A Review on Sensor Network Issues and Robotics <s> Introduction <s> This chapter contains sections titled: Wireless Sensor Networks: Generalities and Applications Sensor Nodes Mobility Mobile Relays Mobile Sinks Comparing Different Approaches to Mobility Comparative Evaluation Some Open Problems and Research Directions Conclusions Exercises Acknowledgments Bibliography <s> BIB001 </s> A Review on Sensor Network Issues and Robotics <s> Introduction <s> Observing microclimate changes is one of the most popular applications of wireless sensor networks. However, some target environments are often too dangerous or inaccessible to humans or large robots and there are many challenges for deploying and maintaining wireless sensor networks in those unfriendly environments. This paper presents a mobile sensor network system for solving this problem. The system architecture, the mobile node design, the basic behaviors and advanced network capabilities have been investigated respectively. A wheel-based robotic node architecture is proposed here that can add controlled mobility to wireless sensor networks. A testbed including some prototype nodes has also been created for validating the basic functions of the proposed mobile sensor network system. Motion performance tests have been done to get the positioning errors and power consumption model of the mobile nodes. Results of the autonomous deployment experiment show that the mobile nodes can be distributed evenly into the previously unknown environments. It provides powerful support for network deployment and maintenance and can ensure that the sensor network will work properly in unfriendly environments. <s> BIB002 </s> A Review on Sensor Network Issues and Robotics <s> Introduction <s> More and more researches focus on the development of mobile wireless sensor networks (MWSNs) due to the favorable advantages and applications of MWSNs. However, there is not a comprehensive survey about the research issues on MWSNS for the state of art. In this paper, we survey the communication and data management issues on MWSNs and provide extensible research directions of MWSNs. <s> BIB003 </s> A Review on Sensor Network Issues and Robotics <s> Introduction <s> Robotics can have many applications in wireless sensor networks. Robotics can be used to help solve many problems in wireless sensor networks, such as localizing nodes, acting as data mules, repositioning nodes, detecting and reacting to sensor failure, aggregate sensor data, and even sometimes provide mobile battery chargers for the nodes. Inversely, wireless sensor networks can help solve many problems in robotics, such as localization of the robot, path planning, mapping, and sensing. <s> BIB004
Technological advances as well as the advent of 4G communications and of pervasive and ubiquitous computing have promoted a new interest in multihop networks (ad hoc communications). In particular, the interest is in self-organizing wireless multihop networks composed of a possibly large number of motes which can be mobile and static and can also be used for computational and power capabilities. Wireless sensor networks (WSNs) are typical examples of these kinds of networks. Most of the research in WSNs concerns networks whose nodes cannot be replaced and do not move. Mobility of the sensor nodes has been exploited for improving, or enabling altogether, communication coverage and sensing BIB001 . The credit for the creation of mobile sensor networks goes to wireless sensor networks and to the interaction of distributed robotics. The class of networks where small sensing devices in a collaborative way move in a space to observe and monitor environmental and physical conditions are known as mobile sensor networks BIB003 . Mobile sensor network is composed of nodes and all nodes have sensing, computation, communication, and locomotion modules ( Figure 1 ). Each sensor node is capable of navigating autonomously or under the control of humans BIB002 . MSNs have emerged as an important area for research and development. Though MSNs are still in the developing stages, they can be used for monitoring of environmental habitat, healthcare, agriculture, defense applications, disaster prone areas, hazardous zones, and so forth. MWSNs can also be used for monitored control, and more and more practical applications of MSNs also continue to emerge [4] . And robotics is the science of technology with applications in various fields such as design, fabrication, and theory  . It can also be considered as the area of technology dealing with construction, operation, control of robotic applications and computer systems, sensory feedback, and information processing. The main advantage of this technology is that it can replace humans in manufacturing processes and dangerous environments or can also resemble humans in behavior, cognition, or experience  . A breakthrough in the autonomous robot technology occurred in the mid-1980s with work in behavior based robotics. We can say that this work was the foundation for many current robotic applications  . By incorporating intelligent, mobile robots directly into sensor networks most of the problems in traditional sensor networks may be addressed. Mobile robots offer the ways to interact and survey the environment in a decentralized and dynamic way. The new system of robots and networked sensors led to the development of new solutions to the existing problems such as navigation and localization  . Mobile 2 Journal