Comparison and Performance Analysis on Clustering Scheme

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A routing protocol for multisink wireless sensor networks in underground coalmine tunnels

Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: Power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks

Energy-Aware Clustering in the Internet of Things by Using the Genetic Algorithm

Internet of things (IoT) uses a lot of key technologies to collect different types of data around the world to make an intelligent and integrated whole. This concept can be as simple as a connection between a smartphone and a smart TV, or can be complex communications between the urban infrastructure and traffic monitoring systems. One of the most challenging issues in the IoT environment is how to make it scalable and energy-efficient with regard to its growing dimensions. Object clustering is a mechanism that increases scalability and provides energy efficiency by minimizing communication energy consumption. Since IoT is a large scale dynamic environment, clustering of its objects is a NP-Complete problem. This paper formulates energy-aware clustering of things as an optimization problem targeting an optimum point in which, the total consumed energy and communication cost are minimal. Then. it employs the Genetic Algorithm (GA) to solve this optimization problem by extracting the optimal number of clusters as well as the members of each cluster. In this paper, a multi objective GA for clustering that has not premature convergence problem is used. In addition, for fast GA execution multiple implementation, considerations has been measured. Moreover, the consumed energy for received and sent data, node to node and node to BS distance have been considered as effective parameters in energy consumption formulation. Numerical simulation results show the efficiency of this method in terms of the consumed energy, network lifetime, the number of dead nodes and load balancing

Selection of Cluster Heads for Wireless Sensor Network in Ubiquitous Power Internet of Things

This paper designs a selection algorithm of cluster heads (CHs) in wireless sensor network (WSN) under the ubiquitous power Internet of Things (UPIoT), aiming to solve the network failure caused by premature death of WSN sensors and overcome the imbalance in energy consumption of sensors. The setting of the cluster head node helps to reduce the energy consumption of the nodes in the network, so the choice of cluster head is very important. The author firstly explains the low energy adaptive clustering hierarchy (LEACH) and the distance and energy based advanced LEACH (DEAL) protocol. Compared with the LEACH, the DEAL considers the remaining nodal energy and the sensor-sink distance. On this basis, the selectivity function-based CH selection (SF-CHs) algorithm was put forward to select CHs and optimize the clustering. Specifically, the choice of CHs was optimized by a selectivity function, which was established based on the remaining energy, number of neighbors, motion velocity and transmission environment of sensors. Meanwhile, a clustering function was constructed to optimize the clustering, eliminating extremely large or small clusters.Finally, the simulation proves that the DEAL protocol is more conducive to prolonging the life cycle of the sensor network. The SF-CHs algorithm can reduce the residual energy variance of nodes in the network, and the network failure time is later, which provides a way to improve the stability of the network and reduce energy loss

Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks

Connectivity is a critical issue in WSNs, as the data collected needs to be sent to the base station or the processing centers. Low connectivity due to the limited radio range of sensor nodes and random distribution leads the network to be partitioned into disconnected groups, which can interrupt or completely prevent communication between nodes. For effective communication, each node must be located close enough to each other. Improper positioning of the nodes can cause a failure in sending or receiving radio signals, resulting in a segmented or incomplete network. A Multi-Hop Selective Constructive Interference Flooding (MSCIF) protocol is proposed to address the problem of low connectivity in WSNs with a sparse distribution and improve the network’s lifetime. MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. The first step of the proposed protocol involves the development of an energy efficient clustering algorithm which is appropriate for WSN with a sparse density topology. Clustering is necessary in the proposed protocol as it helps to exclude nodes that are far away from other nodes, which consume a lot of energy. The stages of clustering are: initialization, scheduling, and clustering. The second step in MSCIF protocol involves designing a selection algorithm to select the minimum connected dominating nodes. This is to improve the network reliability and control the energy consumption by reducing the number of cooperating nodes. The third step is applying a fast-synchronized flooding to achieve a constructive interference at the receiver to improve the received signal strength and improve connectivity

