Cloud computing based load balancing algorithm for erlang concurrent traffic

Abstract

<p>The distribution of scheduler from user inquiries in the clouds is complex. In keeping up with the cloud computing environment and the inquirers, the clouds meet with some problematic load balancing complications as an improving load balancing tool induces the rigorous efficiency of the cloud based website’s user access. Overloaded or underloaded conditions originate processing catastrophe regarding the prolonged execution time, bandwidth hog, malfunction, and etc. Besides, to manipulate Erlang concurrent tasks is another skyward situation. Hence, the load balancing is obliged to exhaust all mentioned conditions. The proposed load balancing algorithm for Erlang concurrent tasks (those are and could also be autonomous and unstable.) on VMware workstations is introduced. There are several load patterns within the clouds corresponding to CPU’s load (utilization), memory load (queue size), link capacity load (bandwidth), and so on. The proposed load balancing is to spot underloaded and overloaded conditions then stabilizes the weight amidst computing nodes. There are countless load balancing approaches in the cloud environment to examine performance parameters. A short outline of corresponding performance metrics in the review and their findings are presented. To investigate the fit efficiency of the proposed algorithm, the simulation is applied then results based on the proposed method are compared to the existing ones. The outcomes settle the weight balancing, outperform others when executing Erlang traffic, and are catered in the context.</p>

Multi-objective load balancing in cloud infrastructure through fuzzy based decision making and genetic algorithm based optimization

“…The load balancing in cloud environment [17], [18] can be of two types, viz., static and dynamic load balancing. Through load balancing, it is expected to improve parameters like overall performance, system stability, quality of service (QoS) [19], fault tolerance [20] as it is essential to improve the service.…”

The influence of Islamic culture on information privacy: case of Malaysia’s computer professionals

“…The summary of findings as shown in Table 3. The summary of findings may be used as reference to various domains such as for cloud computing [10][11][12][13][14][15][16][17][18][19][20][21][22] and IoT [23 -25].…”

Optimized load balance scheduling algorithm

“…These algorithms depend on predicting the number of loads, relations between nodes, implementation of the system. The measured load is different in many aspects, such as central processing unit (CPU) load, the used memory, and time delay [8], [9]. Load balance algorithms can be classified into either static or dynamic resource allocation.…”