Mitigating Hot Spot Problem in Wireless Sensor Networks using Political Optimizer Based Unequal Clustering Technique

2021 ◽  
pp. 42-50
Author(s):  
Sahil Verm ◽  
◽  
Sanjukta Gain ◽  
Keyword(s):  
Hot Spot ◽  
Fitness Function ◽  
Data Gathering ◽  
Detailed Comparison ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Comparison Study ◽  
Unequal Clustering ◽  
Hot Spot Problem

Wireless Sensor Network (WSN) encompasses a set of wirelessly connected sensor nodes in the network for tracking and data gathering applications. The sensors in WSN are constrained in energy, memory, and processing capabilities. Despite the benefits of WSN, the sensors closer to the base station (BS) expels their energy faster. It suffers from hot spot issues and can be resolved by the use of unequal clustering techniques. In this aspect, this paper presents a political optimizer-based unequal clustering scheme (POUCS) for mitigating hot spot problems in WSN. The goal of the POUCS technique is to choose cluster heads (CHs) and determine unequal cluster sizes. The POUCS technique derives a fitness function involving different input parameters to minimize energy consumption and maximize the lifetime of the network. To showcase the enhanced performance of the POUCS technique, a comprehensive experimental analysis takes place, and the detailed comparison study reported the better performance of the POUCS technique over the recent techniques.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

scholarly journals Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Fan Chao ◽  
Zhiqin He ◽  
Renkuan Feng ◽  
Xiao Wang ◽  
Xiangping Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Gathering ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Center ◽  
Mobile Data ◽  
Tour Planning ◽  
Mobile Data Gathering

Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.

Type 2 Fuzzy Logic based Unequal Clustering algorithm for multi-hop wireless sensor networks

2020 ◽  
pp. 33-46
Author(s):  
A. Sariga ◽  
◽  
◽  
J. Uthayakumar
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Clustering Protocols ◽  
Hot Spot Problem

Wireless sensor network (WSN) is an integral part of IoT and Maximizing the network lifetime is a challenging task. Clustering is the most popular energy efficient technique which leads to increased lifetime stability and reduced energy consumption. Though clustering offers several advantages, it eventually raises the burden of CHs located in proximity to the Base Station (BS) in multi-hop data transmission which makes the CHs near BS die earlier than other CHs. This issue is termed as hot spot problem and unequal clustering protocols were introduced to handle it. Presently, some of the clustering protocols are developed using Type-2 Fuzzy Logic (T2FL) but none of them addresses hot spot problem. This paper presents a Type-2 Fuzzy Logic based Unequal Clustering Algorithm (T2FLUCA) for the elimination of hot spot problem and also for lifetime maximization of WSN. The proposed algorithm uses residual energy, distance to BS and node degree as input to T2FL to determine the probability of becoming CHs (PCH) and cluster size. For experimentation, T2FLUCA is tested on three different scenarios and the obtained results are compared with LEACH, TEEN, DEEC and EAUCF in terms of network lifetime, throughput and average energy consumption. The experimental results ensure that T2FLUCA outperforms state of art methods in a significant way.

A Novel Nature Instilled Moving Sink Architecture for Data Gathering in Wireless Sensor Networks

2020 ◽  
Vol 11 (1) ◽  
pp. 36-48
Author(s):  
Amiya Bhusan Bagjadab ◽  
Sushree Bibhuprada B. Priyadarshini
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Gathering ◽  
Mobile Sink ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Packet Forwarding ◽  
Battery Power ◽  
Communication Distance

Wireless sensor networks are commonly used to monitor certain regions and to collect data for several application domains. Generally, in wireless sensor networks, data are routed in a multi-hop fashion towards a static sink. In this scenario, the nodes closer to the sink become heavily involved in packet forwarding, and their battery power is exhausted rapidly. This article proposes that a special node (i.e., mobile sink) will move in the specified region and collect the data from the sensors and transmit it to the base station such that the communication distance of the sensors will be reduced. The aim is to provide a track for the sink such that it covers maximum sensor nodes. Here, the authors compared two tracks theoretically and in the future will try to simulate the two tracks for the sink movement so as to identify the better one.

scholarly journals Delay Tolerance and Energy Saving in Wireless Sensor Networks with a Mobile Base Station

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Oday Jerew ◽  
Nizar Al Bassam
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Saving ◽  
Data Gathering ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hop Count ◽  
Tour Length ◽  
Mobile Base

