Mobile Sensor Network

Abstract. One of the main appeals of mobile sensors is the variety of environments in which they can operate as an autonomous network. Different environments, however, present different challenges, especially in terms of inter-sensor communication. In sparse environments, it may not be possible to maintain full connectivity at all times, setting off the need for agents to communicate opportunistically when they are close to each other. This, in turn, suggests that communication needs be taken into account in the design of agents ’ trajectories. In this paper, we introduce a notion of tour and meeting point as an abstraction of trajectories designed for both sensing and communication, and we study the tradeoffs involved between motion to sense and sample and motion to communicate and interact.

This article reviews the state-of-the-art energy-efficient contention-based and scheduledbased medium access control (MAC) protocols for mobile sensor networks (MSNs) by first examining access schemes for wireless sensor networks (WSNs). Efficient and proper mobility handling in sensor networks provides a window of opportunity for new applications. Protocols, such as S-MAC, reduce energy consumption by putting nodes to sleep after losing to channel contention or to prevent idling. Sleeping is a common method for energyefficient MAC protocols, but delay depends on sleep duration or frame time, and longer delays lead to higher packet lost rate when nodes are unsynchronized due to network mobility. MS-MAC extends S-MAC to include mobility-awareness by decreasing this sleep duration when mobility is detected. S-MAC with extended Kalman filter (EKF) reduces mobility-incurred losses by predicting the optimal data frame size for each transmission. MMAC utilizes a dynamic mobility-adaptive frame time to enhance TRAMA, a scheduled-based protocol, with mobility prediction. Likewise, G-MAC utilizes TDMA for cluster-based WSNs by combining the advantages of contention and contention-free MACs. Z-MAC also combines both methods but without clustering and allows time slot re-assignments during significant topology changes. All of the above MAC protocols are reviewed in detail.

This article reviews the state-of-the-art energy-efficient contention-based and scheduledbased medium access control (MAC) protocols for mobile sensor networks (MSNs) by first examining access schemes for wireless sensor networks (WSNs). Efficient and proper mobility handling in sensor networks provides a window of opportunity for new applications. Protocols, such as S-MAC, reduce energy consumption by putting nodes to sleep after losing to channel contention or to prevent idling. Sleeping is a common method for energyefficient MAC protocols, but delay depends on sleep duration or frame time, and longer delays lead to higher packet lost rate when nodes are unsynchronized due to network mobility. MS-MAC extends S-MAC to include mobility-awareness by decreasing this sleep duration when mobility is detected. S-MAC with extended Kalman filter (EKF) reduces mobility-incurred losses by predicting the optimal data frame size for each transmission. MMAC utilizes a dynamic mobility-adaptive frame time to enhance TRAMA, a scheduled-based protocol, with mobility prediction. Likewise, G-MAC utilizes TDMA for cluster-based WSNs by combining the advantages of contention and contention-free MACs. Z-MAC also combines both methods but without clustering and allows time slot re-assignments during significant topology changes. All of the above MAC protocols are reviewed in detail.

Previous work on the coverage of mobile sensor networks focuses on algorithms to reposition sensors in order to achieve a static configuration with an enlarged covered area. In this paper, we study the dynamic aspects of the coverage of a mobile sensor network that depend on the process of sensor movement. As time goes by, a position is more likely to be covered; targets that might never be detected in a stationary sensor network can now be detected by moving sensors. We characterize the area coverage at specific time instants and during time intervals, as well as the time it takes to detect a randomly located stationary target. Our results show that sensor mobility can be exploited to compensate for the lack of sensors and improve network coverage. For mobile targets, we take a game theoretic approach and derive optimal mobility strategies for sensors and targets from their own perspectives.

This paper investigates an application of mobile sensing: detecting and reporting the surface conditions of roads. We describe a system and associated algorithms to monitor this important civil infrastructure using a collection of sensor-equipped vehicles. This system, which we call the Pothole Patrol (P 2 ), uses the inherent mobility of the participating vehicles, opportunistically gathering data from vibration and GPS sensors, and processing the data to assess road surface conditions. We have deployed P 2 on 7 taxis running in the Boston area. Using a simple machine-learning approach, we show that we are able to identify potholes and other severe road surface anomalies from accelerometer data. Via careful selection of training data and signal features, we have been able to build a detector that misidentifies good road segments as having potholes less than 0.2% of the time. We evaluate our system on data from thousands of kilometers of taxi drives, and show that it can successfully detect a number of real potholes in and around the Boston area. After clustering to further reduce spurious detections, manual inspection of reported potholes shows that over 90% contain road anomalies in need of repair.

