A Message Passing Strategy for Decentralized Connectivity Maintenance in Agent Removal

In a multi-agent system, agents coordinate to achieve global tasks through local communications. Coordination usually requires sufficient information flow, which is usually depicted by the connectivity of the communication network. In a networked system, removal of some agents may cause a disconnection. In order to maintain connectivity in agent removal, one can design a robust network topology that tolerates a finite number of agent losses, and/or develop a control strategy that recovers connectivity. This paper proposes a decentralized control scheme based on a sequence of replacements, each of which occurs between an agent and one of its immediate neighbors. The replacements always end with an agent, whose relocation does not cause a disconnection. We show that such an agent can be reached by a local rule utilizing only some local information available in agents' immediate neighborhoods. As such, the proposed message passing strategy guarantees the connectivity maintenance in arbitrary agent removal. Furthermore, we significantly improve the optimality of the proposed scheme by incorporating $\delta$-criticality (i.e. the criticality of an agent in its $\delta$-neighborhood).Comment: 9 pages, 9 figure

Fast Biconnectivity Restoration in Multi-Robot Systems for Robust Communication Maintenance

Maintaining a robust communication network plays an important role in the success of a multi-robot team jointly performing an optimization task. A key characteristic of a robust multi-robot system is the ability to repair the communication topology itself in the case of robot failure. In this paper, we focus on the Fast Biconnectivity Restoration (FBR) problem, which aims to repair a connected network to make it biconnected as fast as possible, where a biconnected network is a communication topology that cannot be disconnected by removing one node. We develop a Quadratically Constrained Program (QCP) formulation of the FBR problem, which provides a way to optimally solve the problem. We also propose an approximation algorithm for the FBR problem based on graph theory. By conducting empirical studies, we demonstrate that our proposed approximation algorithm performs close to the optimal while significantly outperforming the existing solutions

The Deployment in the Wireless Sensor Networks: Methodologies, Recent Works and Applications

International audienceThe wireless sensor networks (WSN) is a research area in continuous evolution with a variety of application contexts. Wireless sensor networks pose many optimization problems, particularly because sensors have limited capacity in terms of energy, processing and memory. The deployment of sensor nodes is a critical phase that significantly affects the functioning and performance of the network. Often, the sensors constituting the network cannot be accurately positioned, and are scattered erratically. To compensate the randomness character of their placement, a large number of sensors is typically deployed, which also helps to increase the fault tolerance of the network. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN. First, we introduce the problem of deployment and then we present the latest research works about the different proposed methods to solve this problem. Finally, we mention some similar issues related to the deployment and some of its interesting applications

Survey of Deployment Algorithms in Wireless Sensor Networks: Coverage and Connectivity Issues and Challenges

International audienceWireless Sensor Networks (WSNs) have many fields of application, including industrial, environmental, military, health and home domains. Monitoring a given zone is one of the main goals of this technology. This consists in deploying sensor nodes in order to detect any event occurring in the zone of interest considered and report this event to the sink. The monitoring task can vary depending on the application domain concerned. In the industrial domain, the fast and easy deployment of wireless sensor nodes allows a better monitoring of the area of interest in temporary worksites. This deployment must be able to cope with obstacles and be energy efficient in order to maximize the network lifetime. If the deployment is made after a disaster, it will operate in an unfriendly environment that is discovered dynamically. We present a survey that focuses on two major issues in WSNs: coverage and connectivity. We motivate our study by giving different use cases corresponding to different coverage, connectivity, latency and robustness requirements of the applications considered. We present a general and detailed analysis of deployment problems, while highlighting the impacting factors, the common assumptions and models adopted in the literature, as well as performance criteria for evaluation purposes. Different deployment algorithms for area, barrier, and points of interest are studied and classified according to their characteristics and properties. Several recapitulative tables illustrate and summarize our study. The designer in charge of setting up such a network will find some useful recommendations, as well as some pitfalls to avoid. Before concluding, we look at current trends and discuss some open issues

Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment: A Voronoi Approach

The rapid deployment of wireless sensor network (WSN) poses the challenge of finding optimal locations for the network nodes, especially so in (i) unknown and (ii) obstacle-rich environments. This paper addresses this challenge with BISON (Bio-Inspired Self-Organizing Network), a variant of the Voronoi algorithm. In line with the scenario challenges, BISON nodes are restricted to (i) locally sensed as well as (ii) noisy information on the basis of which they move, avoid obstacles and connect with neighboring nodes. Performance is measured as (i) the percentage of area covered, (ii) the total distance traveled by the nodes, (iii) the cumulative energy consumption and (iv) the uniformity of nodes distribution. Obstacle constellations and noise levels are studied systematically and a collision-free recovery strategy for failing nodes is proposed. Results obtained from extensive simulations show the algorithm outperforming previously reported approaches in both, convergence speed, as well as deployment cost.Comment: 17 pages, 24 figures, 1 tabl

Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges

Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant advancements in sensor capabilities and computational abilities, allowing for efficient autonomous navigation and visual tracking applications. However, the demand for computationally complex tasks has increased faster than advances in battery technology. This opens up possibilities for improvements using edge computing. In edge computing, edge servers can achieve lower latency responses compared to traditional cloud servers through strategic geographic deployments. Furthermore, these servers can maintain superior computational performance compared to UAVs, as they are not limited by battery constraints. Combining these technologies by aiding UAVs with edge servers, research finds measurable improvements in task completion speed, energy efficiency, and reliability across multiple applications and industries. This systematic literature review aims to analyze the current state of research and collect, select, and extract the key areas where UAV activities can be supported and improved through edge computing

A Distributed Strategy to Maximize Coverage in a Heterogeneous Sensor Network in the Presence of Obstacles

In this paper, an efficient deployment strategy is proposed for a network of mobile and static sensors with nonidentical sensing and communication radii. The multiplicatively weighted Voronoi (MW-Voronoi) diagram is used to partition the field and assign the underlying coverage task to each mobile sensor. A gradient-based method is applied to find the best candidate point based on the detected coverage holes and the coverage priority considering the relative distance of the mobile sensor from the static ones and the obstacles in the field. The sensors move to a new position if such a relocation increases their local coverage. The efficiency of the proposed strategy in different scenarios is demonstrated by simulations.Comment: 8 pages, 8 figures, submitted to the 62nd IEEE Conference on Decision and Contro