Multiple Objective–Based Modified Exponential Gravitational Search Algorithm to VMM Strategy for Load Balancing in Cloud

Abstract

Cloud computing is a trending topic in the field of science and technology since the internet dependent services have been growing rapidly. In this environment, there are a lot of immense infrastructures and resources to satisfy the internet users. When a large number of service requests reach at a particular time, load balancing becomes a necessity. Load balancing involves the effective migration of the resources from the loaded physical machine to the other physical machine. For the effective migration, a method named Modified Exponential Gravitational Search Algorithm based on Virtual Machine Migration strategy (MEGSA-VMM) has been proposed that uses the gravitational concepts for performing the frequency-based velocity computations. MEGSA algorithm is the integration of the gravitational search algorithm and exponential weighted moving average theory. Also, the qualityof-Service (QoS) constraints considered for VM migration are migration cost, migration time, resource usage and energy. Simulation of the proposed method and the comparison of the results obtained, with the traditional methods like Ant-Colony Optimization (ACO), Gravitational Search Algorithm (GSA) and Exponential Gravitational Search Algorithm (EGSA) is performed. The proposed method is found to achieve an optimum migration with a minimum energy at a rate of 0.26 and minimum migration cost at a rate of 0.015.

Multi‐objective constraint and hybrid optimisation‐based VM migration in a community cloud

“…The methods used for the comparison include random [15], SSA [23], Lion–Whale [24], and modified exponential gravitational search algorithm (MEGSA) [25], and the performance of the methods are evaluated to compare with the proposed method.…”

“…For the optimal VMM, Lion‐Whale VMM used a fitness function that considered resource utilization, energy consumption, and migration cost. Polepally, V and Chatrapati, K.S [25] designed a technique, called Modified Exponential Gravitational Search Algorithm based on Virtual Machine Migration strategy (MEGSA‐VMM), based on the idea of gravitation. The technique adopted MEGSA algorithm that employed gravitational search algorithm and exponential weighted moving average theory, considering various constraints of Quality of‐Service (QoS).…”

Improved GWO-CS Algorithm-Based Optimal Routing Strategy in VANET

“…Regardless of the fact that it's secure to suppose that communications subsist to a few scope and vehicles have entree to that irregularly [15]. It is recognized that the above disadvantages can be addressed simply by developing robust VANET communication route metrics and exploiting robust route optimization methods [18] [19] [20] [21] [22] [23] to determine optimal routes for communication.…”

Optimal Rescheduling Based Congestion Management using HBOABC Algorithm

“…In an open-access electricity market, an efficient optimization method like Firefly method [26] was presented for the CM issues [11]. Moreover, a novel technique [27] [28] [29] [30] is recommended for approximate transmission congestion cost on the basis of power flow tracing using PSO method [12] [24] [25]. Information gap decision theory was used to undertake the CM issue exploiting the flexible abilities of DG as well as demand response [13].…”