Mobile sensors with jumping ability provide several advantages compared with the traditional wheeled sensors such as ability to move in rugged terrain. A controllable jumping robot for this purpose is described in this paper. The robot has dimension about 9.5cm × 9cm × 3cm and weighs 54.1 grams. It can perform the jumping process continuously. This paper focuses on the mechanisms to achieve such a continuous jumping ability, including the jumping mechanism, energy store and release mechanism, and self-righting mechanism. Detail implementation and experimental results are also given in this paper. It is shown that with a 75 • takeoff angle, the robot can jump about 20cm in height.

This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of values from the network in cases of failures. We also extend DRA with a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles to form the Hierarchical-DRA (HDRA) algorithm, which enables the approximate retrieval of events from the network. Our trace-driven exper-Communicated by

In this paper, the problem of mobility handling in wireless sensor network (WSN) is studied with a simple priority backoff technique. To incorporate this technique for stationary and mobile sensor nodes, a novel hybrid MAC protocol called VMAC is designed with a fixed frame length. VMAC combines the advantages of schedule-based MAC for energy savings and contention-based MAC for short transmission delays. To exploit the bandwidth in the network, channel reuse is encouraged and is readily integrated into the protocol. Simulation results using ns2 demonstrate that VMAC with certain frame lengths are suited for selected topologies, but the frame length of one provides sufficient performance. It is also shown that the energy consumption of VMAC is roughly one-third lower compared to pure schedule-based protocol while the average delay is about two-fold less than that of contention-based protocol in one-hop communication scenarios with frame length of one; meaning that VMAC performs very well in short-range communication. The backoff technique is also shown to be fair when nodes contend for medium access and it is even resourceful in speeding up hardware address resolution and routing.

Localization schemes for wireless sensor networks can be classified as range-based or range-free. They differ in the information used for localization. Range-based methods use range measurements, while range-free techniques only use the content of the messages. None of the existing algorithms evaluate both types of information. Most of the localization schemes do not consider mobility. In this paper, a Sequential

Wireless Sensor Networks (WSNs) must be able to operate under very dynamic conditions and, in most cases, in an unattended mode leading to an autonomous network. This scenario becomes more complex when we consider that there will be probably ...

Abstract Mobile sensor networks (MSNs) consist of large number of small and computationally impoverished devices deployed over an area to track mobile objects. Mobility is becoming an important feature of MSNs. Recently, sensors have began to be ...

Mobile wireless sensors need to know their localizations in many control and monitoring applications. Among all sensors, some know their exact position (i.e., they are equipped with GPS or they are positioned by human intervention). These sensors are called anchors. Some sensors can have different capabilities allowing them to calculate either distances or angles when they receive messages from others nodes. So, they only use anchor positions to obtain an estimated position. However, when sensors are mobile they cannot continuously calculate their position because of the energy constraints. This paper concerns the localization problem in the case where all nodes in the network (anchors and others sensors) are mobile. We propose three techniques following the capabilities of nodes. Thus, each node obtains either an exact position or an approximate position with the knowledge of the maximal error born. Also, we adapt the periods where nodes invoke their localization. Simulation results show the performances of our methods in term of accuracy and determinate the technique the more adapted related to the network configurations. 1

Underwater mobile acoustic sensor networks are promising tools for the exploration of the oceans. These networks require new robust solutions for fundamental issues such as: localization service for data tagging and networking protocols for communication. All these tasks are closely related with connectivity, coverage and deployment of the network. A realistic mobility model that can capture the physical movement of the sensor nodes with ocean currents gives better understanding on the above problems. In this paper, we propose a novel physically-inspired mobility model which is representative of underwater environments. We study how the model affects a range-based localization protocol, and its impact on the coverage and connectivity of the network under different deployment scenarios.

