Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 704
Load Balancing For Hybrid LIFI And WIFI Networks
J.Roselin Suganthi1, M.Suba Pradha2, S.Sivaranjani3, S.Susiladevi4, S.S.Sathya5, S.Saravanan6
1Assistant Professor, K.Ramakrishnan College of Engineering, Trichy, Tamilnadu, India
2Assistant Professor, M.A.M School of Engineering, Trichy, Tamilnadu, India
3Assistant Professor, M.Kumarasamy College of Engineering, Karur, Tamilnadu, India
4Assistant Professor, Sri Bharathi Engineering College for Women, Pudukkottai, Tamilnadu, India
5Assistant Professor, Dhanalakshmi Srinivasan Engineering College, Perambalur, Tamilnadu, India
6Professor, Muthayammal Engineering College, Namakkal, Tamilnadu, India
ABSTRACT
The number of nodes in the world is rapidly increasing as the day-to-day communications are entirely depending on the wireless medium. This leads to the main issue of load balancing in the network. To combat this issue, mixture of LIFI and WIFI organizations are mainly emerging criteria in the wireless world. This is called hybrid LIFI and WIFI Networks which improves the framework limit of indoor remote communications. In this task, a joint advancement issue is formed, to decide an organization level determination for every client over a time of time. The proposed approach can improve framework throughput and accomplishing extremely low computational complexity. Burden adjusting turns into a difficult issue because of a total cover between the inclusion spaces of LIFI and WIFI. Shortest path algorithm and hybrid WIFI and LIFI algorithm, is formulated to determine a network-level selection for each user. The proposed approach can improve framework throughput and furthermore to stay away from the information traffic problem. Hybrid LIFI and WIFI organizations (HLWNets) are as of late proposed to improve the framework limit of indoor remote interchanges.
Keywords: Hybrid LIFI and WIFI Networks, Shortest path algorithm, load balancing algorithm.
1. INTRODUCTION
The term remote correspondence was presented in the nineteenth century and remote correspondence innovation has created over the resulting years. It is perhaps the main modes of transmission of data from one gadget to different gadgets. In this innovation, the data can be communicated through the air without requiring any link or wires[2].In the current days, remote correspondence framework has become a fundamental piece of different sorts of remote specialized devices, that grants client to convey even from far off worked zones. There are numerous gadgets utilized for remote correspondence like mobiles. Cordless phones, zigbee wireless innovation, GPS, WI-FI, satellite TV and remote PC parts. Current remote telephones incorporate 3G and 4G organizations, Bluetooth and WI-FI innovations [1]. Versatile information traffic increment between 2016 and 2021 reaching 48.3 hexa bytes each month before the finish of 2021.an indoor remote organization will represent over 80%. This will make a weight on existing WIFI, due its restricted data transfer capacity and thick business. To conquer these issues proposed to consolidate WIFI and LIFI [7]. This is known as hybrid LIFI and WIFI organizations [3]. There are numerous benefits in LIFI over WIFI.LIFI implies light devotion it sends and gets the data through light [6]. LIFI is quick transmission of information and quick web association around multiple times quicker than speeds reachable by WIFI.to stay away from load adjusting issues we join LIFI and WIFI [10][23].Load adjusting is the way toward appropriating network traffic across different servers, this guarantees no single worker bear, too much interest by spreading the work equally by improve application [11].
Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 705 2. METHODOLOGY
2.1 SHORTEST PATH ALGORITHM
For significant distance remote correspondence information sends from source to objective as parcel. Here in this calculation tracking down the most limited way between the sources to objective [4].
STEPS
1. Introduce the distance as per the calculation
2. Pick first node and figure distance to neighbouring node 3. Pick the following node with negligible distance
4. Rehash adjoining node distance estimation and track down the most limited way.[8]
2.2 HYBRID LIFI AND WIFI LOAD BALANCING ALGORITHM
This calculation looks for lightest worker in the organization and hence assigns Proper burden on it .This method conquers the heterogeneity versatile to dynamic Climate amazing in open minded and has a decent adaptability consequently help in improve the presentation of the framework.[5]
3. PROPOSED SYSTEM
In proposed system, there are 3 sorts of organization access, i) LIFI only, ii) WIFI only, LIFI or WIFI.
During the transmission of information through WIFI is feasible, only when impedance happen in that way. In the proposed work WIFI switches over to LIFI during obstruction and make the information transmission without any problem [9]. In WIFI networks, it arrives at the edge level it switches over to LIFI [10]. In proposed system, there are 3 kinds of association access, LIFI only, WIFI only, LIFI or WIFI during the transmission of data through WIFI there is practical for impedance occur in that manner[13]. In the proposed work WIFI is switch over to LIFI during impediment and make the data transmission with no issue [14]. In WIFI networks it shows up at the edge level it switch over to LIFI[15].
