arXiv subjects

Saeid Abrishami

Publications and source records attributed to Saeid Abrishami.

4 recordsLinked to original sources

arXiv2025

Workflow as a Service Broker in Cloud Environment: A Systematic Mapping Study

Cloud computing has emerged as a promising platform for running scientific workflows across various domains. Scientists can take advantage of different cloud service models, such as serverful or serverless, to execute workflows based on their specific requirements, along with diverse pricing models like on-demand, reserved, or spot instances to reduce execution costs. However, the challenge of selecting appropriate resources and pricing models, coupled with the orchestration and scheduling of workflow tasks, creates significant complexity for users. To mitigate this burden, Workflow as a Service (WaaS) brokers have been introduced to facilitate workflow execution. In recent years, numerous studies have been published, either directly or indirectly related to this research area, highlighting the need for a comprehensive and systematic review of WaaS brokers to identify key trends and challenges in this field. In this paper, we conduct a Systematic Mapping Study (SMS) on WaaS brokers within cloud environments. The SMS employs a thorough 3-tier strategy (database search, backward snowballing, and forward snowballing) to answer five research questions. A total of 87 high-quality articles, published in 49 prestigious venues, are analyzed to derive a taxonomy based on the architecture of WaaS brokers. The articles are classified and surveyed according to this taxonomy, and future research directions for the design and implementation of WaaS brokers are explored. This study provides valuable insights for researchers and developers, helping them identify major trends and issues in the field of WaaS brokers.

cs.DC↗

arXiv2022

Edge Computing: A Systematic Mapping Study

Edge computing is a novel computing paradigm that extends cloud resources at the edge of the network to tackle the problem of communication latency in latency-sensitive applications. For the last decades, there have been many efforts dedicated to this field. The dramatic growth in the publications, and the great attention of the research community, have made it necessary to conduct a Systematic Mapping Study (SMS) to enable researchers get a better view of the field. A three-tier search method is considered in this work. In this method, we defined some quality criteria to extract appropriate search spaces and studies. Using this methodology, we select 112 search spaces out of 805 ones, and by searching in these search spaces we select 1440 studies out of 8725. In our SMS, 8 research questions have been designed and answered to identify the main topics, architectures, techniques, etc. in the field of edge computing.

cs.NI↗

arXiv2021

Cloud Broker: A Systematic Mapping Study

In a cloud environment, a cloud broker is an important entity that works as an independent middleware between cloud customers and providers to address issues and conduct negotiations related to satisfying both customer preferences and service provider profits. In recent years, researchers have published many articles which directly or indirectly address this research area. A systematic method is vital for extracting all search spaces (journals, conferences, and workshops) and primary studies (articles) conducted in the cloud broker field and then selecting some of the highest quality studies. The proposed systematic review includes a comprehensive three-tier search strategy (manual search, backward snowballing, and database search). The detailed explanation of the reviewing process is inserted in Appendix A. In the search methodology, qualitative criteria have been defined to select studies with the highest quality and the most relevance among all search spaces. In the present study, out of 1,928 extracted search spaces, 171 search spaces have been selected based on the defined quality criteria. Then, 1,298 articles have been extracted from these 171 selected search spaces. As a result, 496 high-quality papers have been selected among the mentioned papers. The chosen papers were published in prestigious journals, conferences, and workshops from 2009 through 2019. In the current Systematic Mapping Study (SMS), eight research questions have been designed for the purpose of identifying information that is significant to the cloud broker field, such as the most critical and debated topics, existing trends and issues, active researchers and countries, commonly used techniques in building cloud brokers, evaluation methods, the amount of research conducted by year and the place of publication, and the most important active search spaces.

cs.DC↗

arXiv2020

An Efficient Mechanism for Computation Offloading in Mobile-Edge Computing

Mobile edge computing (MEC) is a promising technology that provides cloud and IT services within the proximity of the mobile user. With the increasing number of mobile applications, mobile devices (MD) encounter limitations of their resources, such as battery life and computation capacity. The computation offloading in MEC can help mobile users to reduce battery usage and speed up task execution. Although there are many solutions for offloading in MEC, most usually only employ one MEC server for improving mobile device energy consumption and execution time. Instead of conventional centralized optimization methods, the current paper considers a decentralized optimization mechanism between MEC servers and users. In particular, an assignment mechanism called school choice is employed to assist heterogeneous users to select different MEC operators in a distributed environment. With this mechanism, each user can benefit from minimizing the price and energy consumption of executing tasks while also meeting the specified deadline. The present research has designed an efficient mechanism for a computation offloading scheme that achieves minimal price and energy consumption under latency constraints. Numerical results demonstrate that the proposed algorithm can attain efficient and successful computation offloading.

cs.DC↗