scholarly journals Energy-Efficient Probabilistic Routing Algorithm for Internet of Things

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Sang-Hyun Park ◽  
Seungryong Cho ◽  
Jung-Ryun Lee
Keyword(s):  
Internet Of Things ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Network Performance ◽  
Routing Algorithm ◽  
Distributed Networks ◽  
Residual Energy ◽  
Aodv Protocol ◽  
Probabilistic Routing ◽  
Key Factor

In the future network with Internet of Things (IoT), each of the things communicates with the others and acquires information by itself. In distributed networks for IoT, the energy efficiency of the nodes is a key factor in the network performance. In this paper, we propose energy-efficient probabilistic routing (EEPR) algorithm, which controls the transmission of the routing request packets stochastically in order to increase the network lifetime and decrease the packet loss under the flooding algorithm. The proposed EEPR algorithm adopts energy-efficient probabilistic control by simultaneously using the residual energy of each node and ETX metric in the context of the typical AODV protocol. In the simulations, we verify that the proposed algorithm has longer network lifetime and consumes the residual energy of each node more evenly when compared with the typical AODV protocol.

scholarly journals Secure and Energy Efficient Data Transaction in WSN through SSCHS Routing Protocol

2021 ◽  
Vol 9 (10) ◽  
pp. 1015-1021
Author(s):  
R. Soundarya
Keyword(s):  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Network Performance ◽  
Cluster Formation ◽  
Cluster Head ◽  
Residual Energy ◽  
Delivery Ratio ◽  
Cluster Head Selection ◽  
Election Process

Abstract: Wireless sensor networks are widely used due to its usage and advantages because it can utilize in mission critical tasks. One of the major issues in WSN is reliable data delivery without any loss and to increase network lifetime by utilizing energy efficient process. The objective of this work is to increase network lifetime at the same time ensuring high packet delivery ratio. Clustering is one of the best methods to increase network lifetime, however election process of cluster head will consume energy and reduces network performance. Therefore in proposed work, energy efficient cluster based routing protocol has been implemented which includes residual energy and distance as major parameter to form cluster. Cluster head selection will be a static process, once cluster is formed cluster head will be selected through election process after transaction the residual energy in CH will be checked with the threshold value and same CH will again act as head this reduces cluster formation and election process. In addition to provide secure data transaction MD5 algorithm has been implemented. Attack based data loss is also reduced and concentrated in proposed work to achieve objective of this work. Keywords: (SSCHS) Secure static cluster head selection, network lifetime, cluster, MD5 and Static cluster head.

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 An Efficient Leader Node Selection for Movable Nodes in WSN using PSO Technique

2019 ◽  
Vol 8 (6) ◽  
pp. 5072-5078
Keyword(s):  
Energy Efficient ◽  
Network Performance ◽  
Clustering Algorithm ◽  
Group Formation ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Efficient Prediction ◽  
The Stability ◽  
Effective Group

Wireless Sensor Networks (WSN) is a group of sensor devices, which are used to sense the surroundings. The network performance is still an issue in the WSN and an efficient protocol is introduced such as LEACH. To improve the stability, LEACH with fuzzy descriptors is used in preceding research. However the existing has drawback with effective group formation in heterogeneous WSN and also it is not achieved the Super Leader Node (SLH). To overcome the above mentioned issues, the proposed system enhances the approach which is used for increasing the energy consumption, packet delivery ratio, and bandwidth and network lifetime. The proposed paper contains three phases such as grouping formation, Leader Node (LN) selection, SLN selection with three main objectives:(i) to acquire Energy-Efficient Prediction Clustering Algorithm (EEPCA) in heterogeneous WSN for grouping formation (ii)To design Low Energy Adaptive Clustering Hierarchy- Expected Residual Energy (LEACH-ERE) protocol for LN selection.(iii)To optimize the SCH selection by Particle Swarm Optimization (PSO) based fuzzy approach. The clustering formation is done by Energy-Efficient Prediction Clustering Algorithm (EEPCA) in heterogeneous WSN. It is used to calculate the sensor nodes which have shortest distance between each node. The LEACH-ERE protocol was proposed to form a Leader Node (LN) and all the nodes has to communicate with sink through LN only. New SLN is elected based on distance from the sink and battery power of the node.

scholarly journals Energy Efficient and Reliable Routing Algorithm for Wireless Sensors Networks

2020 ◽  
Vol 10 (5) ◽  
pp. 1885 ◽  
Author(s):  
Liangrui Tang ◽  
Zhilin Lu ◽  
Bing Fan
Keyword(s):  
Energy Efficient ◽  
Routing Algorithm ◽  
Evidence Theory ◽  
Fusion Rule ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Entropy Weight ◽  
Reliable Routing ◽  
Index Value

In energy-constrained wireless sensor networks, low energy utilization and unbalanced energy distribution are seriously affecting the operation of the network. Therefore, efficient and reasonable routing algorithms are needed to achieve higher Quality of Service (QoS). For the Dempster–Shafer (DS) evidence theory, it can fuse multiple attributes of sensor nodes with reasonable theoretical deduction and has low demand for prior knowledge. Based on the above, we propose an energy efficient and reliable routing algorithm based on DS evidence theory (DS-EERA). First, DS-EERA establishes three attribute indexes as the evidence under considering the neighboring nodes’ residual energy, traffic, the closeness of its path to the shortest path, etc. Then we adopt the entropy weight method to objectively determine the weight of three indexes. After establishing the basic probability assignment (BPA) function, the fusion rule of DS evidence theory is applied to fuse the BPA function of each index value to select the next hop. Finally, each node in the network transmits data through this routing strategy. Theoretical analysis and simulation results show that DS-EERA is promising, which can effectively prolong the network lifetime. Meanwhile, it can also reach a lower packet loss rate and improve the reliability of data transmission.

