Sink-Independent Model in Wireless Sensor Networks

Wireless sensor networks generally support users that send queries and receive data via the sinks. The user and the sinks are mostly connected to each other by infrastructure networks. The users, however, should receive the data from the sinks through multi-hop communications between disseminating sensor nodes if such users move into the sensor networks without infrastructure networks. To support mobile users, previous work has studied various user mobility models. Nevertheless, such approaches are not compatible with the existing routing algorithms, and it is difficult for the mobile users to gather data efficiently due to their mobility. To improve the shortcomings, we propose a view of mobility for wireless sensor networks and propose a model to support a user mobility that is independent of sinks

Distributed Power Allocation for Sink-Centric Clusters in Multiple Sink Wireless Sensor Networks

Due to the battery resource constraints, saving energy is a critical issue in wireless sensor networks, particularly in large sensor networks. One possible solution is to deploy multiple sink nodes simultaneously. Another possible solution is to employ an adaptive clustering hierarchy routing scheme. In this paper, we propose a multiple sink cluster wireless sensor networks scheme which combines the two solutions, and propose an efficient transmission power control scheme for a sink-centric cluster routing protocol in multiple sink wireless sensor networks, denoted as MSCWSNs-PC. It is a distributed, scalable, self-organizing, adaptive system, and the sensor nodes do not require knowledge of the global network and their location. All sinks effectively work out a representative view of a monitored region, after which power control is employed to optimize network topology. The simulations demonstrate the advantages of our new protocol

On Mobility Management in Multi-Sink Sensor Networks for Geocasting of Queries

In order to efficiently deal with location dependent messages in multi-sink wireless sensor networks (WSNs), it is key that the network informs sinks what geographical area is covered by which sink. The sinks are then able to efficiently route messages which are only valid in particular regions of the deployment. In our previous work (see the 5th and 6th cited documents), we proposed a combined coverage area reporting and geographical routing protocol for location dependent messages, for example, queries that are injected by sinks. In this paper, we study the case where we have static sinks and mobile sensor nodes in the network. To provide up-to-date coverage areas to sinks, we focus on handling node mobility in the network. We discuss what is a better method for updating the routing structure (i.e., routing trees and coverage areas) to handle mobility efficiently: periodic global updates initiated from sinks or local updates triggered by mobile sensors. Simulation results show that local updating perform very well in terms of query delivery ratio. Local updating has a better scalability to increasing network size. It is also more energy efficient than ourpreviously proposed approach, where global updating in networks have medium mobility rate and speed

On Mobility Management in Multi-Sink Sensor Networks for Geocasting of Queries

In order to efficiently deal with location dependent messages in multi-sink wireless sensor networks (WSNs), it is key that the network informs sinks what geographical area is covered by which sink. The sinks are then able to efficiently route messages which are only valid in particular regions of the deployment. In our previous work (see the 5th and 6th cited documents), we proposed a combined coverage area reporting and geographical routing protocol for location dependent messages, for example, queries that are injected by sinks. In this paper, we study the case where we have static sinks and mobile sensor nodes in the network. To provide up-to-date coverage areas to sinks, we focus on handling node mobility in the network. We discuss what is a better method for updating the routing structure (i.e., routing trees and coverage areas) to handle mobility efficiently: periodic global updates initiated from sinks or local updates triggered by mobile sensors. Simulation results show that local updating perform very well in terms of query delivery ratio. Local updating has a better scalability to increasing network size. It is also more energy efficient than ourpreviously proposed approach, where global updating in networks have medium mobility rate and speed

Sink Mobility Schemes in Wireless Sensor Networks for Network Lifetime Extension

Sensor nodes in Wireless Sensor Networks (WSNs) are normally battery-powered and remain stationary after deployment. When a sensor node runs out of energy it will no longer provide sensing and data processing. This can lead to a huge loss in the network due to the routing path re-allocation and failure of sensing and reporting events in the environment. Hence energy conservation has been receiving increased attention in WSN research works. The concept of mobile sink has been recently introduced for WSNs in order to improve the overall performance of WSNs as it shifts the burden of energy consumption from the sensor nodes to sink nodes, which are typically considered to have unconstrained energy supply and larger computational power. In this thesis we present two sink mobility schemes: Load Base sink Movement (LBM) and Residual Energy Aware Routing (REAR) to prolong network lifetime in a random event-driven scenario. LBM computes the optimal tentative sink node position considering both the geographical distance from sensors to sink and transmission load of sensors as well. REAR is a routing strategy that considers the residual energy of sensors when establishing routing paths. Experimental results confirm that the proposed schemes can significantly extend the network lifetime, compared to existing techniques

A distributed data extraction and visualisation service for wireless sensor networks

With the increase in applications of wireless sensor networks, data extraction and visualisation have become a key issue to develop and operate these networks. Wireless sensor networks typically gather data at a discrete number of locations. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. The aim of this thesis is to develop a service for maximising information return from large scale wireless sensor networks. This aim will be achieved through the development of a distributed information extraction and visualisation service called the mapping service. In the distributed mapping service, groups of network nodes cooperate to produce local maps which are cached and merged at a sink node, producing a map of the global network. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisations. The proposed distributed mapping service utilises a blend of both inductive and deductive models to successfully map sense data and the universal physical principles. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of a sense modality. Furthermore, the proposed mapping service responds to changes in the environmental conditions that may impact the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a newdistributed self-adaptation algorithm, Virtual Congress Algorithm,which is based on the concept of virtual congress is proposed, with the goal of saving more power and generating more accurate data visualisation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Efficient and Practical Query Scoping in Sensor Networks

In a data-gathering sensor network with multiple sinks, it is often unnecessary and redundant for each sink to flood the entire network with its queries. We propose a simple scoping scheme with the property that a query originated at a sink will be forwarded only to the subset of nodes for whom that sink is the closest sink

Efficient and Practical Query Scoping in Sensor Networks

A driving scenario for sensor networks is environmental monitoring: nodes gather data and send it back to a sink (i.e., a basestation with an internet connection or persistent storage) via a multi-hop tree topology. In order to form the data-gathering tree, and in order to configure the sensor nodes, the sink periodically disseminates messages into the network. For scaling, robustness, and load-balancing reasons, it is desirable to introduce multiple sinks and have nodes send data to their closest sink (under a metric, such as hop-count or energy cost) rather than all nodes sending to a unique sink. With multiple sinks, it becomes important to constrain dissemination of queries so that each sink does not flood the whole network. In this work we propose Voronoi scoping, a distributed algorithm to constrain the dissemination of messages from different sinks. It has the property that a query originated by a given sink will be forwarded only to the nodes for which that sink is the closest sink (under the chosen metric). Thus each query is forwarded to the smallest possible number of nodes, and per-node dissemination overhead does not grow with network size or with number of sinks. The algorithm has a simple distributed implementation and requires only a few bytes of state at each node. Experiments over a network of 55 motes confirm the algorithm's effectiveness