Reducing Power Consumption in Hexagonal Wireless Sensor Networks Using Efficient Routing Protocols

Power consumption and network lifetime are vital issues in wireless sensor network (WSN) design. This motivated us to find innovative mechanisms that help in reducing energy consumption and prolonging the lifetime of such networks. In this paper, we propose a hexagonal model for WSNs to reduce power consumption when sending data from sensor nodes to cluster heads or the sink. Four models are proposed for cluster head positioning and the results were compared with well-known models such as Power Efficient Gathering In Sensor Information Systems (PEGASIS) and Low-Energy Adaptive Clustering Hierarchy (LEACH). The results showed that the proposed models reduced WSN power consumption and network lifetime

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

An Energy Efficient, Load Balancing, and Reliable Routing Protocol for Wireless Sensor Networks

AN ENERGY EFFICIENT, LOAD BALANCING, AND RELIABLE ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS by Kamil Samara The University of Wisconsin-Milwaukee, 2016 Under the Supervision of Professor Hossein Hosseini The Internet of Things (IoT) is shaping the future of Computer Networks and Computing in general, and it is gaining ground very rapidly. The whole idea has originated from the pervasive presence of a variety of things or objects equipped with the internet connectivity. These devices are becoming cheap and ubiquitous, at the same time more powerful and smaller with a variety of onboard sensors. All these factors with the availability of unique addressing, provided by the IPv6, has made these devices capable of collaborating with each other to accomplish common tasks. Mobile AdHoc Networks (MANETS) and Wireless Sensor Networks (WSN) in particular play a major role in the backbone of IoT. Routing in Wireless Sensor Networks (WSN) has been a challenging task for researchers in the last several years because the conventional routing algorithms, such as the ones used in IP-based networks, are not well suited for WSNs because these conventional routing algorithms heavily rely on large routing tables that need to be updated periodically. The size of a WSN could range from hundreds to tens of thousands of nodes, which will make routing tables’ size very large. Managing large routing tables is not feasible in WSNs due to the limitations of resources. The directed diffusion algorithm is a well-known routing algorithm for Wireless Sensor Networks (WSNs). The directed diffusion algorithm saves energy by sending data packets hop by hop and by enforcing paths to avoid flooding. The directed diffusion algorithm does not attempt to find the best or healthier paths (healthier paths are paths that use less total energy than others and avoid critical nodes). Hence the directed diffusion algorithm could be improved by enforcing the use of healthier paths, which will result in less power consumption. We propose an efficient routing protocol for WSNs that gives preference to the healthier paths based on the criteria of the total energy available on the path, the path length, and the avoidance of critical nodes. This preference is achieved by collecting information about the available paths and then using non-incremental machine learning to enforce path(s) that meet our criteria. In addition to preferring healthier paths, our protocol provides Quality of Service (QoS) features through the implementation of differentiated services, where packets are classified as critical, urgent, and normal, as defined later in this work. Based on this classification, different packets are assigned different priority and resources. This process results in higher reliability for the delivery of data, and shorter delivery delay for the urgent and critical packets. This research includes the implementation of our protocol using a Castalia Simulator. Our simulation compares the performance of our protocol with that of the directed diffusion algorithm. The comparison was made on the following aspects: • Energy consumption • Reliable delivery • Load balancing • Network lifetime • Quality of service Simulation results did not point out a significant difference in performance between the proposed protocol and the directed diffusion algorithm in smaller networks. However, when the network’s size started to increase the results showed better performance by the proposed protocol

Target tracking in wireless sensor networks

The problem being tackled here relates to the problem of target tracking in wireless sensor networks. It is a specific problem in localization. Localization primarily refers to the detection of spatial coordinates of a node or an object. Target tracking deals with finding spatial coordinates of a moving object and being able to track its movements. In the tracking scheme illustrated, sensors are deployed in a triangular fashion in a hexagonal mesh such that the hexagon is divided into a number of equilateral triangles. The technique used for detection is the trilateration technique in which intersection of three circles is used to determine the object location. While the object is being tracked by three sensors, distance to it from a fourth sensor is also being calculated simultaneously. The difference is that closest three sensors detect at a frequency of one second while the fourth sensor detects the object location at twice the frequency. Using the distance information from the fourth sensor and a simple mathematical technique, location of object is predicted for every half second as well. The key thing to note is that the forth sensor node is not used for detection but only for estimation of the object at half second intervals and hence does not utilize much power. Using this technique, tracking capability of the system is increased. The scheme proposed can theoretically detect objects moving at speeds of up to 33 m/s unlike the paper [16] on which it is based which can detect objects moving only up to speeds of 5 m/s. While the earlier system [16] has been demonstrated with four sensors as well, but for that the arrangement of sensor nodes is a square. The technique demonstrated does not involve a change in the arrangement and utilizes the hexagonal mesh arrangement. Some other scenarios have been tackled such as when displacement of the object is zero at the end of one second. Its movement is predicted during that time interval. Also, incase an object moves in a circle, such motions are also tracked

