In this thesis, we focus on topics relevant to developing and deploying large-scale wireless sensor network (WSN) applications within real dynamic urban environments. Given few reported experiences in the literature, we designed our own such network to provide a foundation for our research. The Smart Condo, a well-defined project with the goal of helping people age in place, provided the setting for our WSN that would non-intrusively monitor an occupant and environment. Although we carefully designed, developed, and deployed the network, all of our planning did not prepare us for a key challenge of that environment: significant radio-frequency interference. Most researchers tend to ignore the existence of interference along with its potentially serious implications: beyond impacting network performance, it can lead researchers to misleading or unrealistic conclusions. Interference is a particularly difficult problem to study because it varies in time, space, and intensity. Other researchers have typically approached the problem by investigating only known interferers. Instead, we approach the problem more generally and consider interference of unknown origins. We envision nodes periodically observing their environment, recognizing patterns in those observations, and responding appropriately, so we use only standard WSN nodes for our data collection. Unfortunately, collecting high-resolution data is difficult using these simple devices, and to the best of our knowledge, other researchers have only used them to collect rather coarse data. Within the Smart Condo urban environment, we recorded a transceiver's received power level at 5000 Hz, a higher rate than we encountered elsewhere in the literature, using 16 synchronized nodes. We explored traces from 256 channels and observed a number of recurring patterns; we then investigated classifying traces automatically and obtained rather promising results. We focused on the two patterns most detrimental to packet reception rates and further investigated both sampling and classification techniques tailored to them. As part of our work, we extended our simulator, making it capable of generating impulsive interference, and developed a proof-of-concept pattern-aware medium access control (MAC) protocol. Through experiments using both the simulator and WSN devices, we evaluated the classifier and proof-of-concept MAC. Our results show that impressive gains in the packet reception rates are possible when nodes can recognize and appropriately react to interference. Using our techniques, nodes can communicate more efficiently by reducing the number of failed transmissions and consequently decreasing overall network congestion.

A local reconfiguration algorithm (INP) for reliable routing in wireless sensor networks that consist of many static (fixed) energy-constrained nodes is introduced in the dissertation. For routing around crash fault nodes, a communication tree structure connecting sensor nodes to the base station (sink or root) is dynamically reconfigured during information dissemination. Unlike other location based routing approaches, INP does not take any support from a high costing system that gives position information such as GPS. For reconfigurations, INP uses only local relational information in the tree structure among nearby nodes by collaboration between the nodes that does not need global maintenance, so that INP is energy efficient and it scales to large sensor networks. The performance of the algorithm is compared to the single path with repair routing scheme (SWR) that uses a global metric and the modified GRAdient broadcast scheme (GRAB-F) that uses interleaving multiple paths by computation and by simulations. The comparisons demonstrate that using local relative information is mostly enough for reconfigurations, and it consumes less energy and mostly better delivery rates than other algorithms especially in dense environments. For the control observer to know the network health status, two new diagnosis algorithms (Repre and Local) that deal with crash faults for wireless sensor networks are also introduced in the dissertation. The control observer knows not only the static faults found by periodic testing but also the dynamic faults found by a path reconfiguration algorithm like INP that is invoked from evidence during information dissemination. With based on this information, the control observer properly treats the network without lateness. Local algorithm is introduced for providing scalability to reduce communication energy consumption when the network size grows. The performance of these algorithms is computationally compared with other crash faults identification algorithm (WSNDiag). The comparisons demonstrate that maintaining the communication tree with local reconfigurations in Repre and Local needs less energy than making a tree per each diagnosis procedure in WSNDiag. They also demonstrate that providing scalability in Local needs less energy than other approaches.

