Capacitated Graph Theoretical Algorithms for Wireless Sensor Networks Towards Internet of Things

2019 ◽  
pp. 347-382
Author(s):  
Can Umut Ileri ◽  
Yasin Yigit ◽  
Ozkan Arapoglu ◽  
Hüseyin Tolga Evcimen ◽  
Mustafa Asci ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Spanning Tree ◽  
Dominating Set ◽  
Vertex Cover ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Capacitated Minimum Spanning Tree ◽  
Main Components

Main components of internet of things such as wireless sensor networks (WSNs) are generally modeled as graphs. Matching, dominating set, spanning tree, and vertex cover are fundamental graph theoretical structures which are widely used to solve backup assignment, clustering, backbone formation, routing, link monitoring, and other important problems in WSNs. Capacitated versions of these graph theoretical problems restrict at least one feature of the original problem such as a capacity value assignment to restrict the number of cluster member that a cluster head can serve in capacitated dominating set problem, limiting the number of nodes in each subtree connected to the root in capacitated minimum spanning tree problem, etc. The general aim of these operations is to provide energy efficiency by balancing the load evenly across the nodes. In this chapter, the authors introduce important capacitated graph theoretical problems and explain both central (sequential) and distributed algorithms for constructing these structures. The operations of the algorithms are demonstrated by sample topologies.

scholarly journals E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

2020 ◽  
Vol 16 (10) ◽  
pp. 155014772096804
Author(s):  
Inam Ul Haq ◽  
Qaisar Javaid ◽  
Zahid Ullah ◽  
Zafar Zaheer ◽  
Mohsin Raza ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Internet Of Things ◽  
Packet Loss ◽  
Energy Efficient ◽  
Cluster Head ◽  
Wireless Sensor

Internet of things have emerged enough due to its applications in a wide range of fields such as governance, industry, healthcare, and smart environments (home, smart, cities, and so on). Internet of things–based networks connect smart devices ubiquitously. In such scenario, the role of wireless sensor networks becomes vital in order to enhance the ubiquity of the Internet of things devices with lower cost and easy deployment. The sensor nodes are limited in terms of energy storage, processing, and data storage capabilities, while their radio frequencies are very sensitive to noise and interference. These factors consequently threaten the energy consumption, lifetime, and throughput of network. One way to cope with energy consumption issue is energy harvesting techniques used in wireless sensor network–based Internet of things. However, some recent studies addressed the problems of clustering and routing in energy harvesting wireless sensor networks which either concentrate on energy efficiency or quality of service. There is a need of an adequate approach that can perform efficiently in terms of energy utilization as well as to ensure the quality of service. In this article, a novel protocol named energy-efficient multi-attribute-based clustering scheme (E2-MACH) is proposed which addresses the energy efficiency and communication reliability. It uses selection criteria of reliable cluster head based on a weighted function defined by multiple attributes such as link statistics, neighborhood density, current residual energy, and the rate of energy harvesting of nodes. The consideration of such parameters in cluster head selection helps to preserve the node’s energy and reduce its consumption by sending data over links possessing better signal-to-noise ratio and hence ensure minimum packet loss. The minimized packet loss ratio contributes toward enhanced network throughput, energy consumption, and lifetime with better service availability for Internet of things applications. A set of experiments using network simulator 2 revealed that our proposed approach outperforms the state-of-the-art low-energy adaptive clustering hierarchy and other recent protocols in terms of first-node death, overall energy consumption, and network throughput.

scholarly journals TLFW: A Three-Layer Framework in Wireless Rechargeable Sensor Network with a Mobile Base Station

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Anwen Wang ◽  
Xianjia Meng ◽  
Lvju Wang ◽  
Xiang Ji ◽  
Hao Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Sensor Network ◽  
Cluster Head ◽  
Mobile Station ◽  
Base Station ◽  
Wireless Sensor ◽  
Total Energy Consumption

Wireless sensor networks as the base support for the Internet of things have been a large number of popularity and application. Such as intelligent agriculture, we have to use the sensor network to obtain the growing environment data of crops and others. However, the difficulty of power supply of wireless nodes has seriously hindered the application and development of Internet of things. In order to solve this problem, people use low-power sleep scheduling and other energy-saving methods on the nodes. Although these methods can prolong the working time of nodes, they will eventually become invalid because of the exhaustion of energy. The use of solar energy, wind energy, and wireless signals in the environment to obtain energy is another way to solve the energy problem of nodes. However, these methods are affected by weather, environment, and other factors, and they are unstable. Thus, the discontinuity work of the node is caused. In recent years, the development of wireless power transfer (WPT) has brought another solution to this problem. In this paper, a three-layer framework is proposed for mobile station data collection in rechargeable wireless sensor networks to keep the node running forever, named TLFW which includes the sensor layer, cluster head layer, and mobile station layer. And the framework can minimize the total energy consumption of the system. The simulation results show that the scheme can reduce the energy consumption of the entire system, compared with a Mobile Station in a Rechargeable Sensor Network (MSiRSN).

Fault Tolerant Reliable Protocol (FTRP) Performance Evaluation in Wireless Sensor Networks: An Extensitive Study

2019 ◽  
pp. 1-36
Keyword(s):  
Wireless Sensor Networks ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Fault Tolerant ◽  
Cluster Head ◽  
Biological Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Good Performer ◽  
Wide Range

Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.

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