Dynamic software rejuvenation in web services: a whale optimizationalgorithm-based approach

Abstract

In this paper, we suggest a method for determining the restarting time for web services to increase availability, known as rejuvenation. We consider different parameters such as number of users, maximum service request number, response time, and throughput of a web service to determine its restarting time. Software rejuvenation is an effective technique to counteract software aging in continuously running applications such as web service-based systems. In these systems, web services are allocated based on the needs of the receivers and facilities of servers. One of the challenges while assigning web services is selecting the appropriate server to reduce faults. Since the selection of a server among candidates while maintaining the optimal quality of service is an NP-hard problem, metaheuristics seem to be suitable. In this paper, we propose dynamic software rejuvenation as a proactive fault-tolerance technique based on the whale optimization algorithm. The threshold for the rejuvenation of each of the web services is considered and training is done based on the features of the service providers as well as the needs of the receivers. The whale optimization algorithm with the criterion of movement radius is utilized for flexibility of web service provider selection. Here, we detect and rejuvenate systems that required rejuvenation before the occurrence of a fault. The simulation results reveal that our strategy can decrease the failure rate by an average of 30 percent in comparison with state-of-the-art strategies and improve the system availability in web services.

Block size optimization for PoW consensus algorithm based blockchain applications by using whale optimization algorithm

“…One reason for choosing these algorithms is that they are robust, simple, and powerful [24]. Furthermore, WOA for solving the objective problem requires few parameters to be tuned and balances between exploitation and exploration without being trapped in local optima [25].…”

A fuzzy neural network for web service selection aimed at dynamic software rejuvenation

“…Kalantari et al [1] investigated an inspection-based method for preventive maintenance in a software operating system that was periodically inspected at specific intervals using Markov's model. The optimum inspection interval has been obtained to minimize faults and costs.…”

“…Therefore, frequent inspections at runtime in a software system cause the system to suffer certain amounts of overheads in terms of faults and costs. This should be considered together with the fault and cost of failure in an attempt to obtain maximum efficiency [1].…”

Presenting a new fuzzy system for web service selection aimed at dynamic software rejuvenation

“…They further clarified the effective criteria for evaluation of fault tolerance in each web service mentioned earlier. In [39,40], fault-tolerance techniques were proposed based on meta-heuristics in an effort to fight software aging in continuously running applications such as web service-based systems. However, the methods are limited due to impossible application in systems requiring short response times.…”