Effective Node Clustering and Data Dissemination In Large-Scale Wireless Sensor Networks

The denseness and random distribution of large-scale WSNs makes it quite difficult to replace or recharge nodes. Energy efficiency and management is a major design goal in these networks. In addition, reliability and scalability are two other major goals that have been identified by researchers as necessary in order to further expand the deployment of such networks for their use in various applications. This thesis aims to provide an energy efficient and effective node clustering and data dissemination algorithm in large-scale wireless sensor networks. In the area of clustering, the proposed research prolongs the lifetime of the network by saving energy through the use of node ranking to elect cluster heads, contrary to other existing cluster-based work that selects a random node or the node with the highest energy at a particular time instance as the new cluster head. Moreover, a global knowledge strategy is used to maintain a level of universal awareness of existing nodes in the subject area and to avoid the problem of disconnected or forgotten nodes. In the area of data dissemination, the aim of this research is to effectively manage the data collection by developing an efficient data collection scheme using a ferry node and applying a selective duty cycle strategy to the sensor nodes. Depending on the application, mobile ferries can be used for collecting data in a WSN, especially those that are large in scale, with delay tolerant applications. Unlike data collection via multi-hop forwarding among the sensing nodes, ferries travel across the sensing field to collect data. A ferry-based approach thus eliminates, or minimizes, the need for the multi-hop forwarding of data, and as a result, energy consumption at the nodes will be significantly reduced. This is especially true for nodes that are near the base station as they are used by other nodes to forward data to the base station. MATLAB is used to design, simulate and evaluate the proposed work against the work that has already been done by others by using various performance criteria

From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites

In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxy–graphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5

A survey of network lifetime maximization techniques in wireless sensor networks

Emerging technologies, such as the Internet of things, smart applications, smart grids and machine-to-machine networks stimulate the deployment of autonomous, selfconfiguring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteri

ASURVEY ON CLUSTER BASED LOAD BALANCINGAPPROACHESFOR WIRELESSSENSOR NETWORK

Wireless sensor network (WSN) is becoming a very interesting field of research in recent days. It has wide area of research due to various issues caused by the hardware capabilities of sensing nodes such as memory, power, and computing capabilities. One of the major issues is to concentrate on the energy consumption of the sensing node which determines the lifetime of the network. One of such problem is called Hot-spot problem, in which the best channel to the sink are overloaded with traffic and thus causing the nodes to deplete their energy quicker than the energy of other nodes in the network. Clustering algorithms along with sink mobility widely support for equal distribution of the load in the network. In order to overcome this problem various load balancing algorithms are discussed for improving the lifetime of the network

On demand multicast routing in wireless sensor networks

The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs

On demand multicast routing in wireless sensor networks

The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs

Integrated placement and routing of relay nodes for fault-tolerant hierarchical sensor networks

In two-tiered sensor networks, using higher-powered relay nodes as cluster heads has been shown to lead to further improvements in network performance. Placement of such relay nodes focuses on achieving specified coverage and connectivity requirements with as few relay nodes as possible. Existing placement strategies typically are unaware of energy dissipation due to routing and are not capable of optimizing the routing scheme and placement concurrently. We, in this thesis, propose an integrated integer linear program (ILP) formulation that determines the minimum number of relay nodes, along with their locations and a suitable communication strategy such that the network has a guaranteed lifetime as well as ensuring the pre-specified level of coverage (ks) and connectivity (kr). We also present an intersection based approach for creating the initial set of potential relay node positions, which are used by our ILP, and evaluate its performance under different conditions. Experimental results on networks with hundreds of sensor nodes show that our approach leads to significant improvement over existing energy-unaware placement schemes

Performance optimization of wireless sensor networks for remote monitoring

Wireless sensor networks (WSNs) have gained worldwide attention in recent years because of their great potential for a variety of applications such as hazardous environment exploration, military surveillance, habitat monitoring, seismic sensing, and so on. In this thesis we study the use of WSNs for remote monitoring, where a wireless sensor network is deployed in a remote region for sensing phenomena of interest while its data monitoring center is located in a metropolitan area that is geographically distant from the monitored region. This application scenario poses great challenges since such kind of monitoring is typically large scale and expected to be operational for a prolonged period without human involvement. Also, the long distance between the monitored region and the data monitoring center requires that the sensed data must be transferred by the employment of a third-party communication service, which incurs service costs. Existing methodologies for performance optimization of WSNs base on that both the sensor network and its data monitoring center are co-located, and therefore are no longer applicable to the remote monitoring scenario. Thus, developing new techniques and approaches for severely resource-constrained WSNs is desperately needed to maintain sustainable, unattended remote monitoring with low cost. Specifically, this thesis addresses the key issues and tackles problems in the deployment of WSNs for remote monitoring from the following aspects. To maximize the lifetime of large-scale monitoring, we deal with the energy consumption imbalance issue by exploring multiple sinks. We develop scalable algorithms which determine the optimal number of sinks needed and their locations, thereby dynamically identifying the energy bottlenecks and balancing the data relay workload throughout the network. We conduct experiments and the experimental results demonstrate that the proposed algorithms significantly prolong the network lifetime. To eliminate imbalance of energy consumption among sensor nodes, a complementary strategy is to introduce a mobile sink for data gathering. However, the limited communication time between the mobile sink and nodes results in that only part of sensed data will be collected and the rest will be lost, for which we propose the concept of monitoring quality with the exploration of sensed data correlation among nodes. We devise a heuristic for monitoring quality maximization, which schedules the sink to collect data from selected nodes, and uses the collected data to recover the missing ones. We study the performance of the proposed heuristic and validate its effectiveness in improving the monitoring quality. To strive for the fine trade-off between two performance metrics: throughput and cost, we investigate novel problems of minimizing cost with guaranteed throughput, and maximizing throughput with minimal cost. We develop approximation algorithms which find reliable data routing in the WSN and strategically balance workload on the sinks. We prove that the delivered solutions are fractional of the optimum. We finally conclude our work and discuss potential research topics which derive from the studies of this thesis