journal article·2023Open access

TRS Scheduling for Improved QoS Performance in Cloud System

G. John Samuel Babu, M. Baskar

Computers, Materials & Continua· Volume 75· Issue 1

Abstract

Numerous methods are analysed in detail to improve task scheduling and data security performance in the cloud environment. The methods involve scheduling according to the factors like makespan, waiting time, cost, deadline, and popularity. However, the methods are inappropriate for achieving higher scheduling performance. Regarding data security, existing methods use various encryption schemes but introduce significant service interruption. This article sketches a practical Real-time Application Centric TRS (Throughput-Resource utilization–Success) Scheduling with Data Security (RATRSDS) model by considering all these issues in task scheduling and data security. The method identifies the required resource and their claim time by receiving the service requests. Further, for the list of resources as services, the method computes throughput support (Thrs) according to the number of statements executed and the complete statements of the service. Similarly, the method computes Resource utilization support (Ruts) according to the idle time on any duty cycle and total servicing time. Also, the method computes the value of Success support (Sus) according to the number of completions for the number of allocations. The method estimates the TRS score (Throughput Resource utilization Success) for different resources using all these support measures. According to the value of the TRS score, the services are ranked and scheduled. On the other side, based on the requirement of service requests, the method computes Requirement Support (RS). The selection of service is performed and allocated. Similarly, choosing the route according to the Route Support Measure (RSM) enforced route security. Finally, data security has gets implemented with a service-based encryption technique. The RATRSDS scheme has claimed higher performance in data security and scheduling.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Cloud Computing and Resource Management · IoT and Edge/Fog Computing · Blockchain Technology Applications and Security

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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