Maggie X. Cheng

Wireless Sensor Networks with Energy Efficient Organization

A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend the operational time. One important class of wireless sensor applications of deployment of large number of sensors in an area for environmental monitoring. The data collected by the sensors is sent to a central node for processing. In this paper we propose an efficient method to achieve energy savings by organizing the sensor nodes into a maximum number of disjoint dominating sets (DDS) which are activated successively. Only the sensors from the active set are responsible for monitoring the target area and for disseminating the collected data. All other nodes are into a sleep mode, characterized by a low energy consumption. We define the maximum disjoint dominating sets problem and we design a heuristic that computes the sets. Theoretical analysis and performance evaluation results are presented to verify our approach.

Bio-inspired node localization in wireless sensor networks

Many applications of wireless sensor networks (WSNs) require location information of the randomly deployed nodes. A common solution to the localization problem is to deploy a few special beacon nodes having location awareness, which help the ordinary nodes to localize. In this approach, non-beacon nodes estimate their locations using noisy distance measurements from three or more non-collinear beacons they can receive signals from. In this paper, the ranging-based localization task is formulated as a multidimensional optimization problem, and addressed using bio-inspired algorithms, exploiting their quick convergence to quality solutions. An investigation on distributed iterative localization is presented in this paper. Here, the nodes that get localized in an iteration act as references for remaining nodes to localize. The problem has been addressed using particle swarm optimization (PSO) and bacterial foraging algorithm (BFA). A comparison of the performances of PSO and BFA in terms of the number of nodes localized, localization accuracy and computation time is presented.

Joint routing and link rate allocation under bandwidth and energy constraints in sensor networks

In sensor networks, both energy and bandwidth are scarce resources. In the past, many energy efficient routing algorithms have been devised in order to maximize network lifetime, in which wireless link bandwidth has been optimistically assumed to be sufficient. This article shows that ignoring the bandwidth constraint can lead to infeasible routing solutions. As energy constraint affects how data should be routed, link bandwidth also affects not only the routing topology but also the allowed data rate on each link. In this paper, we discuss the sufficient condition on link bandwidth that makes a routing solution feasible, then provide mathematical optimization models to tackle both energy and bandwidth constraints.We first present a basic mathematical model to address using uniform transmission power for routing without data aggregation, then extend it to handle nonuniform transmission power, and then routing with data aggregation. We propose two efficient heuristics to compute the routing topology and link data rate. Simulation results show that these heuristics provide more feasible routing solutions than previous work, and provide significant improvement on throughput and lifetime.

Cross-Layer Throughput Optimization With Power Control in Sensor Networks

In wireless sensor networks, transmission power has a significant impact on network throughput as wireless interference increases with transmission power, and interference negatively impacts the network throughput. In this paper, we try to improve the network throughput through cross-layer optimization. We first present two algorithms to compute the transmission power of each node with the objectives of minimizing the total transmission power and minimizing the total interference, respectively, from which we can obtain a network topology that ensures a connected path from each source to the sink; then, we compute the maximum achievable throughput from the obtained topology by using joint routing and link rate control. The power control algorithms can generate symmetric links or asymmetric links if so desired. Based on different link models, we use different algorithms to compute the maximum achievable throughput. Since computing the maximum throughput is an NP-hard problem, we use efficient heuristics that use a sufficient condition instead of the computationally expensive-to-get optimal condition to capture the mutual conflict relation in a collision domain. The formal proof for the sufficient condition is provided, and the proposed algorithms are compared with previous work. Simulation results show that the proposed algorithms improve the network throughput and reduce the energy consumption, with significant improvement over previous work on both aspects.