Wireless sensor networks for heritage object deformation detection and tracking algorithm

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection

Research routing and MAC based on LEACH and S-MAC for energy efficiency and QoS in wireless sensor network

The wireless sensor is a micro-embedded device with weak data processing capability and small storage space. These nodes need to complete complex jobs, including data monitoring, acquisition and conversion, and data processing. Energy efficiency should be considered as one of the important aspects of the Wireless Sensor Network (WSN) throughout architecture and protocol design. At the same time, supporting Quality of Service (QoS) in WSNs is a research field, because the time-sensitive and important information is expected for the transmitting to to the sink node immediately. The thesis is supported by the projects entitled “The information and control system for preventing forest fires”, and “The Erhai information management system”, funded by the Chinese Government. Energy consumption and QoS are two main objectives of the projects. The thesis discusses the two aspects in route and Media Access Control (MAC). For energy efficiency, the research is based on Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is a benchmark clustering routing protocol which imposes upon cluster heads to complete a lot of aggregation and relay of messages to the base-station. However, there are limitations in LEACH. LEACH does not suit a wide area in clustering strategy and multi-hop routing. Moreover, routing protocols only focus on one factor, combining the clustering strategy and multi-hop routing mechanism were not considered in routing protocol for performance of network. QoS is supported by the MAC and routing protocol. Sensor MAC(S-MAC) makes the use of the periodically monitoring / sleeping mechanism, as well as collision and crosstalk avoidance mechanism. The mechanism reduces energy costs. Meanwhile, it supports good scalability and avoids the collision. However, the protocols do not take the differentiated services. For supporting QoS,A new route protocol needs to be designed and realized on embed platforms, which has WIFI mode and a Linux operation system to apply on the actual system. This research project was conducted as following the steps: A new protocol called RBLEACH is proposed to solve cluster on a widely scale based on LEACH. The area is divided into a few areas, where LEACH is improved to alter the selecting function in each area. RBLEACH creates routes selected by using a new algorithm to optimize the performance of the network. A new clustering method that has been developed to use several factors is PS-ACO-LEACH. The factors include the residual energy of the cluster head and Euclidean distances between cluster members and a cluster head. It can optimally solve fitness function and maintain a load balance in between the cluster head nodes, a cluster head and the base station. Based on the “Ant Colony” algorithm and transition of probability, a new routing protocol was created by “Pheromone” to find the optimal path of cluster heads to the base station. This protocol can reduce energy consumption of cluster heads and unbalanced energy consumption. Simulations prove that the improved protocol can enhance the performance of the network, including lifetime and energy conservation. Additionally, Multi Index Adaptive Routing Algorithm (MIA-QR) was designed based on network delay, packet loss rate and signal strength for QoS. The protocol is achieved by VC on an embedded Linux system. The MIA-QR is tested and verified by experiment and the protocol is to support QoS. Finally, an improved protocol (SMAC -SD) for wireless sensor networks is proposed, in order to solve the problem of S-MAC protocol that consider either service differentiation or ensure quality of service. According to service differentiation, SMAC-SD adopts an access mechanism based on different priorities including the adjustment of priority mechanisms of channel access probability, channel multi-request mechanisms and the configuring of waiting queues with different priorities and RTS backoff for different service, which makes the important service receive high channel access probability, ensuring the transmission quality of the important service. The simulation results show that the improved protocol is able to gain amount of important service and shortens the delay at the same time. Meanwhile, it improves the performance of the network effectivel

A distributed algorithm for semantic collectors election in wireless sensors networks

