Wireless Sensor and Robot Networks

The following sections are included:

• Preface
• Contents

Node mobility has long been considered as a hazard in wireless sensor networks, causing a degradation of performance or even persistent routing failures. The advance of technology has made possible a new vision in which mobility allows the improvement of performances and new applications. In this chapter, we focus on some of the contributions that take advantage of controlled mobility in wireless sensor networks to improve message delivery performances.

Random walks in Wireless Sensor Networks can serve as fully local, very simple strategies for sink motion that lift from sensors the computational burden of propagating collected data via complex routing algorithms. In such schemes, sensors maintain a passive role waiting for the sink to visit them and collect their data. Therefore, energy dissipation is significantly reduced at the expense of increasing the latency of data delivery. To achieve satisfactory energy-latency trade-offs, the sink walks can be made adaptive, depending on critical network parameters (density, history of past visits in each network region) as well as characteristic attributes of the network topology. In this chapter, we study known random walks on two well established network models; the Grid and the Random Geometric Graphs. Towards better balances of memory/performance, we propose four new random walks that we experimentally evaluate in terms of several performance metrics that capture important differences in the network traversal process. The simulation findings demonstrate that even with limited memory usage, random walks can prove themselves very efficient when carefully designed.

Problem of coordination among robots is addressed in the context of Wireless sensor and robot networks (WSRNs) in this chapter. The two traditional fields of wireless sensor networks (WSNs) and multi-robot systems meet in the WSRNs. This chapter considers coordination among robots aimed for application of networked robots to manage and improve functionality of sensor networks, in various tasks in which response to events detected by sensors is needed. Coordination problem consists of two parts: task assignment (or allocation) and task fulfillment. Most of the papers in the traditional field of multi-robots deal with generic problem statements with heavy assumptions (e.g., complete communication graph is assumed) when it comes to task assignment problem. Literature still lacks solutions for the task assignment scenarios with non-ideal or limited communication, especially in cases with several concurrent events. This chapter focuses on the task assignment problem as a part of coordination among robots in WSRNs starting from the simplest single-event scenarios to complex multiple-event scenarios and reviews possible solutions and current research challenges.

The advances in mobile robotics allow us today to add the mobility concept into many different classes of wireless sensor networks (WSN) or wireless sensor and actuator networks (WSAN) applications. The deployment of mobile sensors is possible and useful in many application scenarios, ranging from the environmental monitoring, e.g., volcano activity, dispersion of fire, pollutants or gas plumes, and public safety applications (event or object surveillance), to the industry (structure and machinery health) and military applications (automated warfare, land mine detection). Manual sensor deployment represents a rather difficult task to achieve in such type of applications due to various reasons that will be discussed in this chapter. The use of mobile agents, i.e., robotic platforms equipped with sensory and motion capabilities, allows us to overcome these difficulties by deploying the sensor network in a random manner and applying the self-repositioning of self-deploying techniques.

A substitution network is a rapidly deployable backup wireless solution to quickly react to network topology changes due to failures or to flash crowd effects on the base network. Unlike other ad hoc and mesh solutions, a substitution network does not attempt to provide new services to customers but rather to restore and maintain at least some of the services available before the failure. Furthermore, a substitution network is not deployed directly for customers but to help the base network to provide services to customers. Therefore, a substitution network is not, by definition, a stand-alone network. In this chapter, we describe the main challenges regarding the implementation of substitution networks that are related to some simple questions: 1) When to deploy the substitution network and when to stop the deployment? 2) Where to place the mobile substitution routers and where to place the network services that must be implemented? 3) How to implement the network mechanism and protocols in order to fit the base network and substitution network needs?

Restoration of sensors' energy is crucial to ensure continuous operations of a sensor network. In static sensor networks, energy restoration requires the use of special mobile entities (e.g., robots, actuators). In mobile sensor networks, the sensors themselves can solve the problem by moving to recharge facilities deployed throughout the sensing area. An efficient energy restoration strategy is one in which the losses are limited in scope and time; that is, with the minimum number of sensor losses, it allows the system to reach a state of equilibrium guaranteeing continuous operation of the network without any further sensor losses. In this Chapter, we describe and examine the basic strategies for energy restoration, passive and active, and analyze their performance.

Deployment of WSNs is an important issue that requires careful consideration, as it can make the difference between an efficient and an unproductive system. The introduction of node mobility provides a wealth of potential solutions to the deployment problem, which can lead to higher robustness, flexibility and adaptivity. When provided with mobility features, network nodes are analogous to autonomous robots with local sensing and communication abilities. Therefore, behavioral strategies developed for collections of autonomous robots may be exploited in the mobile WSN domain. This is particularly true for swarm robotics studies, which emphasize self-organizing behaviors that deal with limited individual abilities, local sensing and local communication. In this chapter, we discuss the challenges and opportunities offered by swarm robotics with respect to the deployment of mobile WSNs. We review the state of the art in swarm robotics for coverage, exploration and navigation tasks, which are directly linked to the deployment problem, and we identify relevant directions for an hybridization of WSN and swarm robotics research.

This chapter is devoted to illustrate and characterize the relationship between Swarm Intelligence and cooperation among robots. Individuals with very limited computational capabilities are able to carry out very complex tasks when they can work together. From a methodological point of view, Swarm Intelligence is a set of heuristic solutions inspired by animal swarm behaviors and capable to offer empirical solutions to many computationally hard problems pertaining to several disciplines. In this chapter, we will try to outline the main research directions in Swarm Intelligence implementation within a robot network through the cooperation among the robots. The latter topic will be presented along with its advantages, issues and challenges. The convergence of robot cooperation and Swarm Intelligence is leading towards a new discipline, called Swarm Robotics. In this chapter, we will introduce this new field of study, its most relevant works and its main research directions.

With the proliferation of Wireless Sensor Networks (WSN) applications, knowing the node current location have become a crucial requirement. Location awareness enables various applications from object tracking to event monitoring, and also supports core network services such as: routing, topology control, coverage, boundary detection and clustering. Therefore, WSN localization have become an important area that attracted significant research interest. In the most common case, position related parameters are first extracted from the received measurements, and then used in a second step for estimating the position of the tracked node by means of a specific algorithm. From this perspective, this chapter is intended to provide an overview of the major localization techniques, in order to provide the reader with the necessary inputs to quickly understand the state-of-the-art and/or apply these techniques to localization problems such as robot networks. We first review the most common measurement techniques, and study their theoretical accuracy limits in terms of Cramer-Rao lower bounds. Secondly, we classify the main localization algorithms, taking those measurements as input in order to provide an estimated position of the tracked node(s).

Wireless sensor networks (WSNs) have emerged as an effective solution for a wide range of business applications. Most of the traditional WSN architectures consist of stationary nodes that are densely deployed over a sensing area. Recently, several WSN architectures deploying mobile devices have been proposed to exploit node mobility, and address problems of data transmission and collection in WSNs. In this chapter, we first define mobile wireless sensor networks (MWSNs). Then, we present an overview of the major challenges encountered in data transmission in MWSNs. Finally, we focus on the importance of MWSNs in business applications. We identify recent business applications where mobile wireless sensors have become important along with the challenges they are facing.