Certain investigations on meta heuristic algorithms for resource allocation in latency sensitive cloud object storage systems

Abstract

Billions of heavy data are stored in the cloud object storage system and newlineit is considered as one of the most important duties of cloud services. The user newlinemay experience latency when providing the query to the cloud system. This is newlinemainly because of the huge number of requests provided by the customer. newlineThe response latency occurs because of the time-out issues. In cloud services, newlinethe clients face lots of issues regarding the accessing of data at a particular period. newlineThe main reason behind this issue is the dynamics of load and congestion in the newlinenetwork. The delay in response can be solved by assigning the request to multiple newlineservers. The heavy data objects are stored by the cloud object storage system. newlineThese systems give solutions to various queries developed by the user. newlineEvery day, tons and tons of queries are answered by cloud services. In most web newlineapplications, the cloud storage system plays a significant role in storing data such newlineas video, documents, photos, etc. In the cloud object storage system, the cost newlineexpenditure is considered as the most important concern due to the large volume newlineof data. The latency issues in the cloud service are solved by allocating data to the newlineminimum number of servers, which lowers the cost required for the storage newlineprocess. newlineThe conventional techniques require more running time, which newlineenhances the cost of the storage process. So, in this chapter two diverse newlinecontributions are offered for storing the data in a cloud system with minimum newlinelatency and cost. In the first contribution, a novel cloud object storage system is newlineoffered to handle the latency issue in the allocation, reallocation, and workload newlineconsolidation process. newline