One important problem which may arise in designing a deployment strategy for a wireless sensor network is how to deploy a specific number of sensor nodes throughout an unknown network area so that the covered section of the area is maximized. In a mobile sensor network, this problem can be addressed by first deploying sensor nodes randomly in some initial positions within the area of the network, and then letting sensor nodes to move around and find their best positions according to the positions of their neighboring nodes. The problem becomes more complicated if sensor nodes have no information about their positions or even their relative distances to each other. In this paper, we propose a cellular learning automata-based deployment strategy which guides the movements of sensor nodes within the area of the network without any sensor to know its position or its relative distance to other sensors. In the proposed algorithm, the learning automaton in each node in cooperation with the learning automata in the neighboring nodes controls the movements of the node in order to attain high coverage. Experimental results have shown that in noise-free environments, the proposed algorithm can compete with the existing algorithms such as PF, DSSA, IDCA, and VEC in terms of network coverage. It has also been shown that in noisy environments, where utilized location estimation techniques such as GPS-based devices and localization algorithms experience inaccuracies in their measurements, or the movements of sensor nodes are not perfect and follow a probabilistic motion model, the proposed algorithm outperforms the existing algorithms in terms of network coverage.

Disruption Tolerant Networking (DTN) is a new area of research to improve network communication when connectivity is periodic, intermittent, and/or prone to disruptions. A seminar on DTN was held at at Schloß Dagstuhl, Germany, from 3 to 6 April 2005. Researchers from different fields discussed their approaches to dealing with delays, intermittent connectivity, and the potential non-existence of an end-to-end path in a number of different environments. The two major areas identified were: (1) dealing with delay and disruption in the present Internet in the context of wireless, mobile, and nomadic communications, supporting existing applications and (2) addressing new applications with a focus on exploiting discontinuous connectivity and opportunistic contacts for asynchronous communications. This article briefly reviews the seminar presentations and discussions.

Distributed cognition of dynamic processes is commonly observed in mobile groups of animates like schools of fish, hunting lions, or in human teams for sports or military maneuvers. This paper presents methods for dynamic distributed cognition using an ad hoc mobile network of microsensors to detect, identify and track targets in noisy environments. We develop off-line algorithms for aggregating the most appropriate knowledge abstractions into semantic information, which is then used for on-line fusion of relevant attributes observed by local clusters in the sensor network.

The advancement of mobile sensor networks yields a variety of wireless sensor network applications. One typical application for wireless sensors networks is area monitoring in wildlife environments. Sensor networks are utilized in wildlife to track animals. A significant number of studies have been done in tracking moving targets with sensor networks. However, at this moment, we believe there is no

In this paper, we investigate coverage control problem for mobile sensor networks. The novelty is to consider an anisotropic sensor model whose performance depends not only on the distance but also on the orientation to a target point. By adapting Lloyd algorithm, a distributed control law is derived. Aside from coverage, we also show that the control law guarantees collision avoidance between the agents. The performance of the control laws is demonstrated through not only numerical simulation but also experiments on a mobile robot test bed.

This paper addresses the tradeoff between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty in order to prolong node lifetime. We use empirical GPS and radio contact data from a largescale animal tracking deployment to model node mobility, GPS and radio performance. These models are used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose a versatile contact logging strategy that relies on RSSI ranging and GPS lock back-offs for reducing the node energy consumption relative to GPS duty cycling. Results show that our strategy can cut the node energy consumption by half while meeting applicationspecific positioning criteria.

Abstract—In this work, we discuss multiplayer pervasive games that rely on the use of ad hoc mobile sensor networks. The unique feature in such games is that players interact with each other and their surrounding environment by using movement and presence as a means of ...

This paper develops a set of methods enabling an information-theoretic distributed control architecture based on particle filters to facilitate search by a mobile sensor network, permitting the use of nonlinear and non-Gaussian sensor models. Given a particular configuration sensors, this technique exploits the structure of the probability distributions of the target state and of the sensor measurements to compute the control inputs to the mobile sensors leading to future observations that minimize, in expectation, the future uncertainty of the target state. We compute the mutual information using a particle set representation of the posterior distribution. In order to control a large number of mobile sensors as a network, singlenode and pairwise-node approximation schemes are presented, with analytically bounded error, making the approach scalable to increasing network sizes, while still planning cooperatively. The methods are applied in simulation to bearings-only sensing, and to localizing an avalanche rescue beacon of a buried victim, using transceivers on quadrotor aircraft to measure the magnetic field. Monte Carlo simulations also demonstrate that as network size increases, the sensors more quickly localize the target, and the pairwise-node approximation results in superior performance to the single-node approximation.

