Movement-based Group Awareness with Wireless Sensor Networks

We propose a method through which dynamic sensor nodes determine that they move together, by communicating and correlating their movement information. We describe two possible solutions, one using inexpensive tilt switches, and another one using low-cost MEMS accelerometers. We implement a fast, incremental correlation algorithm, with an execution time of 6ms, which can run on resource constrained devices. The tests with the implementation on real sensor nodes show that the method is reliable and distinguishes between joint and separate movements. In addition, we analyze the scalability from four different perspectives: communication, energy, memory and execution speed. The solution using tilt switches proves to be simpler, cheaper and more energy efficient, while the accelerometer-based solution is more reliable, more robust to sensor alignment problems and, potentially, more accurate by using extended features, such as speed and distance

Online Movement Correlation of Wireless Sensor Nodes

Sensor nodes can autonomously form ad-hoc groups based on their common context. We propose a solution for grouping sensor nodes attached on the same vehicles on wheels. The nodes periodically receive the movement data from their neighbours and calculate the correlation coefficients over a time history. A high correlation coefficient implies that the nodes are moving together. We demonstrate the algorithm using two types of movement sensors: tilt switches and MEMS accelerometers. We place the nodes on two wirelessly controlled toy cars, and we observe in real-time the group membership via the LED colours of the nodes. In addition, a graphical user interface running on the base station shows the movement signals over a recent time history, the latest sampled data, the correlation between each two nodes and the group membership

Distributed Service Discovery for Heterogeneous Wireless Sensor Networks

Service discovery in heterogeneous Wireless Sensor Networks is a challenging research objective, due to the inherent limitations of sensor nodes and their extensive and dense deployment. The protocols proposed for ad hoc networks are too heavy for sensor environments. This paper presents a resourceaware solution for the service discovery problem, which exploits the heterogeneous nature of the sensor network and alleviates the high-density problem from the flood-based approaches. The idea is to organize nodes into clusters, based on the available resources and the dynamics of nodes. The clusterhead nodes act as a distributed directory of service registrations. Service discovery messages are exchanged among the nodes in the distributed directory. The simulation results show the performance of the service discovery protocol in heterogeneous dense environments

Demo Abstract: Service Oriented Wireless Sensor Networks - A Cluster-based Approach

In this paper we demonstrate a service-oriented solution for heterogeneous WSNs. The main operations are service discovery and service usage. Our solution is integrated with mobile platforms (smartphones and PDAs), that act as gateways to the GSM network and the Internet

Performance Evaluation of a Cluster-Based Service Discovery Protocol for Heterogeneous Wireless Sensor Networks

Abstract—This paper evaluates the performance in terms of resource consumption of a service discovery protocol proposed for heterogeneous Wireless Sensor Networks (WSNs). The protocol is based on a clustering structure, which facilitates the construction of a distributed directory. Nodes with higher capabilities are chosen to be clusterheads. We measure the energy and memory costs depending on the capabilities and the roles of the nodes in the clustering structure, both during the maintenance of the structure and discovery of services. We show that the service discovery protocol succeeds in alleviating the resource-lean sensor nodes of heavy tasks, while delegating more consuming duties to the more powerful nodes

Cluster-based service discovery for heterogeneous wireless sensor networks

We propose an energy-efficient service discovery protocol for heterogeneous wireless sensor networks that interact with the users in open and dynamic environments. Our solution exploits a cluster overlay, where the clusterhead nodes form a distributed service registry. A service lookup results in visiting only the clusterhead nodes. We aim for minimising the communication costs during discovery of services and maintenance of a functional distributed service registry. To achieve these objectives we propose a clustering algorithm which makes decisions based on 1-hop neighbourhood information, avoids chain reactions and constructs a set of sparsely distributed clusterheads. We analyse how the properties of the clustering structure influence the performance of the service discovery protocol, by comparing theoretically and through simulations our proposed clustering algorithm with distributed mobility-adaptive clustering (DMAC). To validate our simulations we implement the proposed solution on resource-constraint sensor nodes and we measure the performance of the protocol running on different testbeds