A local reconfiguration algorithm (INP) for reliable routing in wireless sensor networks that consist of many static (fixed) energy-constrained nodes is introduced in the dissertation. For routing around crash fault nodes, a communication tree structure connecting sensor nodes to the base station (sink or root) is dynamically reconfigured during information dissemination. Unlike other location based routing approaches, INP does not take any support from a high costing system that gives position information such as GPS. For reconfigurations, INP uses only local relational information in the tree structure among nearby nodes by collaboration between the nodes that does not need global maintenance, so that INP is energy efficient and it scales to large sensor networks. The performance of the algorithm is compared to the single path with repair routing scheme (SWR) that uses a global metric and the modified GRAdient broadcast scheme (GRAB-F) that uses interleaving multiple paths by computation and by simulations. The comparisons demonstrate that using local relative information is mostly enough for reconfigurations, and it consumes less energy and mostly better delivery rates than other algorithms especially in dense environments. For the control observer to know the network health status, two new diagnosis algorithms (Repre and Local) that deal with crash faults for wireless sensor networks are also introduced in the dissertation. The control observer knows not only the static faults found by periodic testing but also the dynamic faults found by a path reconfiguration algorithm like INP that is invoked from evidence during information dissemination. With based on this information, the control observer properly treats the network without lateness. Local algorithm is introduced for providing scalability to reduce communication energy consumption when the network size grows. The performance of these algorithms is computationally compared with other crash faults identification algorithm (WSNDiag). The comparisons demonstrate that maintaining the communication tree with local reconfigurations in Repre and Local needs less energy than making a tree per each diagnosis procedure in WSNDiag. They also demonstrate that providing scalability in Local needs less energy than other approaches.

Pulse synchronization is the evolution of spontaneous firing action across a network of sensor nodes. In the pulse synchronization model all nodes across a network produce a pulse, or "fire", at regular intervals even without access to a shared global time. Previous researchers have proposed the Reachback Firefly algorithm for pulse synchronization, in which nodes react to the firings of other nodes by changing their period. We propose an extension to this algorithm for tolerating arbitrary or Byzantine faults of nodes. Our algorithm queues up all the firings heard in the current cycle and discards outliers at the end of the cycle. An adjustment is computed with the remaining values and used as a starting point of the next cycle. Through simulation we validate the performance of our algorithm and study the overhead in terms of convergence time and periodicity. The simulation considers two specific kinds of Byzantine faults, the No Jump model where faulty nodes follow their own firing cycle without reacting to firings heard from other nodes and the Random Jump model where faulty nodes fire at any random time in their cycle.

Mobile robots have found numerous applications in recent years, in areas such as consumer robotics, environmental monitoring, security and transportation. For information dissemination, multi-robot cooperation or operator intervention, reliable communications are important. The combination of communication constraints with other requirements in robotics, such as navigation and obstacle avoidance is called communication-aware motion planning. To facilitate integration, communication-aware methods should fit into traditional layered architectures of motion planning. This thesis contains two main contributions, applicable to such an architecture. The first contribution is to develop strategies for exploiting multipath fading while following a reference trajectory. By deviating from the reference, a robot can stop and communicate at positions with high signal strength, trading tracking performance for link quality. We formulate this problem in three different ways: First we maximize the link quality, subject to deterministic bounds on the tracking error. We control the velocity based on the position and channel quality. Second, we consider probabilistic tracking error bounds and develop a cascaded control architecture that performs time-triggered stopping while regulating the tracking error. Third, we formulate a hybrid optimal control problem, switching between standing still to communicate and driving to improve tracking. The resulting channel quality is analyzed and we perform extensive experiments to validate the communication model and compare the proposed methods to the nominal case of driving at constant velocity. The results show good agreement with the model and improvements of over 100% in the throughput when the channel quality is low. The second contribution is to plan velocities for a group of N robots, moving along pre-determined paths through an obstacle field. Robots can only communicate if they have an unobstructed line of sight, and the problem is to maintain connectivity while traversing the paths. This is mapped to motion planning in an N-dimensional configuration space. We propose and investigate two solutions, using a rapidly exploring random tree (RRT) and an exact method inspired by cell decomposition. The RRT method scales better with the problem size than the exact method, which has a worst-case time complexity that is exponential in the number of obstacles. But the randomization in the RRT method makes it difficult to set a timeout for the solver, which runs forever if a problem instance is unsolvable. The exact method, on the other hand, detects unsolvable problem instances in finite time. The thesis demonstrates, both in theory and experiments, that mobile robots can improve communications by planning trajectories that maintain visual connectivity, or by exploiting multipath fading when there is no line of sight. The proposed methods are well suited for integration in a layered motion planning architecture. / QC 20120117