This paper presents a comparison of cluster-based position and non position-based routing protocols for mobile wireless sensor networks to outline design considerations of protocols for mobile environments. The selected protocols are compared on the basis of multiple parameters, which include packet delivery ratio, packet loss, network lifetime, and control overhead using variable number of nodes and speeds. The extensive simulation and analysis of results show that position-based routing protocols incur less packet loss as compared to the non position based protocols. However, position-based protocols require localization mechanism or a GPS for the location information, which consumes energy and affects the network lifetime. Alternatively, non position-based protocols are more energy efficient and provide extended network lifetime.

In this paper, we propose a framework for fault repair in mobile sensor networks. A hierarchical structure which consists of replacement module, management policy module, knowledge module, decision making module, and evaluation module is adopted. We also propose a solution for faulty sensor replacement problem. Through the numerical results, we show that our algorithm is more efficient and achieves higher energy savings than the greedy approach to sensor replacement. We believe that the problem of faulty sensor nodes can be solved efficiently through the cooperation and communication across different modules, such as evaluation decision making, knowledge management, and replacement.

Mobility in wireless sensor networks poses unique challenges to the medium access control (MAC) protocol design. P~v i o u s MAC protocols for sensor networks assume static sensor nodes and focus o n energyeficiency. I n this paper, we present a mobilityadaptive, collision-free medium access control protocol (A!lh!lAC) for mobile sensor networks. MMAC caters for both weak mobility (e.g., topology changes, mode joins, and node failures) and strung mobility (e.g., concurrent node joins and failures, and physical mobility of nodes). MMAC as a scheduling-based protocol and thus it guarantees collision avoidance. MMAC allows nodes the transmission rights at particular timeslots based on th.e traffic information and mobility pattern of the nodes. Simulation results indicate that the performance of MMAC is equivalent to that of TRAMA [ l ] in static sensor network environments. I n sensor networks with mobile nodes or high network dynamics, hIMAC outperforms existing MAC protocols, like TRAMA and S-MAC 121, an t e r m s of energyeficie m y , delay, and packet delivery.

1 To turn an ideal mobile sensor network simulation model into reality, terrain is one of the inevitable factors we have to consider. This work is the first attempt to address this issue, by studying the behavior of mobile sensors under constraints of terrain. Specifically, we study the power consumption and the loss ratio of mobile sensors when they are moving on different terrains. These two metrics are utilized to select the best destinations, the best paths to the destinations, and match these destinations with mobile sensors.

In this paper, we describe a swarm-based fuzzy logic control (FLC) mobile sensor network approach for collaboratively locating the hazardous contaminants in an unknown large-scale area. The mobile sensor network is composed of a collection of distributed nodes (robots), each of which has limited sensing, intelligence and communication capabilities. An ad-hoc wireless network is established among all nodes, and each node considers other nodes as extended sensors. By gathering other nodes' locations and measurement data, each node's FLC can independently determine its next optimal deployment location. Simultaneously, by applying the three properties of the swarm behavior: separation, cohesion and alignment, the approach can ensure the sensor network attains wide regional coverage and dynamically stable connectivity. The simulation presented in this paper shows the swarm-based FLC mobile sensor network can achieve better performance and have higher fault tolerance in the event of partial node failures and sensor measurement errors.

In this paper, a new method is proposed to identify and classify the data obtained by the sensor network (SN) for the detection of mines. This method is used for the identification of antitank and antipersonnel mines and classification of buried objects within a target region. In this paper, a mobile SN is used to detect mines and some other objects buried and creating magnetic anomaly in and around the region where they are found, with the behavior of the individual sensors swarming onto the area under which a mine or any other object is buried. The process of collecting data by the SN and modeling it mathematically are explained in detail. The SN is modeled as a fictitious twodimensional spatial impulse sampler. This paper is motivated by clearing the territories of mine fields to open them to agriculture. It is very important because, currently, in some countries, very fertile territories around the borders are covered by buried mines. The approach is basically based on magnetic anomaly measurements, which directly tackles the subregions corresponding to buried objects whether they represent objects that are separately located or occluded by other objects. It is based on a new developed method that is called "the back-most object detection and identification algorithm." This method is fully automatic, and there is no human intervention throughout the process. In this paper, classification of objects is based on their well-known shapes and dimensions. Therefore, there is no need for sophisticated learning algorithms to achieve classification. The experimental results are given both for detection and identification of a single mine and classification of a number of mines and any other objects that have a potential of giving false alarms in a target region.

