors mounted on a commercial mobile robot. Experimental results show that a swarm of mobile robots equipped with the DRIr sensors can autonomously configure themselves into an area.

We consider a class of single hop wireless sensor networks in which the sensor nodes collect data periodically and transmit it to a sink. To reduce the complexity, cost and energy consumption of the nodes we propose the use of an asymmetric transceiver model in which the sensor nodes can transmit to the sink using standard physical layer modulation schemes that support relatively high data rates but can receive from the sink using basic modulation schemes that can only support very low data rates. The use of the transceiver module in each sensor node is thus limited to receiving simple feedback in the form of a few bytes of ACK from the sink node. In this paper we propose and study a new MAC protocol that enables effective communication between the sensor nodes and sink in such a network. We develop an analytical model to evaluate the performance of the MAC protocol and verify these results through extensive simulations. We also present results from the implementation of the protocol on a test bed consisting of XSM motes and evaluate its performance in a real world scenario.

This paper proposes a novel medium access control scheme for low cost, single-hop wireless networks where the source nodes have a transmitter module but no receiver module and hence they can only transmit data to a sink but cannot receive any control signals, like an ACK or NAK, from any other node. The goal of the proposed scheme is to provide QoS (in terms of packet delivery probability) to the nodes in such a network, where the existing schemes like polling or scheduled transmissions, CSMA and ARQ will be ineffective because of the unavailability of a receiver module at the nodes. The proposed scheme uses distributed control and allows the nodes to transmit each packet an optimal number of times at random instants in time within the packet generation interval. We define two optimization problems based on minimizing total network traffic and maximizing the delivery probability of the class of nodes requiring the highest QoS, respectively, and develop mathematical formulae and efficient algorithms to solve them. Numerical analysis and simulation results show that our scheme can provide high QoS to networks of different sizes.

Stationary wireless sensor networks (WSNs) fail to scale when the area to be monitored is open (i.e borderless) and the physical phenomena to be monitored may migrate through a large region. Deploying mobile sensor networks (MSNs) alleviates this problem, as the self-configuring MSN can relocate to follow the phenomena of interest. However, a major challenge here is to maximize the sensing coverage in an unknown, noisy, and dynamic sensing environment while minimizing energy consumption. Another major challenge is to maintain network connectivity for each MSN node during relocations. To address these challenges, we propose a new distributed algorithm, Causataxis1, that enables the MSN to relocate toward the interesting regions and adjust its shape and position as the sensing environment changes. Causataxis achieves scalable control of the MSN via a backbone-tree infrastructure maintained over clusterhead nodes, and achieves agility via localized cluster formation and dissolution. Unlike conventional cluster-based systems with backbone networks, a unique feature of our proposed approach is its bio-system inspired growing and rotting behaviors with coordinated locomotion. We compare Causataxis with a custom tuned swarm algorithm, which uses the concept of virtual spring forces to relocate mobile nodes based on local neighborhood information. Our simulation results show that Causataxis can outperform the swarm based algorithm in terms of the sensing coverage, the energy consumption, and the noise tolerance with a slightly high communication overhead.

Given a probabilistic graph G representing an intermittently connected network and routing algorithm A, we wish to determine a delivery subgraph G[A] of G with at most k edges, such that the probability Conn2(G[A]) that there is a path from source s to destination t (in a graph H chosen randomly from the probability space defined by G[A]) is maximized. To the best of our knowledge, this problem and its complexity has not been addressed in the literature. Also, there is the corresponding distributed version of the problem where the delivery subgraph G[A] is to be constructed distributively, yielding a routing protocol. Our proposed solution to this routing problem is multi-fold: First, we prove the hardness of our optimization problem of finding a delivery subgraph that maximizes the delivery probability and discuss the hardness of computing the objective function Conn2(G[A]); Second, we present an algorithm to approximate Conn2(G[A]) and compare it with an optimal algorithm; Third, we focus on intermittently connected networks, and model the users' mobility within them; and Fourth, we propose an edge-constrained routing protocol (EC-SOLAR-KSP) based on the insights obtained from the first step and the contact probabilities computed in the third step. We then highlight the protocol's novelty and effectiveness by comparing it with a probabilistic routing protocol, and an epidemic routing protocol proposed in literature.

In this paper, we study search algorithms for using a set of autonomous and cooperative mobile sensor nodes (MSN) with limited sensing and communication ranges to search a large area. Our objectives include minimizing the total search time and the travel distance of MSNs while enabling fault tolerance to possible MSN failures. We propose a new rendezvous scheme, namely X synchronization (XS) to facilitate the exchange of both data and control signals among the MSNs during search. We also devise a way to calculate appropriate timeout periods used to detect an MSN failure at rendezvous points and describe how surviving MSNs subsequently carry out the search mission. Numerical analysis and simulations have been performed to evaluate the performance of XS. The results show that XS can outperform other rendezvous schemes in terms of the total search time and the average travel distance of MSNs.