Clustering Algorithm Based on the Direction of Overlapping Field of Views for Wireless Multimedia Sensor Networks

2017 ◽  
Vol 14 (1) ◽  
pp. 685-693
Author(s):  
Ahmed Salim ◽  
Hagar Ramdan

Wireless Multimedia Sensor network (WMSN) composed of multiple video cameras with possibly overlapping field of views. Node clustering for coordinating multimedia sensing and processing based on classical sensor clustering algorithms cannot enable wireless multimedia sensor nodes to sense areas that are uncorrelated to the areas covered by radio neighboring sensors. In this paper, a distributed clustering algorithm is proposed for WMSNs based on the coverage areas of the overlapped field of views (FoVs) and also on the direction of the FoV. A node may belong to multiple clusters, if its FoV intersects more than one cluster-head which affects efficiently in terms of energy conservation in sensing and processing. Simulation results show that our proposed algorithm has a more advantage in energy conservation, and in decreasing the number of singular nodes which impacts on the clustering efficiency and prolongs the network lifetime effectively.

Author(s):  
Alphonse PJA ◽  
Sivaraj C ◽  
Janakiraman T N.

Efficient energy management is a key issue in battery equipped wireless sensor networks (WSNs). The cluster based routing in WSNs is a prominent approach for energy conservation of the network which provides a hierarchical data collection mechanism. In order to maximize the energy conservation of sensor nodes, this paper proposes an Energy-efficient Layered Clustering Algorithm (ELCA) for routing in wireless sensor networks. ELCA constructs two layers of clusters to reduce the transmission rate and to balance the energy consumption of sensors. As early energy depletion of clusterheads (CHs) is a major limitation in clustering, this algorithm provides local remedy for energy suffering CHs through efficient CH substitution scheme. The performance of the proposed algorithm is analysed through extensive simulation experiments and verified by compared results with existing clustering algorithms.


2020 ◽  
pp. 238-262
Author(s):  
P. J. A. Alphonse ◽  
C. Sivaraj ◽  
T. N. Janakiraman

Efficient energy management is a key issue in battery equipped wireless sensor networks (WSNs). The cluster based routing in WSNs is a prominent approach for energy conservation of the network which provides a hierarchical data collection mechanism. In order to maximize the energy conservation of sensor nodes, this paper proposes an Energy-efficient Layered Clustering Algorithm (ELCA) for routing in wireless sensor networks. ELCA constructs two layers of clusters to reduce the transmission rate and to balance the energy consumption of sensors. As early energy depletion of clusterheads (CHs) is a major limitation in clustering, this algorithm provides local remedy for energy suffering CHs through efficient CH substitution scheme. The performance of the proposed algorithm is analysed through extensive simulation experiments and verified by compared results with existing clustering algorithms.


2017 ◽  
Vol 26 (3) ◽  
pp. 505-522
Author(s):  
Nagesha Shivappa ◽  
Sunilkumar S. Manvi

AbstractWireless multimedia sensor networks (WMSNs) are usually resource constrained, and where the sensor nodes have limited bandwidth, energy, processing power, and memory. Hence, resource mapping is required in a WMSN, which is based on user linguistic quality of service (QoS) requirements and available resources to offer better communication services. This paper proposes an adaptive neuro fuzzy inference system (ANFIS)-based resource mapping for video communications in WMSNs. Each sensor node is equipped with ANFIS, which employs three inputs (user QoS request, available node energy, and available node bandwidth) to predict the quality of the video output in terms of varying number of frames/second with either fixed or varying resolution. The sensor nodes periodically measure the available node energy and also the bandwidth. The spatial query processing in the proposed resource mapping works as follows. (i) The sink node receives the user query for some event. (ii) The sink node sends the query through an intermediate sensor node(s) and cluster head(s) in the path to an event node. A cluster head-based tree routing algorithm is used for routing. (iii) The query passes through ANFIS of intermediate sensor nodes and cluster heads, where each node predicts the quality of the video output. (iv) The event node chooses the minimum quality among all cluster heads and intermediate nodes in the path and transmits the video output. The work is simulated in different network scenarios to test the performance in terms of predicted frames/second and frame format. To the best of our knowledge, the proposed resource mapping is the first work in the area of sensor networks. The trained ANFIS predicts the output video quality in terms of number of frames/second (or H.264 video format) accurately for the given input.


2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Yongwei Zhang ◽  
Pin Wan ◽  
Shunchao Zhang ◽  
Yonghua Wang ◽  
Nan Li

In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.


2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.