Semantic clustering is a recent technique for saving energy in wireless sensor networks. Its mechanism of action consists in dividing the network into groups (clusters) formed by semantically related nodes and at least one semantic collector, which acts as a bridge between its internal nodes and the sink node. Since semantic collector nodes need to perform more tasks than normal nodes, they deplete their energy budget faster, so it is necessary to use efficient mechanisms for electing semantic collectors to prolong the network lifetime. Our hypothesis is that an effective choice of semantic collectors allows a longer network lifetime. To test it, we start from a previous work of the authors of this article and we propose an algorithm for electing semantic collectors in a distributed way based on a fuzzy inference engine. The inputs of the inference engine are the residual energy of nodes and their received signal strength indicator (RSSI). Simulation results confirm our hypothesis, since the algorithm provides (i) an improvement of 17.4% in relation to another proposal of the related literature, and (ii) a gain of 68.8% over the time life of the network’s original work.Keywords: Wireless Sensors Networks, Semantic Cluster, Semantic Collector Election

Energy conservation in wireless sensor networks

This dissertation presents a system-level approach for minimizing the power expended in achieving communication between a ground-based sensor network and an overhead Unmanned Aerial Vehicle (UAV). A subset of sensor nodes, termed a transmit cluster, aggregates data gathered by the network and forms a distributed antenna array, concentrating the radiated transmission into a beam aimed towards the UAV. We present a method for more uniformly distributing the energy burden across the sensor network, specifying the time that should elapse between reassignments of the transmit cluster and the number of hops that should be placed between successive transmit clusters. We analyze the performance of two strategies for reconfiguring the communication burden between the sensor network and the UAV in order to bring the UAV and the sensor network's beam into alignment quickly, while minimizing the energy expenditure. We analyze the optimal number of nodes that should participate in a beamforming process in order to minimize the energy expended by the network, and we provide a framework to analyze the minimum energy expended in a simple beamforming algorithm. Finally, we analyze the probability that an arbitrarily selected sensor node is connected to a specified number of other nodes and we present an algorithm for the formation of near-linear arrays given random placement of nodes.http://archive.org/details/energyconservati1094510228Approved for public release; distribution is unlimited

Enabling sustainable power distribution networks by using smart grid communications

Smart grid modernization enables integration of computing, information and communications capabilities into the legacy electric power grid system, especially the low voltage distribution networks where various consumers are located. The evolutionary paradigm has initiated worldwide deployment of an enormous number of smart meters as well as renewable energy sources at end-user levels. The future distribution networks as part of advanced metering infrastructure (AMI) will involve decentralized power control operations under associated smart grid communications networks. This dissertation addresses three potential problems anticipated in the future distribution networks of smart grid: 1) local power congestion due to power surpluses produced by PV solar units in a neighborhood that demands disconnection/reconnection mechanisms to alleviate power overflow, 2) power balance associated with renewable energy utilization as well as data traffic across a multi-layered distribution network that requires decentralized designs to facilitate power control as well as communications, and 3) a breach of data integrity attributed to a typical false data injection attack in a smart metering network that calls for a hybrid intrusion detection system to detect anomalous/malicious activities. In the first problem, a model for the disconnection process via smart metering communications between smart meters and the utility control center is proposed. By modeling the power surplus congestion issue as a knapsack problem, greedy solutions for solving such problem are proposed. Simulation results and analysis show that computation time and data traffic under a disconnection stage in the network can be reduced. In the second problem, autonomous distribution networks are designed that take scalability into account by dividing the legacy distribution network into a set of subnetworks. A power-control method is proposed to tackle the power flow and power balance issues. Meanwhile, an overlay multi-tier communications infrastructure for the underlying power network is proposed to analyze the traffic of data information and control messages required for the associated power flow operations. Simulation results and analysis show that utilization of renewable energy production can be improved, and at the same time data traffic reduction under decentralized operations can be achieved as compared to legacy centralized management. In the third problem, an attack model is proposed that aims to minimize the number of compromised meters subject to the equality of an aggregated power load in order to bypass detection under the conventionally radial tree-like distribution network. A hybrid anomaly detection framework is developed, which incorporates the proposed grid sensor placement algorithm with the observability attribute. Simulation results and analysis show that the network observability as well as detection accuracy can be improved by utilizing grid-placed sensors. Conclusively, a number of future works have also been identified to furthering the associated problems and proposed solutions