Cross-Layer Schemes for Reducing Delay in Multihop Wireless Networks

End-to-end delay is an important QoS metric in multihop wireless networks such as sensor networks and mesh networks. End-to-end delay is defined as the total time it takes for a single packet to reach the destination. It is a result of many factors including the length of the route and the interference level along the path. In this paper we address how to minimize end-to-end delay jointly through optimizing routing and link layer scheduling. We present two cross-layer schemes, a loosely coupled cross-layer scheme and a tightly coupled cross-layer scheme. In the loosely coupled cross-layer scheme, routing is computed first and then the information of routing is used for link layer scheduling; in the tightly coupled scheme, routing and link scheduling are solved in one optimization model. The two cross-layer schemes involve interference modeling in multihop wireless networks with omnidirectional antenna. A sufficient condition on conflict-free transmission is established, which can be transformed to polynomial-sized linear constraints, and a linear program based on the sufficient condition is developed. Through simulation, we show that the proposed routing and scheduling schemes can outperform their counterparts in each layer, and the integrated cross-layer schemes are superior to the combination of the existing routing and scheduling schemes.

Transmission Scheduling in Sensor Networks via Directed Edge Coloring

This paper presents a transmission scheduling scheme in sensor networks. Each node is assigned a list of time slots to use for unicast and broadcast communication. The algorithm employs edge coloring on a directed graph for transmission scheduling. It is different from previous works that use vertex coloring of a graph for node scheduling, or those that use edge coloring of undirected graphs for link scheduling. The proposed algorithm uses the least number of time slots compared to its counterparts and it avoids both the hidden terminal problem and the exposed terminal problem in both unicast and broadcast communication.

Maximum lifetime coverage preserving scheduling algorithms in sensor networks

In wireless sensor networks, when each target is covered by multiple sensors, sensors can take turns to monitor the targets in order to extend the lifetime of the network. In this paper, we address how to improve network lifetime through optimal scheduling of sensor nodes. We present two algorithms to achieve the maximum lifetime while maintaining the required coverage: a linear programming-based exponential-time exact solution, and an approximation algorithm. Numerical simulation results from the approximation algorithm are compared to the exact solution and show a high degree of accuracy and efficiency.

Energy-efficient data gathering algorithm in sensor networks with partial aggregation

In sensor networks, data aggregation at intermediate nodes can significantly reduce redundant data and reduce communication load. However, there are scenarios where data aggregation is restricted. In this paper, we study the problem of building an energy-efficient tree structure that can be used for both aggregate data and non-aggregate data. Such a tree provides a transition between the optimal solutions for both aggregate data and for non-aggregate data. A single parameter can be used to control the transition. We proposed a new algorithm Balanced Aggregation Tree (BAT) for tree construction and also suggested how to determine the value of the control parameter for the highest energy efficiency of a given network.

Link Activity Scheduling for Minimum End-to-End Latency in Multihop Wireless Sensor Networks

End-to-end delay is an important QoS metric in sensor networks as well as any application that involves transferring of small-sized files. In this paper, we address how to minimize the end-to-end delay in a multihop wireless network. End-to-end delay is defined as the total time it takes for a single packet to reach the destination. It is a result of many factors including the length of the routing path and the interference level along the path. In this paper we present a transmission scheduling scheme that minimizes the end-to-end delay along a given route. The link scheduling scheme is based on integer linear programming and involves interference modeling. Using this schedule, there are no conflicting transmissions at any time. Through simulation, we show that the proposed link scheduling scheme can significantly reduce end-to- end latency regardless of the routing algorithm used.

Link Rate Allocation under Bandwidth and Energy Constraints in Sensor Networks

In sensor networks, both energy and bandwidth are scarce resources. In the past, the energy efficient routing problem has been vastly studied in order to maximize network lifetime, but link bandwidth has been optimistically assumed to be abundant. As energy constraint affects how data should be routed, link bandwidth also affects not just the routing topology but also the allowed data rate on each link, which in turn affects lifetime. Previous works that focus on energy efficient operations in sensor networks with the sole objective of maximizing network lifetime only consider the energy constraint and ignore the bandwidth constraint. This article shows how infeasible these solutions could be if bandwidth does become a constraint, then provides a new mathematical model to tackle both energy and bandwidth constraints. Two efficient heuristics are proposed based on this model; Simulation results show these heuristics provide more feasible routing solutions than previous works, and provide significant improvement on throughput.