Approach to minimizing consumption of energy in wireless sensor networks

The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime

VGDRA: A Virtual Grid-Based Dynamic Routes Adjustment Scheme for Mobile Sink-Based Wireless Sensor Networks

In wireless sensor networks, exploiting the sink mobility has been considered as a good strategy to balance the nodes energy dissipation. Despite its numerous advantages, the data dissemination to the mobile sink is a challenging task for the resource constrained sensor nodes due to the dynamic network topology caused by the sink mobility. For efficient data delivery, nodes need to reconstruct their routes toward the latest location of the mobile sink, which undermines the energy conservation goal. In this paper, we present a virtual gridbased dynamic routes adjustment (VGDRA) scheme that aims to minimize the routes reconstruction cost of the sensor nodes while maintaining nearly optimal routes to the latest location of the mobile sink. We propose a set of communication rules that governs the routes reconstruction process thereby requiring only a limited number of nodes to readjust their data delivery routes toward the mobile sink. Simulation results demonstrate reduced routes reconstruction cost and improved network lifetime of the VGDRA scheme when compared with existing work

Virtual coordinate based techniques for wireless sensor networks: a simulation tool and localization & planarization algorithms

2013 Summer.Includes bibliographical references.Wireless sensor Networks (WSNs) are deployments of smart sensor devices for monitoring environmental or physical phenomena. These sensors have the ability to communicate with other sensors within communication range or with a base station. Each sensor, at a minimum, comprises of sensing, processing, transmission, and power units. This thesis focuses on virtual coordinate based techniques in WSNs. Virtual Coordinates (VCs) characterize each node in a network with the minimum hop distances to a set of anchor nodes, as its coordinates. It provides a compelling alternative to some of the localization applications such as routing. Building a WSN testbed is often infeasible and costly. Running real experiments on WSNs testbeds is time consuming, difficult and sometimes not feasible given the scope and size of applications. Simulation is, therefore, the most common approach for developing and testing new protocols and techniques for sensor networks. Though many general and wireless sensor network specific simulation tools are available, no available tool currently provides an intuitive interface or a tool for virtual coordinate based simulations. A simulator called VCSIM is presented which focuses specifically on Virtual Coordinate Space (VCS) in WSNs. With this simulator, a user can easily create WSNs networks of different sizes, shapes, and distributions. Its graphical user interface (GUI) facilitates placement of anchors and generation of VCs. Localization in WSNs is important for several reasons including identification and correlation of gathered data, node addressing, evaluation of nodes' density and coverage, geographic routing, object tracking, and other geographic algorithms. But due to many constraints, such as limited battery power, processing capabilities, hardware costs, and measurement errors, localization still remains a hard problem in WSNs. In certain applications, such as security sensors for intrusion detection, agriculture, land monitoring, and fire alarm sensors in a building, the sensor nodes are always deployed in an orderly fashion, in contrast to random deployments. In this thesis, a novel transformation is presented to obtain position of nodes from VCs in rectangular, hexagonal and triangular grid topologies. It is shown that with certain specific anchor placements, a location of a node can be accurately approximated, if the length of a shortest path in given topology between a node and anchors is equal to length of a shortest path in full topology (i.e. a topology without any voids) between the same node and anchors. These positions are obtained without the need of any extra localization hardware. The results show that more than 90% nodes were able to identify their position in randomly deployed networks of 80% and 85% node density. These positions can then be used for deterministic routing which seems to have better avg. path length compared to geographic routing scheme called "Greedy Perimeter Stateless Routing (GPSR)". In many real world applications, manual deployment is not possible in exact regular rectangular, triangular or hexagonal grids. Due to placement constraint, nodes are often placed with some deviation from ideal grid positions. Because of placement tolerance and due to non-isotropic radio patterns nodes may communicate with more or less number of neighbors than needed and may form cross-links causing non-planar topologies. Extracting planar graph from network topologies is known as network planarization. Network planarization has been an important technique in numerous sensor network protocols--such as GPSR for efficient routing, topology discovery, localization and data-centric storage. Most of the present planarization algorithms are based on location information. In this thesis, a novel network planarization algorithm is presented for rectangular, hexagonal and triangular topologies which do not use location information. The results presented in this thesis show that with placement errors of up to 30%, 45%, and 30% in rectangular, triangular and hexagonal topologies respectively we can obtain good planar topologies without the need of location information. It is also shown that with obtained planar topology more nodes acquire unique VCs