3.1 NETTWORK MODEL
Fig1. Network Model
Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 706
This figure1 shows Hybrid LIFI WIFI network model is contains combination of two types of networks such LIFI and WIFI.WIFI is higher area coverage network and LIFI is high speed network [16]. When interference occurs in WIFI network LIFI network will combine and reaches the destination [17]. It is used to determine a network level selection for each over a period of time.
3.2 FLOW CHART
Fig.2 shows the work flow of information from source to destination. This flowchart clearly explains the selection of network for transmission without affecting the load and the traffic.
Fig2. Flow Chart
In this process it creates the source node and destination node, and calculating the distance and load based on algorithm .There are two type of networks such as LIFI and WIFI network .when it select WIFI network it has two conditions when WIFI reached the threshold level or any interference the WIFI network chooses the LIFI network [12] .when the WIFI under threshold level it chooses WIFI and reaches the destination node. The LIFI node meets any light path blockage it chooses the WIFI network.
4. RESULTS AND DISCUSSIONS
4.1 NODE ALLOCATION
The First Step of the process is node allocation, enter number of nodes and destiontion.it allocates the node based on the network availability and shortest path algorithm.
Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 707
Fig 3. Node Allocation
This figure 3 shows node allocation it means it creates the source node and destination node. First enter number of the nodes and run the select network. Number of node is 75 and destination node is 50.then it find priority path.
4.2 PRIORITY PATH SELECTION
The second step of the process is priority path selection. It finds the shortest path for source and destination. It uses hybrid load balancing LIFI and WIFI algorithm. First it Initializes distances according to the algorithm. Pick first node and calculate distances to adjacent nodes [20][25]. Pick next node with minimal distance, repeat adjacent node distance calculations. Final result of shortest- path tree.
This Figure 4.2 shows priority path selection based on shortest path algorithm. For long distance wireless communication data send from source to destination in he form of packet.it shows priority path for all source node.
4.3 OUTPUT OF HLWNETWORKS
Fig4. Priority Path Selection
This is the output of the load balancing for hybrid LIFI and WIFI networks. Here dark line represents LIFI networks and other colour represents WIFI networks.in this project throughput is increased and delay is reduced.
Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 708
Fig5. Output of the HLWN
The figure 5 shows the output of HLWN by using shortest path and hybrid LIFI and WIFI algorithm.
When WIFI reached threshold level it switches over to LIFI. When LIFI meets any obstacles, it switches over to WIFI network. It transfers the data without any interference [21].50th node is the destination node and 54th node is source node when interference occurs in 70th is the WIFI node it switches over to 3 LIFI nodes.
4.4 DELAY ANALYSIS
This is the delay analysis of proposed system,the graph is drawn between packet and time.the delay of proposed system is reduced than existing system.it takes lesser time than other systems.
Fig 6 Delay Analysis
Figure 6 shows delay analysis of HLW networks by using shortest path and hybrid LIFI and WIFI algorithm [22]. The waveform represents decreases in delay. It reduces the amount of time taking longer than expected time.
4.5 THROUGHPUT ANALYSIS
This is the throughput analysis of the proposed system; this graph is drawn between packet and time. Packet takes lesser time than other and without any interference so it increases the throughput.
Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 709
Fig7. Throughput Analysis
The figure 7 Shows Throughput analysis Of HLW networks. Throughput is the actual amount of data that can be successfully delivered over a communication channel. The throughput increased than existing system. The graph represents increases in the throughput.
5. CONCLUSION & FUTURE SCOPE
In the rapid increase of the communication nodes in the network. The demand of increase of the population of network makes demand in the spectrum allocation of the network in the transmission. The technique employed in this paper is an appreciable way for managing the load traffic in the network. Load balancing will help in making the network in a comfortable way so that spectrum is allocated in an efficient way by choosing the appropriate network with respect to obstacles. The throughput is achieved in the accepting way and delay has been reduced in the 50% in case of delay.
REFERENCES
[1] Y. Wang and H. Haas, “Dynamic load balancing with handover in hybrid Li-Fi and Wi-Fi networks,” J. Lightw. Technol., vol. 33, no. 22, pp. 4671–4682, Nov. 15, 2015.
[2] X. Li, R. Zhang, and L. Hanzo, “Cooperative load balancing in hybrid visible light communications and WiFi,” IEEE Trans. Commun., vol. 63, no. 4, pp. 1319–1329, Apr. 2015 [3] Xiping Wu, Member, IEEE, and Harald Haas , Fellow, IEEE,” Load Balancing for Hybrid
LiFi and WiFi Networks: To Tackle User Mobility and Light-Path Blockage”, IEEE Transactions On Communications, Vol. 68, No. 3, March 2020
[4] Harald Haas,” LiFi is a paradigm-shifting 5G technology, Review in physics,”
Volume3, November 2018, Pages 26-31
[5] Hou H.W, Zhou,Tian, Shi J.L,and Vucetic.B, “Radio environment map aided Doppler shift estimation in LTE railway,” IEEETrans. Veh. Tech., to be published, doi:
10.1109/TVT.2016.2599558.