Mobile communication systems are experiencing a huge growth. While traditional communication paradigms deal with fixed networks, mobility raises a new set of questions, techniques, and solutions. This work focuses on wireless sensor networks (WSNs) where each node is a mobile device. The main objectives of this thesis have been to develop algorithms and protocols enabling WSNs with a special interest in overcoming mobility support limitations of standards such as Bluetooth and Zigbee. The contributions of this work may be divided in four major parts related to mobility support. The first part describes the implementation of local positioning services in Bluetooth since local positioning is not supported in Bluetooth v1.1. The obtained results are used in later implemented handover algorithms in terms of deciding when to perform the handover. Moreover local positioning information may be used in further developed routing protocols. The second part deals with handover as a solution to overcome the getting out of range problem. Algorithms for handover have been implemented enabling mobility in Bluetooth infrastructure networks. The principal achievement in this part is the significant reduction of handover latency since sensor cost and quality of service are directly affected by this parameter. The third part solves the routing problems originated with handovers. The main contribution of this part is the impact of the Bluetooth scatternet formation and routing protocols, for multi-hop data transmissions, in the system quality of service. The final part is a comparison between Bluetooth and Zigbee in terms of mobility support. The main outcome of this comparison resides on the conclusions, which can be used as a technology election guide. The main scientific contribution relies on the implementation of a mobile WSN with Bluetooth v1.1 inside the scope of the ”Multi Monitoring Medical Chip (M3C) for Homecare Applications” European Union project (Sixth Framework Program (FP6) Reference: 508291) offering multi-hop routing support and improvements in handover latencies with aid of local positioning services.

The main purpose of this thesis is to utilize landmarks with known coordinates and the distance between a target and landmarks to establish an objective function, and to optimize the objective function by using unconstrained direct search method to estimate the coordinate of target. A number of nodes in the sensor network serve as the landmarks according to landmark selection algorithm. Since the landmark selection algorithm is time-consuming, a simplified scheme that would improve the algorithm is to reuse the distance information that had been computed. Due to the limit of transmission range between nodes, utilizing the shortest-path distance estimation model can quickly estimate the distance between the target and non-adjacent landmarks. The main conception of the model is combining the manner of multi-hop with the shortest-path model. Due to the possible errors in distance estimation, the error per hop is considered for reducing the estimation errors. It will obviously reduce the localization errors of the target. The thesis utilizes unconstrained direct search method to optimize the objective functions such as the simplex evolutionary method (SEM), the cyclic coordinate method(CCM) and the Powell method (PM). CCM and PM will tackle the problem of finding the forward length along search direction. Hence, two schemes that combine CCM or PM with SEM are proposed to resolve the problem. Finally, simulations are conducted to generate random some nodes in an known area and to select landmarks from the nodes. Let the target be assigned in the area and do performance analysis of positioning algorithm. We discuss the performance of the positioning algorithm by considering the error per hop approach. We also discuss the effects on positioning by changing some variables such as the number of nodes, the number of landmarks and the transmission range of nodes. It is seen that the positioning errors will be reduced in examples where the number of landmark are four or the number of node are four hundred. The performance of positioning becomes accurate by reducing the distance estimation error.

Wireless sensor networks consist of many small sensor nodes with sensing, computation, and wireless communications capabilities. Recently, there have been numerous research results in the power consumption for routing protocol. Routing protocols in WSNs might difference depending on the application and network architecture. This paper focuses on reducing the power consumption for routing protocol of wireless sensor networks too. We present a routing protocol called ACRP. sensor nodes will organize many clusters voluntarily. Cluster heads will distribute time slot to the sensor nodes in the same cluster and sensor nodes will transmit data to cluster head in it¡¦s time slot. After the data had been aggregated by cluster heads, they will send the aggregated data to base station through the routing path that had been established. In addition, in order to lengthen the living time of wireless sensor network, the base station will periodically adjust the amount of sensor nodes in all clusters according to the cluster information.

