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

Data collection algorithm for wireless sensor networks using collaborative mobile elements

The simplest approach to reduce network latency for data gathering in wireless sensor networks (WSN) is to use multiple mobile elements rather than a single mobile sink. However, the most challneging issues faced this approach are firstly the high network cost as a result of using large number of mobile elements. Secondly, it suffers from the difficulty of network partitioning to achieve an efficient load balancing among these mobile elements. In this study, a collaborative data collection algorithm (CDCA) is developed. Simulation results presented in this paper demonstrated that with this algorithm the latency is significantly reduced at small number of mobile elements. Furthermore, the performance of CDCA algorithm is compared with the Area Splitting Algorithm (ASA). Consequently, the CDCA showed superior performance in terms of network latency, load balancing, and the required number of mobile elements

Enhanced VGDRA for Dynamic WSN

Sensor Nodes are fundamental blocks of Wireless Sensor Networks. The focus of researchers is still on reducing the energy dissipation by the sensor nodes over time. Sensor nodes once deployed have a fixed amount of energy available to them. In order to use the energy efficiently the sensor nodes are grouped together based on the tasks performed by them. These groups of sensor nodes are known as clusters. Each cluster is headed by a cluster head connecting the cluster with the base station. Energy consumption is directly proportional to the distance from the base station. The concept of network lifetime is closely related to the energy consumption and area coverage in wireless sensor network. The main aim of the proposed technique is to select cluster heads in such a way that they extend the network lifetime and increase throughput of the network. The efficiency of the proposed cluster head selection technique is that it covers energy consumption and routes selection for data delivery from sensor node to the base station. In this paper an Enhanced Virtual Grid-based Dynamic Routes Adjustment Scheme is proposed presenting a set of rules for the selection of cluster heads in such a way that the energy consumption by the cluster heads is balanced throughout the network and it does not get over exploited

Mobility in wireless sensor networks : advantages, limitations and effects

The primary aim of this thesis is to study the benefits and limitations of using a mobile base station for data gathering in wireless sensor networks. The case of a single mobile base station and mobile relays are considered. A cluster-based algorithm to determine the trajectory of a mobile base station for data gathering within a specified delay time is presented. The proposed algorithm aims for an equal number of sensors in each cluster in order to achieve load balance among the cluster heads. It is shown that there is a tradeoff between data-gathering delay and balancing energy consumption among sensor nodes. An analytical solution to the problem is provided in terms of the speed of the mobile base station. Simulation is performed to evaluate the performance of the proposed algorithm against the static case and to evaluate the distribution of energy consumption among the cluster heads. It is demonstrated that the use of clustering with a mobile base station can improve the network lifetime and that the proposed algorithm balances energy consumption among cluster heads. The effect of the base station velocity on the number of packet losses is studied and highlights the limitation of using a mobile base station for a large-scale network. We consider a scenario where a number of mobile relays roam through the sensing field and have limited energy resources that cannot reach each other directly. A routing scheme based on the multipath protocol is proposed, and explores how the number of paths and spread of neighbour nodes used by the mobile relays to communicate affects the network overhead. We introduce the idea of allowing the source mobile relay to cache multiple routes to the destination through its neighbour nodes in order to provide redundant paths to destination. An analytical model of network overhead is developed and verified by simulation. It is shown that the desirable number of routes is dependent on the velocity of the mobile relays. In most cases the network overhead is minimized when the source mobile relay caches six paths via appropriately distributed neighbours at the destination. A new technique for estimating routing-path hop count is also proposed. An analytical model is provided to estimate the hop count between source-destination pairs in a wireless network with an arbitrary node degree when the network nodes are uniformly distributed in the sensing field. The proposed model is a significant improvement over existing models, which do not correctly address the low-node density situation

Software defined communication framework for smart grid to meet energy demands in smart cities

In smart cities, the electricity is an essential component since it preserves a certain level of residents' life quality and provisions the entire spectrum of their economic activities. Thus, a smart way is essential to develop cities without disregarding energy issues. In this scope, the smart grid paradigm offers power supply in an efficient, sustainable and economical manner with minimal impact on the environment and can meet the future energy demands. However, real-time monitoring and control of the smart grid (SG) for continuous and quality-aware power supply in smart cities (SCs) is challenging and requires an advanced quality of service (QoS)-aware communication framework. In this context, this research aims to present a novel data-gathering scheme by using the Internet of software-defined mobile sinks (SDMSs) and wireless sensor networks (WSNs) in the smart grid. The extensive simulation results conducted through the EstiNet9.0 indicate that the designed scheme outperforms existing approaches and achieves its defined goals for events-drive applications in the SG

A Cluster–based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN

Envoy Node Identification (ENI) and Halting Location Identifier (HLI) algorithms have been developed to reduce the travel time of Mobile Element (ME) by determining Optimal Path(OP) in Wireless Sensor Networks. Data generated by cluster members will be aggregated at the Cluster Head (CH) identified by ENI for onward transmission to the ME and it likewise decides an ideal path for ME by interfacing all CH/Envoy Nodes (EN). In order to reduce the tour length (TL) further HLI determines finest number of Halting Locations that cover all ENs by taking transmission range of CH/ENs into consideration. Impact of ENI and HLI on energy consumption and travel time of ME have been examined through simulations

Design of Three-Tiered Sensor Networks with a Mobile Data Collector under Energy and Buffer Constraints

A sensor network consists of a network with a large number of sensor nodes deployed around some phenomenon to gather information. Since the nature of sensor nodes is that their energy is limited, many techniques focus on addressing the problem of minimizing the energy consumption in order to extend the network lifetime. One approach is to deploy relay nodes. However, the requirement to transmit over large distances leads to a high rate of energy dissipation. Therefore, mobile data collectors are introduced to resolve this problem. In this thesis, we present an Integer Linear Programming formulation that takes different parameters into consideration to determine an optimal relay node placement scheme in networks with a mobile data collector, which ensures that there is no data loss and the energy dissipation does not exceed a specified level. The simulation results show that our formulation can significantly extend the network lifetime and provide Quality of Service