[6] S.Susiladevi M Subapradha .J Roselin Suganthi C.Malarvizhi,” Integration Of 3d Mems Accelerometer Sensor”, Annals Of The Romanian,3, 2021
[7] Sun.N, Zhao, “Distributed and dynamic resource management for wireless service delivery to high-speed trains,” IEEEAccess, vol. 5, pp. 620-632, 2017.
[8] J. Roselin Suganthi ,” Efficient Channel Utilisation in Ultra Dense Networks”, International Journal of Latest Technology in Engineering, Management & Applied Science
Annals of R.S.C.B., ISSN:1583-6258, Vol. 25, Issue 6, 2021, Pages. 704-710 Received 25 April 2021; Accepted 08 May 2021.
http://annalsofrscb.ro 710
(IJLTEMAS),Volume VII, Issue V, May 2018 | ISSN 2278-2540
[9] Wu.J and Fan.P, “A survey on high mobility wireless communications: Challenges, opportunities and solutions” IEEE Access, vol. 4,pp. 450-476, 2016.
[10] J Roselin Suganthi, J Swapna,”Vehicle Control System Using VANET”, International Journal of Modern Agriculture, 2020
[11] C Bhuvaneshwari, A Manjunathan, “Reimbursement of sensor nodes and path optimization”, Materials Today: Proceedings, 2020.
[12] Bhuvaneshwari C, Manjunathan A, “Advanced gesture recognition system using long-term recurrent convolution network”, Materials Today: Proceedings, vol. 21, pp.731-733, 2020.
[13] M Ramkumar, C Ganesh Babu, K Vinoth Kumar, D Hepsiba, A Manjunathan, R Sarath Kumar,
“ECG Cardiac arrhythmias Classification using DWT, ICA and MLP Neural Network”, Journal of Physics: Conference Series, vol.1831, issue.1, pp.012015, 2021
[14] K Balachander, G Suresh Kumaar, M Mathankumar, A Manjunathan, S Chinnapparaj,
“Optimization in design of hybrid electric power network using HOMER”, Materials Today:
Proceedings, 2020.
[15] M.D.Udayakumar, G.Anushree, J.Sathyaraj, A.Manjunathan, “The impact of advanced technological developments on solar PV value chain”, Materials Today: Proceedings, 2020.
[16] C.Vivek, S.Palanivel Rajan, "Z-TCAM : An Efficient Memory Architecture Based TCAM", Asian Journal of Information Technology, ISSN No.: 1682-3915, Vol. No.: 15, Issue : 3, pp.
448-454, 2016.
[17] Jothimani.S, Suganya.A, “Estimating Securities Exchange Utilizing Profound Neural Networks” International Journal of Grid and Distributed Computing Vol. 12, No. 3, 2019.
[18] S.Palanivel Rajan, S.Vijayprasath, “Performance Investigation of an Implicit Instrumentation Tool for Deadened Patients Using Common Eye Developments as Paradigm”, International Journal of Applied Engineering Research, Vol.10, Issue 1, pp.925-929, 2015.
[19] P T Sivagurunathan, P Ramakrishnan, “A Survey on Wearable health sensor – based system design”, International Journal of pure and applied mathematics, vol.118, issue.08, page no.383-385, 2018.
[20] A Manjunathan, A Lakshmi, S Ananthi, A Ramachandran, C Bhuvaneshwari, “Image Processing Based Classification of Energy Sources in Eatables Using Artificial Intelligence”, Annals of the Romanian Society for Cell Biology,vol.25, issue.3, pp.7401-7407, 2021.
[21] A Manjunathan, C Bhuvaneshwari, “Design of smart shoes”, Materials Today: Proceedings 21, 500-503
[22] P Matheswaran, C Navaneethan, S Meenatchi, S Ananthi, K Janaki, A Manjunathan,” Image Privacy in Social Network Using Invisible Watermarking Techniques”, Annals of the Romanian Society for Cell Biology, vol.25, issue.5, pp.319-327, 2021
[23] C Bhuvaneshwari, G Saranyadevi, R Vani, A Manjunathan, “Development of High Yield Farming using IoT based UAV”, IOP Conference Series: Materials Science and Engineering 1055 (1), 012007
[24] Manjunathan A, Suresh Kumar A, Udhayanan S, Thirumarai Selvi C, Albert Alexander Stonier, “Design of Autonomous Vehicle Control using IoT”, IOP Conference Series:
Materials Science and Engineering, vol:1055, pp:012008
[25] Manjunathan A, Indumathi K, Balasundhari G, Dharani M, “IoT technology for remote controlled watering system”, International Journal of Engineering Research & Technology, vol.5, issue 13, pp. 1-3,2017.