Recent research shows that significant energy saving can be achieved in wireless sensor networks by using mobile devices. A mobile device roams sensing fields and collects data from sensors through a short transmission range. Multihop communication is used to improve data gathering by reducing the tour length of the mobile device. In this paper we study the trade-off between energy saving and data gathering latency in wireless sensor networks. In particular, we examine the balance between the relay hop count and the tour length of a mobile Base Station (BS). We propose two heuristic algorithms, Adjacent Tree-Bounded Hop Algorithm (AT-BHA) and Farthest Node First-Bounded Hop Algorithm (FNF-BHA), to reduce energy consumption of sensor nodes. The proposed algorithms select groups of Collection Trees (CTs) and a subset of Collection Location (CL) sensor nodes to buffer and forward data to the mobile BS when it arrives. Each CL node receives sensing data from its CT nodes within bounded hop count. Extensive experiments by simulation are conducted to evaluate the performance of the proposed algorithms against another heuristic. We demonstrate that the proposed algorithms outperform the existing work with the mean of the length of mobile BS tour.

scholarly journals Energy-Efficient Wireless Sensor Network with an Unequal Clustering Protocol Based on a Balanced Energy Method (EEUCB)

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 784
Author(s):  
Ahmed A. Jasim ◽  
Mohd Yamani Idna Idris ◽  
Saaidal Razalli Bin Azzuhri ◽  
Noor Riyadh Issa ◽  
Muhammad Towfiqur Rahman ◽  
...  
Keyword(s):  
Energy Method ◽  
Energy Efficient ◽  
Hot Spot ◽  
Average Distance ◽  
Average Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Clustering Methods ◽  
Unequal Clustering ◽  
Rotation Strategy

A hot spot problem is a problem where cluster nodes near to the base station (BS) tend to drain their energy much faster than other nodes due to the need to perform more communication. Unequal clustering methods such as unequal clustering routing (UDCH) and energy-efficient fuzzy logic for unequal clustering (EEFUC) have been proposed to address this problem. However, these methods only concentrate on utilizing residual energy and the distance of sensor nodes to the base station, while limited attention is given to enhancing the data transmission process. Therefore, this paper proposes an energy-efficient unequal clustering scheme based on a balanced energy method (EEUCB) that utilizes minimum and maximum distance to reduce energy wastage. Apart from that, the proposed EEUCB also utilizes the maximum capacity of node energy and double cluster head technique with a sleep-awake mechanism. Furthermore, EEUCB has devised a clustering rotation strategy based on two sub-phases, namely intra- and inter-clustering techniques, that considers the average energy threshold, average distance threshold, and BS layering node. The performance of the proposed EEUCB protocol is then compared with various prior techniques. From the result, it can be observed that the proposed EEUCB protocol shows lifetime improvements of 57.75%, 19.63%, 14.7%, and 13.06% against low-energy adaptive clustering hierarchy (LEACH), factor-based LEACH FLEACH, EEFUC, and UDCH, respectively.

scholarly journals Enhancing Packet Delivery Ratio and a lifetime of Wireless Sensor Networks using Energy-Efficient Unequal Clustering Routing Algorithm

2019 ◽  
Vol 8 (12) ◽  
pp. 376-382
Keyword(s):  
Energy Efficient ◽  
Wireless Sensors ◽  
Base Station ◽  
Packet Delivery Ratio ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Limited Resources ◽  
Delivery Ratio ◽  
Unequal Clustering ◽  
Packet Delivery

Sensors are regarded as significant components of electronic devices. The sensor nodes deployed with limited resources, such as the power of battery inserted in the sensor nodes. So the lifetime of wireless sensor networks(WSNs) can be increased by using the energy of the sensor nodes in an efficient way. A major part of energy is consumed during the communication of data. Also, the growing demand for usage of wireless sensors applications in different aspects makes the quality-of-service(QoS) to be one of the paramount issues in wireless sensors applications. QoS guarantee in WSNs is difficult and more challenging due to the fact that the sensors have limited resources and the various applications running over these networks have different constraints in their nature and requirements. The packet delivery ratio(PDR) is a major factor of QoS. To achieve high QoS the packet delivery ratio should be maximum. The energy-efficient unequal clustering routing protocol (EEUCR) is evaluated and results show that it enhances the packet delivery ratio(PDR) and a lifetime of WSNs. In this protocol, the area of the network is divided into a number of rings of unequal size and each ring is further divided into a number of clusters. Rings nearer to the base station(BS) have smaller area and area of rings keeps on increasing as the distance from BS increases for balanced energy consumption. The nodes with heterogeneous energy are deployed in the network. Nodes nearer to the base station have higher energy as compared to farther nodes. Static clustering is used but cluster heads(CHs) are not fixed and are elected on the basis of remaining energy. This helps to increase lifetime of EEUCR. PDR of EEUCR is improved because multiple rings help to find better route which further aids to ensure safe reception of packets at the destination. Simulation results are compared with existing protocols and show that this algorithm gives better results.

