Advanced services in wireless sensor networks (2007)

Wireless Sensor Network (WSN) is an active area of research today. A WSN consists of a number of sensor nodes each with limited energy, bandwidth, storage, and processing capability. Sensor nodes are programmed to perform specific functions through which a user or an application can sense and interact with the environment. Towards this end, the sensor nodes are often required to communicate with one another to exchange information about physical attribute sensed in the environment. The design and implementation of a sensor network is driven by the requirements of the specific application. Applications include structural protection, healthcare monitoring, transportation system services, target tracking, environmental monitoring, habitat monitoring, etc. which can vary both in terms of the size of the area being where the nodes are deployed as well as the mobility of the nodes. As the number of WSN applications grow, network management services are necessary to meet different application requirements. We present in this dissertation a detailed survey of the recent advances and current research in WSN. We also present three important research contributions related to minimizing power consumption and maximizing the network lifetime, namely: (1) placement of network services, (2) distributed target tracking and boundary estimation, and (3) location-based active queue management. 
Communication protocols are developed to meet application-specific design goals and requirements. Network management and services are developed to enhance the sensor network performance. In our survey, we present an overview of the current sensor technologies, sensor applications, existing protocol designs, and current provisioning, management and control services. For provisioning, management and control services, we focus on issues such as localization, coverage, synchronization, network security, and data aggregation and compression. 
Placement of network services is an important problem when designing a WSN. The placement of network services can affect overall performance of the network and the lifetime of the sensor nodes. System performance may reduce if there are insufficient numbers of management and control service nodes in the network. The lifetime of sensor nodes may also reduce because of long distance communication. Thus, it is important for network services to be placed such that the total power consumed by the overall network is minimized. In our work, we consider the placement of beacons and cluster heads in a hierarchical cluster-based network. The placement of beacons in the network allows a sensor node to determine its own position while the placement of cluster heads minimizes the long distance transmission from each sensor node to the base station. To solve these two problems, we formulate an optimization problem which is solved using an Integer Linear Program (ILP). We present a detailed sensitivity analysis of the various parameters. 
WSN has many applications, one of which is target tracking and boundary estimation. Consider the problem of tracking and estimating the boundary of a substance diffusing from a mobile source using a WSN. Each sensor node senses and measures the target's position and the intensity of the chemical in the environment. The accuracy of tracking depends on the sensor node's relative position to the target and the energy used for sensing. Energy is a scarce resource in a WSN. An important goal in target tracking is to minimize energy consumption while maintaining high tracking accuracy. We propose a prediction-based mobility adaptive tracking (P-MAT) algorithm that minimizes overall energy consumption by incorporating both advanced resource reservation and adaptive tracking. With P-MAT, we study the tradeoffs between energy, accuracy of tracking, coverage, and boundary estimation. 
Applications in WSN can consist of hundreds to thousands of sensor nodes transmitting data to a single base station via multi-hop routing at the same time. In the absence of congestion control and avoidance, the network could suffer from packet loss and degradation of system performance. We propose a location-based active queue management (LB-AQM) protocol that manages a sensor node's resources and monitors congestion in the network. LB-AQM uses priority-based queue management to improve performance in congested situation. To avoid congestion, LB-AQM estimates the degree of congestion using current buffer size at a sensor node and comparing this value to two thresholds, a fixed minimum threshold and a dynamic maximum threshold, to determine the dropping probability. We study the effectiveness of our LB-AQM protocol through a simulation model.