of Sensors nodes can be implemented as autonomous perceptive mobile robots or as perceptive robots whose sensor systems address environmental and navigational tasks. So, we can say robotic sensor networks are the distributed systems in which mobile robots carry sensors around an area to sense phenomena and to produce detailed environmental assessments  . The use of multirobot systems for carrying sensors around the environment represents a solution that has received a significant attention and can also provide some extraordinary advantages. A number of applications have been addressed so far by robotic sensor networks, such as rescue, search, and environmental monitoring. In wireless sensor networks, robotics can also be used to solve many problems to advance performances, such as responding to a particular sensor failure, node distribution, and data aggregation. Similarly for solving the problems that exist in the field of robotics wireless sensor networks can play a crucial role. Problems like localization, path planning, coordination for multiple robot, and sensing can be solved by using wireless sensor networks BIB004 . Today we have many applications of sensor networks on ground, air, underwater, and underground. In mobile UWSN sensor mobility can bring two major benefits. Floating sensors can increase system reusability and can also help to enable dynamic monitoring and coverage. Mobile sensors can help to track changes in water masses thus providing 4D (space and time) environmental monitoring. As compared to ground based sensor networks mobile UWSNs have to employ acoustic communications because in hard water environments radio does not work. Similarly underground sensor network can be used to monitor a variety of conditions such as properties of soil and environmental monitoring for toxic substances. They are buried completely underground and do not require any wired connections. On the ground they can be used for target tracking, environmental monitoring, detecting forest fire, industrial monitoring, and machine health monitoring. Wireless sensor nodes are into the service from a long time and were being used for different applications such as earthquake measurements and warfare. The recent growth of small sensor nodes dates back to the year 1998 NASA Sensor Webs project and smart dust project. To make autonomous sensing and communication possible within a cubic millimeter of space was the main purpose of the smart dust project. This project led to many more research projects including major research centers in CENS and Berkeley NEST. The term mote was coined by researchers working in these projects to refer to a sensor node; pod is the same term used in the NASA Sensor Webs project for a physical sensor node, although in a Sensor Web the sensor node can be another Sensor Web itself [10] . The main components of a sensor node are as follows: transceiver, a microcontroller external memory, one or more sensors, and power source [10] . The controller processes the data and controls functionality of other components in the sensor nodes. The feasible option of wireless transmission media is infrared, radio frequency (RF), and optical communication. As far as external memory is concerned the most relevant kinds of memory are the flash memory and the on-chip memory of a microcontroller. The most important feature in the development of a wireless sensor node is to make sure that there is always sufficient energy available to the power system. Sensor nodes consume power for data processing, sensing, and communication; power is stored in capacitors or batteries. Batteries can be both rechargeable and nonrechargeable and for sensor nodes they are the main resource of power supply. And, sensor is a device that detects or senses heat, light, sound, motion, and so forth and then responds to it in a particular way [11] (Figure 2) . The crossbow radio/processor boards usually known as motes permit many sensors scattered over a large area to wirelessly transmit their data back to the base station which is attached to the computer (Figure 3 ). These motes run TinyOS operating system which is an open source operating system designed for low-power wireless devices, such as those used in PANs, smart meters, ubiquitous computing, sensor networks, and smart buildings [12] . It controls power, radio transmission and networking transparent to the user, and the network which is formed as an ad hoc network [13] . The MICA2 Mote is a third generation mote module with 512 Kbytes of measurement (serial) flash memory, 128 Kbytes of program flash memory, and 4 Kbytes of programmable read-only memory (Figure 4) . Stargate is a 400 MHZ Intel PXA255 Xscale processor with 32 Mbytes of flash memory and 64 Mbytes of synchronous dynamic random access memory. A number of classes of sensors are available; these include barometric pressure, acceleration, seismic, acoustic, radar, magnetic camera, light, temperature, relative humidity, magnetic camera, and global positioning system (GPS). Usually sensors are classified into 3 types: passive, omnidirectional, passive, narrow-beam, and active sensors. Passive sensors are selfpowered; they sense the data without actually manipulating the environment by active probing while active sensors actively probe the environment. Narrow beam sensors have a well-defined notion of direction of measurement. Omnidirectional sensors have no notion of direction involved in their measurements [10] ( Figure 5 ). 