Meanwhile sensors are a vital part of our everyday's lives. But due to the lack of standardizing their measurement output, its information can often not be fully leveraged. With the convergence of GIS and embedded technologies the context driven usage of spatial information anytime and anywhere is one of the major challenges in broad pervasive utilization of Geographic Information Systems (GIS). The purpose of this paper is to propose a solution for integrating federally organized mobile sensor networks into GI-software. The main contribution includes a prototype embedded device system architecture for federal organized sensor networks, software components (embedded web-services) serving standardized near real-time sensor information as well as connector components for GI-software to interface and analyze this information based on open standards. The mobile prototype infrastructure, which has been practically proven in several smaller research projects, will be fully implemente...

Because of nodes mobility, one of important and fundamental issues in mobile sensor networks is how to cluster the nodes in network. The clustering is a method for best managing nodes energies, data collectting and sending information to base station and increasing network lifetime. In a wireless mobile network, the created clusters change continually and the nodes move from one cluster to another, constantly. Therefore, using fault tolerant methods capable to creating new clusters while the moving of nodes between clusters, will be necessary. One of clustering methods in mobile Ad-Hoc networks is based on neighborhood benchmark in which, the cluster heads are selected based on maximum connection degree and minimum fault in a specific time period. In this paper, the improvement of mentioned method in term of increasing network lifetime, based on its combination with minimum hop number to cluster head, will be considered. With using this new method, having symmetric and balanced-sized clusters with cluster heads that have most communications and least faults, will be possible.

In this work, we study the target detection and tracking problem in mobile sensor networks, where the performance metrics of interest are probability of detection and tracking coverage, when the target can be stationary or mobile and its duration is finite. We propose a physical coverage-based mobility model, where the mobile sensor nodes move such that the overlap between the covered areas by different mobile nodes is small. It is shown that for stationary target scenario the proposed mobility model can achieve a desired detection probability with a significantly lower number of mobile nodes especially when the detection requirements are highly stringent. Similarly, when the target is mobile the coverage-based mobility model produces a consistently higher detection probability compared to other models under investigation.

Distributed computing must adapt its techniques to networks of mobile agents. Indeed, we are facing new problems like the small size of memory and the lack of computational power. In this paper, we extend the results of Angluin et al (see [4,3,2,1]) by finding self-stabilizing algorithms to count the number of agents in the network. We focus on two different models of communication, with a fixed base station or with pairwise interactions. In both models we decide if there exist algorithms (probabilistic, deterministic, with k-fair adversary) to solve the self-stabilizing counting problem.

This paper presents fundamental results for the problem of throughput optimization in heterogeneous mobile sensor networks by considering the penalty incurred when a mobile node switches to another receiver. We present online and offline algorithms determining which receiver each mobile node connects to at each time slot to maximize total throughput. We initially consider the network setup with a single mobile sensor, and expand our solutions for two models with multiple mobile sensors and limited capacity for stationary receivers. We analyze the difficulty of our problem, and also the lower bound of the throughput ratio of our online algorithms. Simulation results demonstrate the impact of the decision parameter used to determine the propensity to switch receivers on the throughput ratio.

A methodology for surveillance of multiple targets through a distributed mobile sensor network is proposed in this paper. We examine coordination among sensors that monitor a rectangular surveillance zone that is crisscrossed by targets. After a target is detected, monitoring ...

The use of mobile sensors is of great relevance to monitor critical areas where sensors cannot be deployed manually. The presence of data collector sinks causes increased energy depletion in their proximity, due to the higher relay load under multi-hop communication schemes (sink-hole phenomenon). We propose a new approach towards the solution of this problem by means of an autonomous

Sensing coverage is an important issue in wireless mobile sensor networks. The strategy of how to deploy sensor nodes in an environment, especially in unknown large environment, will affect the utility of the network just like the quality of communication. We present an efficient method for sensor deployment assuming that global information is not available. Our algorithm (Self-Deployment by Density Control, SDDC), uses density control by each node to deploy sensor nodes concurrently. We also make nodes to form clusters ...