2016 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Wan Isni Sofiah Wan Din ◽  
Saadiah Yahya ◽  
Mohd Nasir Taib ◽  
Ahmad Ihsan Mohd Yassin ◽  
Razulaimi Razali

Clustering in Wireless Sensor Network (WSN) is one of the methods to minimize the energy usage of sensor network. The design of sensor network itself can prolong the lifetime of network. Cluster head in each cluster is an important part in clustering to ensure the lifetime of each sensor node can be preserved as it acts as an intermediary node between the other sensors. Sensor nodes have the limitation of its battery where the battery is impossible to be replaced once it has been deployed. Thus, this paper presents an improvement of clustering algorithm for two-tier network as we named it as Multi-Tier Algorithm (MAP). For the cluster head selection, fuzzy logic approach has been used which it can minimize the energy usage of sensor nodes hence maximize the network lifetime. MAP clustering approach used in this paper covers the average of 100Mx100M network and involves three parameters that worked together in order to select the cluster head which are residual energy, communication cost and centrality. It is concluded that, MAP dominant the lifetime of WSN compared to LEACH and SEP protocols. For the future work, the stability of this algorithm can be verified in detailed via different data and energy. 


2011 ◽  
Vol 317-319 ◽  
pp. 1078-1083 ◽  
Author(s):  
Qing Tao Lin ◽  
Xiang Bing Zeng ◽  
Xiao Feng Jiang ◽  
Xin Yu Jin

This paper establishes a 3-D localization model and based on this model, it proposes a collaborative localization framework. In this framework, node that observes the object sends its attitude information and the relative position of the object's projection in its camera to the cluster head. The cluster head adopts an algorithm proposed in this paper to select some nodes to participate localization. The localization algorithm is based on least square method. Because the localization framework is based on a 3-D model, the size of the object or other prerequisites is not necessary. At the end of this paper, a simulation is taken on the numbers of nodes selected to locate and the localization accuracy. The result implies that selecting 3~4 nodes is proper. The theoretical analysis and the simulation result also imply that a const computation time cost is paid in this framework with a high localization accuracy (in our simulation environment, a 0.01 meter error).


Author(s):  
Hassan El Alami ◽  
Abdellah Najid

Energy efficiency and throughput are critical factors in the design routing protocols of WSNs. Many routing protocols based on clustering algorithm have been proposed. Current clustering algorithms often use cluster head selection and cluster formation to reduce energy consumption and maximize throughput in WSNs. In this chapter, the authors present a new routing protocol based on smart energy management and throughput maximization for clustered WSNs. The main objective of this protocol is to solve the constraint of closest sensors to the base station which consume relatively more energy in sensed information traffics, and also decrease workload on CHs. This approach divides network field into free area which contains the closest sensors to the base station that communicate directly with, and clustered area which contains the sensors that transmit data to the base station through cluster head. So due to the sensors that communicate directly to the base station, the load on cluster heads is decreased. Thus, the cluster heads consume less energy causing the increase of network lifetime.


Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3544 ◽  
Author(s):  
Md Arafat Habib ◽  
Sangman Moh

Nowadays, wireless multimedia sensor networks (WMSNs) are used in various applications. An energy-efficient and robust routing protocol is essential for WMSNs because the quality of service is important for traffic-intensive multimedia data, such as images and videos. A WMSN with multiple sinks allows cluster heads (CHs) to deliver the collected data to the nearest sink, thereby mitigating the delivery overhead. In this study, we propose a novel evolutionary-game-based routing (EGR) protocol for WMSNs with multiple sinks, in which the evolutionary game theory is exploited for selecting CHs. In EGR, an algorithm to mitigate data redundancy, based on the overlapping field of views of the multimedia sensor nodes, is also presented. This algorithm decreases the number of redundant transmissions, thereby increasing energy efficiency and network performance. According to the performance evaluation results of this study, the proposed EGR significantly outperforms the state-of-art protocols in terms of energy efficiency, end-to-end delay, packet delivery ratio, cluster formation time, and network lifetime.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Amine Rais ◽  
Khalid Bouragba ◽  
Mohammed Ouzzif

Energy is the most valuable resource in wireless sensor networks; this resource is limited and much in demand during routing and communication between sensor nodes. Hierarchy structuring of the network into clusters allows reducing the energy consumption by using small distance transmissions within clusters in a multihop manner. In this article, we choose to use a hybrid routing protocol named Efficient Honeycomb Clustering Algorithm (EHCA), which is at the same time hierarchical and geographical protocol by using honeycomb clustering. This kind of clustering guarantees the balancing of the energy consumption through changing in each round the location of the cluster head, which is in a given vertex of the honeycomb cluster. The combination of geographical and hierarchical routing with the use of honeycomb clustering has proved its efficiency; the performances of our protocol outperform the existing protocols in terms of the number of nodes alive, the latency of data delivery, and the percentage of successful data delivery to the sinks. The simulations testify the superiority of our protocol against the existing geographical and hierarchical protocols.


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