scholarly journals Increased Network Lifetime and Load Balancing Based on Network Interface Average Power Metric for RPL

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 48686-48696
Author(s):  
Hermano Pereira ◽  
Guilherme Luiz Moritz ◽  
Richard Demo Souza ◽  
Anelise Munaretto ◽  
Mauro Fonseca
Keyword(s):  
Load Balancing ◽  
Network Lifetime ◽  
Average Power ◽  
Network Interface

scholarly journals CAPNet: An Enhanced Load Balancing Clustering Algorithm for Prolonging Network Lifetime in WSNs

2014 ◽  
Vol 10 (2) ◽  
pp. 234394 ◽  
Author(s):  
Mucheol Kim ◽  
Sunhong Kim ◽  
Jiwan Seo ◽  
Kiseok Choi ◽  
Sangyong Han
Keyword(s):  
Load Balancing ◽  
Network Lifetime ◽  
Clustering Algorithm

scholarly journals Portable Library of Migratable Sockets

2001 ◽  
Vol 9 (4) ◽  
pp. 211-222 ◽  
Author(s):  
Marian Bubak ◽  
Dariusz Żbik ◽  
Dick van Albada ◽  
Kamil Iskra ◽  
Peter Sloot
Keyword(s):  
Parallel Computing ◽  
Distributed Computing ◽  
Load Balancing ◽  
High Performance ◽  
Internal Communication ◽  
Network Interface ◽  
Prototype Implementation ◽  
Computing Environments ◽  
User Space ◽  
Socket Interface

Efficient load balancing is essential for parallel distributed computing. Many parallel computing environments use TCP or UDP through the socket interface as a communication mechanism. This paper presents the design and development of a prototype implementation of a network interface that can preserve communication between processes during process migration. This new communication library is a substitution for the well-known socket interface. It is implemented in user — space; it is portable, and no modifications of user applications are required. TCP/IP is applied for internal communication, which guarantees relatively high performance and portability.

scholarly journals An Energy Efficient Clustering based Distributed Load Balancing Technique for Mobile Adhoc Networks

2019 ◽  
Vol 8 (9) ◽  
pp. 1869-1877
Keyword(s):  
Energy Efficiency ◽  
Load Balancing ◽  
Network Lifetime ◽  
Fault Tolerant ◽  
Mobile Nodes ◽  
Battery Lifetime ◽  
Mobile Adhoc Network ◽  
Distributed Load ◽  
Adhoc Network ◽  
Energy Efficient Clustering

In a mobile adhoc network (MANET), energy efficiency and mobility prediction are the two main challenging design issues due to the mobile nature of the nodes in any direction with limited battery lifetime, thus leads to adequate topology modifications. These two issues are mainly considered to maximize the lifetime of MANET. Load-balancing and reliable data transmission among the mobile nodes is mandatory to increase the network lifetime. To achieve this, clustering techniques can be employed to minimize the topology size and to aggregate the details related to the topology. In this paper, we introduce a new clustering based distributed load balancing (D-CALB) algorithm to maximize energy efficiency and network lifetime. Furthermore, a fault tolerant feature is included in the D-CALB algorithm, which maintains a secondary CH as a backup node in case of the failure of the present CH. The presented ZXCD- CALB algorithm has undergone an extensive set of experimentation under a varying number of nodes and speed. The detailed investigation of the experimental results verified the superior nature of the presented D-CALB algorithm over compared ones under several measures.

scholarly journals Zone-based Energy Efficient Routing Protocols for Wireless Sensor Networks

2019 ◽  
Vol 20 (1) ◽  
pp. 55-70
Author(s):  
Rajan Sharma ◽  
Balwinder Singh Sohi ◽  
Nitin Mittal
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Residual Energy ◽  
Total Energy Consumption ◽  
Energy Efficient Routing ◽  
Phase Zone ◽  
Zone Formation ◽  
Competitive Algorithms

This paper proposes a novel zone or grid-based network deployment framework for energy efficient selection and reselection process of Zone-Head (ZH) in the WSNs. The proposed zone head reselection process ensures energy efficiency, load balancing, and stability which further prolongs the network lifetime. Instead of carrying out periodic reselection of Zone-Head (ZH) that leads to extra energy consumption and network overhead, the protocol dynamically initiates the process of reselection based on residual energy level of ZH. In the proposed approach the process is segregated into four phases; deployment phase, the zone formation phase, zone head selection phase, data transmission phase and reselection phase. We implemented the proposed algorithm in MATLAB and its result outcomes reveal that the proposed method outperforms the competitive algorithms for parameters such as load balancing, total energy consumption and network lifetime.

Improvement of network lifetime performance using load balancing clustering and super clustering approach

2020 ◽  
Author(s):  
Sandeep Srivastava ◽  
Shubham Joshi ◽  
Ritesh Rastogi ◽  
Sayamuddin Ahmed Jilani ◽  
Neeraj Kumar
Keyword(s):  
Load Balancing ◽  
Network Lifetime ◽  
Lifetime Performance ◽  
Clustering Approach

Energy Aware Better Implementation of Load Balancing in Cloud Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Alekhya Orugonda ◽  
V. Kiran Kumar
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Power Consumption ◽  
Virtual Machines ◽  
Average Power ◽  
Power Saving ◽  
System Level ◽  
Energy Aware ◽  
Physical Machine ◽  
Average Power Consumption

Background: It is important to minimize bandwidth that improves battery life, system reliability and other environmental concerns and energy optimization.It also do everything within their power to reduce the amount of data that flows through their pipes.To increase resource exertion, task consolidation is an effective technique, greatly enabled by virtualization technologies, which facilitate the concurrent execution of several tasks and, in turn, reduce energy consumption. : MaxUtil, which aims to maximize resource exertion, and Energy Conscious Task Consolidation which explicitly takes into account both active and idle energy consumption. Method: In this paper an Energy Aware Cloud Load Balancing Technique (EACLBT) is proposed for the performance improvement in terms of energy and run time. It predicts load of host after VM allocation and if according to prediction host become overloaded than VM will be created on different host. So it minimize the number of migrations due to host overloading conditions. This proposed technique results in minimize bandwidth and energy utilization. Results: The result shows that the energy efficient method has been proposed for monitor energy exhaustion and support static and dynamic system level optimization.The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving.Besides minimization in bandwidth along with energy exertion, reduction in the number of executed instructions is also achieved. Conclusion: This paper comprehensively describes the EACLBT (Energy Aware Cloud Load Balancing Technique) to deploy the virtual machines for power saving purpose. The average power consumption is used as performance metrics and the result of PALB is used as baseline. The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving. It shown that on average an idle server consumes approximately 70% of the power consumed by the server running at the full CPU speed.The performance holds better for Common sub utterance elimination. So, we can say the proposed Energy Aware Cloud Load Balancing Technique (EACLBT) is effective in bandwidth minimization and reduction of energy exertion.

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