This paper describes the architecture and design of ParkNet, a mobile sensor network consisting of vehicles, which collects and disseminates real-time information about the availability of parking spaces in urban areas. We outline the broad challenges in real-time data collection and consumption by a mobile sensor network, as well as the design issues specific to ParkNet. Sensor nodes in ParkNet are a combination of privately owned and city owned vehicles and employ low cost ultrasonic sensors to detect the presence of vacant parking spots as they drive by. We present early results on the performance of our sensor platform.

This paper describes a new approach of using mobile sensor networks for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper first describes the design of a mobile sensing node that is capable of maneuvering on structures built with ferromagnetic materials. The mobile sensing node can also attach/detach an accelerometer onto/from the structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments. Two mobile sensing nodes are adopted for navigating on a steel portal frame and providing dense acceleration measurement. Transmissibility function analysis is conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes of using mobile sensors for future structural health monitoring.

for pervasive information gathering. We develop simple and efficient data delivery schemes tailored for DFT-MSN, which has several unique characteristics such as sensor mobility, loose connectivity, fault tolerability, delay tolerability, and buffer limit. We first study two basic approaches, namely, direct transmission and flooding. We analyze their performance by using queuing theory and statistics. Based on the analytic results that show the tradeoff between data delivery delay/ratio and transmission overhead, we introduce an optimized flooding scheme that minimizes transmission overhead in flooding. Then, we propose a simple and effective DFT-MSN data delivery scheme, which consists of two key components for data transmission and queue management, respectively. The former makes decision on when and where to transmit data messages based on the delivery probability, which reflects the likelihood that a sensor can deliver data messages to the sink. The latter decides which messages to transmit or drop based on the fault tolerance, which indicates the importance of the messages. The system parameters are carefully tuned on the basis of thorough analyses to optimize network performance. Extensive simulations are carried out for performance evaluation. Our results show that the proposed DFT-MSN data delivery scheme achieves the highest message delivery ratio with acceptable delay and transmission overhead.

In this paper, we use an integrated architecture that takes advantage of the low cost mobile sensor networks and 3G cellular networks to accommodate multimedia medical calls with differentiated Quality-of-Service (QoS) requirements. We propose a lowenergy, distributed, and concentric-zone-based data query mechanism that takes advantages of hierarchical ad hoc routing algorithms to enable a medical specialist to collect physiological data from mobile and/or remote patients. The medical specialist uses cellular network to report patients' data to the medical center. Moreover, we propose a transmission scheme among different zones with balance-based energy efficiency, which can extend network lifetime. We evaluate the validity of our proposals through simulations and analyze their performance. Our results clearly indicate the energy efficiency of the proposed sensor network query algorithms and the efficiency of our multiclass medical call admission control scheme in terms of meeting the multimedia telemedicine QoS requirements.

One of the main appeals of mobile sensors is the variety of environments in which they can operate as an autonomous network. Different environments, however, present different challenges, especially in terms of inter-sensor communication. In sparse environments, it may not be possible to maintain full connectivity at all times, setting off the need for agents to communicate opportunistically when they are close to each other. This, in turn, suggests that communication needs be taken into account in the design of agents' trajectories. In this paper, we introduce a notion of tour and meeting point as an abstraction of trajectories designed for both sensing and communication, and we study the tradeoffs involved between motion to sense and sample and motion to communicate and interact.

Vehicle-based sensors can be used for traffic monitoring. These sensors are usually set with long sampling intervals to save communication costs and to avoid network congestion. In this paper, we are interested in understanding the traffic-monitoring performance that we can expect from such vehicle-based mobile sensor networks, despite the incomplete information provided. This is a fundamental problem to be addressed. A performance evaluation has been carried out in Shanghai, China, by utilizing the vehicle-based sensors installed in about 4000 taxies. Two types of traffic status-estimation algorithms, i.e., the link-based and the vehicle-based, are introduced and analyzed. The results show that estimations of the traffic status based on these imperfect data are reasonably accurate. Therefore, the feasibility of such an application is demonstrated.