scholarly journals AOCR: adaptive on chip router algorithm for multicore domain controller platform

2018 ◽  
Vol 7 (4) ◽  
pp. 2246
Author(s):  
T Shanmuganathan ◽  
U Ramachandraiah
Keyword(s):  
Energy Efficient ◽  
Cost Reduction ◽  
Network Performance ◽  
Rapid Development ◽  
Routing Algorithm ◽  
Routing Algorithms ◽  
Core Domain ◽  
Latency Reduction ◽  
Increasing Demand ◽  
On Chip

In the recent years, with the rapid development of semiconductor technologies and increasing demand for more effective multi-Core Domain Controller platforms, there is a clear demand for effective routing algorithms that can be used to route the packets between these platforms, while enhancing an on chip network performance, achieving a better latency and throughput. This paper proposes an adaptive on Chip Router algorithm with a simple adaptive routing algorithm based on runtime weighted arbitration and resource allocation methodology, where the routing decisions are minimized for applications-specific MDCU platforms. The proposed scheme is evaluated by simulations and its performance in terms of latency, area, power consumption and cost reduction per vehicle are presented. The results show that, 24.5% of latency reduction, 62.25% area utilization optimization and 63.76% of energy efficient compare with existing methods.  

scholarly journals Green Data Gathering under Delay Differentiated Services Constraint for Internet of Things

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Mingfeng Huang ◽  
Anfeng Liu ◽  
Tian Wang ◽  
Changqin Huang
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Data Gathering ◽  
Differentiated Services ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensitive Data ◽  
Delay Sensitive ◽  
Delay Tolerant

Energy-efficient data gathering techniques play a crucial role in promoting the development of smart portable devices as well as smart sensor devices based Internet of Things (IoT). For data gathering, different applications require different delay constraints; therefore, a delay Differentiated Services based Data Routing (DSDR) scheme is creatively proposed to improve the delay differentiated services constraint that is missed from previous data gathering studies. The DSDR scheme has three advantages: first, DSDR greatly reduces transmission delay by establishing energy-efficient routing paths (E2RPs). Multiple E2RPs are established in different locations of the network to forward data, and the duty cycles of nodes on E2RPs are increased to 1, so the data is forwarded by E2RPs without the existence of sleeping delay, which greatly reduces transmission latency. Secondly, DSDR intelligently chooses transmission method according to data urgency: the direct-forwarding strategy is adopted for delay-sensitive data to ensure minimum end-to-end delay, while wait-forwarding method is adopted for delay-tolerant data to perform data fusion for reducing energy consumption. Finally, DSDR make full use of the residual energy and improve the effective energy utilization. The E2RPs are built in the region with adequate residual energy and they are periodically rotated to equalize the energy consumption of the network. A comprehensive performance analysis demonstrates that the DSDR scheme has obvious advantages in improving network performance compared to previous studies: it reduces transmission latency of delay-sensitive data by 44.31%, reduces transmission latency of delay-tolerant data by 25.65%, and improves network energy utilization by 30.61%, while also guaranteeing the network lifetime is not lower than previous studies.

An Energy-Balanced Routing Algorithm in Wireless Seismic Sensor Network

2016 ◽  
Vol 13 (10) ◽  
pp. 6823-6833
Author(s):  
Xunqian Tong ◽  
Gengfa Fang ◽  
Diep Nguyen ◽  
Jun Lin ◽  
Emerson Cabrera
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hamming Distance ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Residual Energy ◽  
Data Collector ◽  
Energy Balanced Routing ◽  
Candidate Set

Due to unpredictable geological outdoor environments and imbalances in energy consumption of seismometer nodes in the wireless seismic sensor networks (WSSN), some seismometer nodes fail much earlier than others due to power loss. This would cause hot spot problems, network partitions, and significantly shorten network lifetime. In this paper, we designed an energy-balanced routing algorithm (EBRA) to ensure balanced energy consumption from all seismometer nodes in the WSSN and to enhance the connectivity and lifetime of the WSSN. By aiming at minimizing the imbalance in the residual energy, we divide the routing algorithm into two parts: clustering formation and inter-cluster routing. In clustering formation, we design an energy-balanced clustering algorithm, which selects the cluster head dynamically, based on residual energy, distance between the seismometer node and data collector. The clustering algorithm mitigates hot spot problems by balancing energy consumption among seismometer nodes. In regards to inter-cluster routing, we can relate it to the pareto-candidate set. To reduce the average multi-hop delay from cluster heads to the data collector, we optimize the pareto-candidate set by Hamming distance. In the design of EBRA, we consider minute details such as energy consumed by transmitting bits and impact of average multi-hop delay. This adds to the novelty of this work compared to the existing studies. Simulation results demonstrated a reduction in the average multi-hop delay by 87.5% with network size of 200 nodes in ten different data collector locations. Our algorithm also improves the network lifetime over the others three schemes by 7.8%, 23% and 45.4%, respectively.

Sign in / Sign up

Export Citation Format

Share Document