In wireless sensor networks, periodic data collection appears in many applications. During data collection, messages from sensor nodes are periodically collected and sent back to a set of base stations for processing. In this article, we present and analyze a near-lifetime-optimal and scalable solution for data collection in stationary wireless sensor networks and an energy-efficient packet exchange mechanism. In our solution, instead of using a fixed network topology, we construct a set of communication topologies and apply each topology to different data collection cycles. We not only use the flexibility in distributing the traffic load across different routes in the network (spatial load balancing), but also balance the energy consumption in the time domain (temporal load balancing). We show that this method achieves an average energy consumption rate very close to the optimal value found by network flow optimization techniques. To increase the scalability, we further extend our solution such that it can be applied to networks with multiple base stations where each base station only stores part of the network configuration, cooperating with each other to find a global solution in a distributed manner. The proposed methods are analyzed and evaluated by simulations.

Immediate notification of urgent but rare events and delivery of time sensitive actuation commands appear in many practical wireless sensor and actuator network applications. Multi-parent wake-up scheduling was presented as a technique which can provide bi-directional end-to-end latency guarantees while optimizing the node battery lifetime. This method takes a cross-layer approach where multiple routes for transfer of messages and wake-up schedules for nodes are crafted in synergy to reduce overall message latencies. In this paper, we generalize the multi-parent method to support a multi-cluster model for the network where we assume that the network has multiple central points called cluster-head (CH) that are in charge of scheduling the nodes in the network. A key step in multi-parent method is to divide the nodes in network into disjoint groups such that each node has at least one link to a node in each group. We formulate this step as a graph coloring problem which is shown to be NP-complete. We propose an algorithm where all the cluster-heads cooperate to find a heuristic solution for the graph coloring optimization problem in a distributed manner. We show that each cluster-head requires less memory and computational power compared to the case where one cluster-head finds the global solution, therefore the solution is very scalable.

We consider the problem of supervision or periodic data collection for stationary wireless sensor networks and present a practical, energy-efficient, and reliable solution. Energy-efficiency is achieved by combining three design methods: (a) adopting network flow optimization techniques, the optimal scheme for balancing the communication load among all the nodes in the network is calculated. This gives the lower bound for the energy required for data collection process, (b) instead of using a fixed network topology (communication tree), a set of optimized trees is constructed and the communication tree varies over different data collection cycles. We show that this method achieves an average energy consumption rate very close to the optimal value, (c) the packet exchange procedure is designed based on collision-free schedules, to minimize the number of packets and the transmission and reception times for each node. Reliability of the process is guaranteed by including many retransmission opportunities in the schedules. The performance is evaluated through simulations.

Within a camera network, the contribution of a camera to the observation of a scene depends on its viewpoint and on the scene configuration. This is a dynamic property, as the scene content is subject to change over time. An automatic selection of a subset of cameras that significantly contributes to the desired observation of a scene can be of great value for the reduction of the amount of transmitted or stored image data. In this work, we propose low data rate schemes to select from a vision network a subset of cameras that provides a good frontal observation of the persons in the scene and allows for the best approximation of their 3D shape. We also investigate to what degree low data rates trade off quality of reconstructed 3D shapes.

We present novel techniques for localization of nodes in a wireless image sensor network. Based on visual observations of a moving object by the network nodes, the proposed techniques employ simple image processing functions to produce equations that contain the node positions and orientation angles as the unknown parameters. Observations made at the nodes relate the position of the observed object to the physical coordinates of the node via the mapped position of the object in the node's image plane. In one formulation of the problem, multiple observations by a network node from a moving beacon with known coordinates result in a system of equations with a rank-deficient matrix. Hence, the solution for the desired node coordinates lies in the null space of the data matrix. In a second formulation, a different configuration of image sensor deployment with more degrees of freedom results in a least-squares solution for the unknown parameters. In a third formulation, multiple observations are made at each node from a target which moves at a fixed velocity vector. The solution to this problem formulation is also shown to correspond to the null space of the data matrix. The proposed algorithms are based on in-node processing and hence are scalable to large networks. Simulation and experimental results are provided in the paper.

A large number of ractical sensing and actuating applications require immediate notification of rare but urgent events and also fast delivery of time sensitive actuation commands. In this a er,we consider the design of efficient wakeup scheduling schemes for energy constrained sensor nodes that adhere to the bidirectional end-to-end delay constraints posed by such applications. We evaluate several existing scheduling schemes and propose novel scheduling methods that outperform existing ones.We also resent a new family of wakeu methods,called multi-parent schemes, which take a cross-layer a roach where multiple routes for transfer of messages and wakeup schedules for various nodes are crafted in synergy to increase longevity while reducing message delivery latencies. We analyze the power-delay and lifetime-latency tradeoffs for several wakeup methods and show that our proposed techniques significantly improve the performance and allow for much longer network lifetime while satisfying the latency constraints.

We present a vision-based solution to the problem of topology discovery and localization of wireless sensor networks. In the proposed model, a robot controlled by the network is introduced to assist with localization of a network of image sensors, which are assumed to have image planes parallel to the agent's motion plane. The localization algorithm for the scenario where the moving agent has knowledge of its global coordinates is first studied. This baseline scenario is then used to build more complex localization algorithms in which the robot has no knowledge of its global positions. Two cases where the sensors have overlapping and non-overlapping fields of view (FOVs) are investigated. In order to implement the discovery algorithms for these two different cases, a forest structure is introduced to represent the topology of the network. We consider the collection of sensors with overlapping FOVs as a tree in the forest. The robot searches for nodes in each tree through boundary patrolling, while it searches for other trees by a radial pattern motion. Numerical analyses are provided to verify the proposed algorithms. Finally, experiment results show that the sensor coordinates estimated by the proposed algorithms accurately reflect the results found by manual methods

We investigate trellis coding with multiuser detection (MUD) applied in direct-sequence code-division multiple-access (DS/CDMA) communications. A generalized model called multi-sequence model is applied to systematically design the transceivers. In multi-sequence model, each user can be assigned more than one spreading sequence and the coding, modulation, and spreading sequences are jointly considered based on the extended Ungerboeck's set partitioning principle to maximize free distance. We derive the optimum detector under the maximum likelihood criterion. To measure the influence on the bit-error-rate due to coding and multiple-access interference, asymptotic multiuser coding gain (AMCG) is defined to provide lower and upper bounds for transceivers. The numerical experiments justify the precision of AMCG to evaluate system performance. Verified by numerical analysis, a transmitter designed by multi-sequence model can achieve significant coding gain over uncoded systems while applying optimum detector, and the performance of coded systems is severely degraded without MUD. Therefore, these facts not only demonstrate the value to jointly design coding, modulation, and spreading sequences in trellis-coded DS/CDMA communications but also emphasis the needs of MUD to optimize the system performance.