Wireless sensor networks (WSNs) have a tremendous potential to improve the efficiencyof many systems, for instance, in building automation and process control.Unfortunately, the current technology does not offer guaranteed energy efficiencyand reliability for closed-loop stability. The main contribution of this thesis is toprovide a modeling, analysis, and design framework for WSN protocols used in controlapplications. The protocols are designed to minimize the energy consumption ofthe network, while meeting reliability and delay requirements from the applicationlayer. The design relies on the analytical modeling of the protocol behavior.First, modeling of the slotted random access scheme of the IEEE 802.15.4medium access control (MAC) is investigated. For this protocol, which is commonlyemployed in WSN applications, a Markov chain model is used to derive theanalytical expressions of reliability, delay, and energy consumption. By using thismodel, an adaptive IEEE 802.15.4 MAC protocol is proposed. The protocol designis based on a constrained optimization problem where the objective function is theenergy consumption of the network, subject to constraints on reliability and packetdelay. The protocol is implemented and experimentally evaluated on a test-bed. Experimentalresults show that the proposed algorithm satisfies reliability and delayrequirements while ensuring a longer lifetime of the network under both stationaryand transient network conditions.Second, modeling and analysis of a hybrid IEEE 802.15.4 MAC combining theadvantages of a random access with contention with a time division multiple access(TDMA) without contention are presented. A Markov chain is used to model thestochastic behavior of random access and the deterministic behavior of TDMA.The model is validated by both theoretical analysis and Monte Carlo simulations.Using this new model, the network performance in terms of reliability, averagepacket delay, average queueing delay, and throughput is evaluated. It is shown thatthe probability density function of the number of received packets per superframefollows a Poisson distribution. Furthermore, it is determined under which conditionsthe time slot allocation mechanism of the IEEE 802.15.4 MAC is stable.Third, a new protocol for control applications, denoted Breath, is proposedwhere sensor nodes transmit information via multi-hop routing to a sink node. Theprotocol is based on the modeling of randomized routing, MAC, and duty-cycling.Analytical and experimental results show that Breath meets reliability and delayrequirements while exhibiting a nearly uniform distribution of the work load. TheBreath protocol has been implemented and experimentally evaluated on a test-bed.Finally, it is shown how the proposed WSN protocols can be used in controlapplications. A co-design between communication and control application layers isstudied by considering a constrained optimization problem, for which the objectivefunction is the energy consumption of the network and the constraints are thereliability and delay derived from the control cost. It is shown that the optimaltraffic load when either the communication throughput or control cost are optimizedis similar. / QC 20110217

Non-parametric belief propagation (NBP) is a well-known message passing method for cooperative localization in wireless networks. However, due to the over-counting problem in the networks with loops, NBP’s convergence is not guaranteed, and its estimates are typically less accurate. One solution for this problem is non-parametric generalized belief propagation based on junction tree. However, this method is intractable in large-scale networks due to the high-complexity of the junction tree formation, and the high-dimensionality of the particles. Therefore, in this article, we propose the non-parametric generalized belief propagation based on pseudo-junction tree (NGBP-PJT). The main difference comparing with the standard method is the formation of pseudo-junction tree, which represents the approximated junction tree based on thin graph. In addition, in order to decrease the number of high-dimensional particles, we use more informative importance density function, and reduce the dimensionality of the messages. As by-product, we also propose NBP based on thin graph (NBP-TG), a cheaper variant of NBP, which runs on the same graph as NGBP-PJT. According to our simulation and experimental results, NGBP-PJT method outperforms NBP and NBP-TG in terms of accuracy, computational, and communication cost in reasonably sized networks. / COOPLOC / FP7-ICT WHERE2