scholarly journals Novel Learning Algorithms for Efficient Mobile Sink Data Collection Using Reinforcement Learning in Wireless Sensor Network

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Santosh Soni ◽  
Manish Shrivastava
Keyword(s):  
Reinforcement Learning ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Research Study ◽  
Hot Spot ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Hot Spot Problem

Generally, wireless sensor network is a group of sensor nodes which is used to continuously monitor and record the various physical, environmental, and critical real time application data. Data traffic received by sink in WSN decreases the energy of nearby sensor nodes as compared to other sensor nodes. This problem is known as hot spot problem in wireless sensor network. In this research study, two novel algorithms are proposed based upon reinforcement learning to solve hot spot problem in wireless sensor network. The first proposed algorithm RLBCA, created cluster heads to reduce the energy consumption and save about 40% of battery power. In the second proposed algorithm ODMST, mobile sink is used to collect the data from cluster heads as per the demand/request generated from cluster heads. Here mobile sink is used to keep record of incoming request from cluster heads in a routing table and visits accordingly. These algorithms did not create the extra overhead on mobile sink and save the energy as well. Finally, the proposed algorithms are compared with existing algorithms like CLIQUE, TTDD, DBRkM, EPMS, RLLO, and RL-CRC to better prove this research study.

Trust Aware Moth Flame Optimization based Secure Clustering for Wireless Sensor Networks

2019 ◽  
pp. 54-64
Author(s):  
Abdul Rahaman Wahab Sait ◽  
◽  
M. Ilayaraja ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Selection Process ◽  
Fitness Function ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Trust Level

Wireless sensor networks (WSN) encompass numerous sensor nodes deployed in the physical environment to sense parameters and transmit to the base station (BS). Since the nodes in WSN communicate via a wireless channel, security remains a significant issue that needs to be resolved. The choice of cluster heads (CHs) is critical to achieving secure data transmission in WSN. In this aspect, this article presents a novel trust-aware mothflame optimization-based secure clustering (TAMFO-SC) technique for WSN. The goal of the TAMFO-SC technique is to determine the trust level of the nodes and determine the secure CHs. The proposed TAMFO-SC technique initially determines the nodes' trust level, and the node with maximum trust factor can be chosen as CHs. In addition, the TAMFO-SC technique derives a fitness function using two parameters, namely residual energy and trust level. The inclusion of trust level in the CH selection process helps to accomplish security in WSN. A comprehensive experimental analysis exhibits the promising performance of the TAMFO-SC technique over the other compared methods.

scholarly journals Unequal clustering algorithm with IDA* multi-hop routing to prevent hot spot problem in WSNs

2020 ◽  
Vol 20 (1) ◽  
pp. 445
Author(s):  
Ahmed A. Alkadhmawee ◽  
Mohammed A. Altaha ◽  
Wisam Mahmood Lafta
Keyword(s):  
Clustering Algorithm ◽  
Hot Spot ◽  
Cluster Head ◽  
Base Station ◽  
Unequal Clustering ◽  
Term Operation ◽  
Network Cluster ◽  
Primary Means ◽  
The Stability ◽  
Hot Spot Problem

Energy conservation techniques are considered as the primary means of lengthening the lifetime of Wireless Sensor Networks (WSNs). Clustering is a useful technique that achieves long-term operation of the network. Cluster heads that are near the base station are expected to die early because they are responsible for collecting data that comes from far away in addition to their own data, thereby leading to problem of hot spot in the WSN.This paper presents a new protocol that uses an unequal clustering algorithm with an IDA* routing method to address the hot spot problem. The base station divides the network into three levels of unequal sizes of clusters. The base station takes into consideration the energy level and the distance from the base station for cluster-head selection in each cluster. The cluster head will be changed based on the energy threshold for each cluster. The proposed method uses an IDA* algorithm for efficient multi-hop routing in the network. The uneven clustering algorithm reduces the energy consumption of the nodes, thereby minimising the hot spot problem. The obtained simulation results prove that our approach increases the load balancing, improves the stability and prolongs the network lifetime compared with other related approaches.<p> </p>

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