S. Abrishami

Ferdowsi University Of Mashhad | FUM · Department of Computer Engineering

In a cloud environment, a cloud broker plays a vital role as an intermediary between cloud customers and providers, resolving issues and facilitating negotiations to balance customer preferences and provider profits. Over the past few years, numerous research articles have either directly or indirectly examined this area. Conducting a Systematic Ma...

The utilization of cloud computing environments is highly popular for carrying out workflow executions due to its ability to provide clients with immediate access to computing resources. Among the various workflow scheduling problems in the cloud, deadline-constrained workflow scheduling has garnered increasing attention in recent years. This paper...

Scheduling workflows in cloud environments is an important issue that many types of research have been conducted in this field. However, these approaches often focus on single workflow scheduling while the need for scheduling multiple workflows is growing. This study aims at presenting a cloud Broker for executing Deadline-constrained Periodic scie...

In recent times, cloud computing has become a popular platform for running various applications, with workflows being one of the most common types. However, efficient execution of workflows on cloud resources requires expertise in resource management techniques. Moreover, combining and running workflows from different users can be more cost-effecti...

Edge computing is a new way of computing that uses resources at the edge of a network to solve the problem of communication delays in applications that require immediate responses. This field has received a lot of attention from the research community over the past few decades, leading to a significant increase in publications. To better understand...

Cloud computing has transformed computer science and attracted academics, businesses, and state organs. Today, distributed cloud has received more attention than centralized cloud model due to emerging new computational requirements and the geographical dispersion of cloud users. Efficient and optimal management of cloud resources has become one of...

In Wireless Sensor Networks (WSNs), clustering is often used to improve communication and routing. Therefore, clustering approaches highly attract several researchers since performing clustering saves energy, and energy efficiency is a significant goal in WSN. To beneficially adopt WSN technology, efficient application development is necessary. The...

A federated cloud is a form of the inter-cloud environment in which cloud service providers cooperate for better scalability and service provisioning. By communicating with other cloud providers and sharing resources, federated members gain more advantages from utilizing a comprehensive resource management system. There are different setups for fed...

A cloud computing environment is the most popular choice for workflow execution, as it gives customers on-demand access to computing resources. However, in cloud workflow scheduling, cloud-native requirements regarding QoS requirements such as monetary cost and execution time should be taken into account. This paper proposes PCP-ACO, a list schedul...

Nowadays, cloud computing is an attractive and competitive market, and many computational jobs have migrated to cloud resources. Scheduling a workflow is a common issue in cloud computing. In some applications, a group of interrelated workflows with the same structure but different sizes and inputs is considered as a single job called an ensemble....

A workflow is an effective way for modeling complex applications and serves as a means for scientists and researchers to better understand the details of applications. Cloud computing enables the running of workflow applications on many types of computational resources which become available on-demand. As one of the most important aspects of cloud...

Scientific workflows are used to process large amounts of data and perform complex analyses; thus, they require powerful computing resources to produce the desired results in an acceptable time and at reasonable costs. For this purpose, distributed resources such as cloud computing, with access to virtualized, infinite, and elastic resources are us...

To augment the capabilities of mobile devices, application partitioning solutions in mobile cloud computing have emerged to decide the execution location of each application part between mobile device and cloud servers. To adapt to the network and server status changes during application execution, we propose a cloudlet-assisted ready-time partitio...

جریان‌های کاری علمی برای پردازش داده‌های عظیم و تحلیل‌ها و شبیه‌سازی‌های پیچیده استفاده می‌شوند، درنتیجه نیازمند منابع محاسباتی قدرتمندی هستند که بتوانند نتایج موردنظر را در زمان قابل‌قبول و با هزینه مطلوب تولید کنند. به‌این منظور از منابع زیرساخت‌های توزیع‌شده‌ای چون ابر محاسباتی به دلیل مزایایی ازجمله دسترسی به منابع مجازی ، نامحدود و کشسان برای...

The current systematic review includes a comprehensive 3-tier strategy (manual search, backward snowballing, and database search). The accuracy of the search methodology has been analyzed in terms of extracting related studies and collecting comprehensive and complete information in a supplementary file. In the search methodology, qualitative crite...

Edge computing is a novel computing paradigm which extends cloud computing storage and computation resources at the edge of network and closer to the end-users in order to tackle the problem of communication latency in latency-sensitive applications. For the last decades, there have been many research efforts dedicated to this field. However, there...

Cloud federation helps cloud providers to scale up by renting resources from other providers when the workload increased. Moreover, cloud providers with idle or underutilized resources can sell their resources to others and earn revenue inside a cloud federation. One of the most critical problems in the federated cloud environment is the management...

Method for Decentralized Clustring in Wireless Sensor Networks

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...

In ubiquitous environments today, there are numerous sensors that generate a large amount of data. The results of processing this massive data can be applied through peripheral actuators in the surrounding environment of users. On the other hand, users are more interested in running compute-intensive applications on their mobile devices in the mini...

An improved method of dynamically scheduling clustering operations in a network includes determining if one or more conditions for reclustering are met before deciding to perform the next reclustering operation. Therefore, to achieve load balancing for a network, the method of dynamically scheduling clustering operations schedules reclustering oper...

An improved method of clustering wireless sensor networks includes selecting cluster heads in the network based on a score calculated for each node. The score is calculated based on one or more predetermined criteria of each node and determines which node is selected as a cluster head among one or more nodes in the vicinity of each other. As a resu...

In ubiquitous and mobile computing environments, most of user requests have timing constraints. Therefore, for their execution, real-time scheduling mechanisms should be employed. In such environments, some mechanisms, such as Earliest Deadline First and Least Slack Time Rate (LSTR), are the most used real-time scheduling algorithms today. However,...

Challenges in pure ubiquitous computing, including the limitation of being multi-domain, absence of a uniform namespace, impossible intensive mobility of users, limited resources, lack of scalability, intensive applications, and so forth, have led researchers to provide hybrid ubiquitous architectures that are generally cloud-based. However, variou...

Cloud computing is able to allocate different resources as virtual machines (VMs) to users, who need only pay for the amount of resources used. Two of the challenges in clouds are resource allocation and pricing in such a way to satisfy both cloud providers and users. Existing allocation and pricing mechanisms cannot guarantee increased profits due...

Organizing sensor nodes into a clustered architecture is an effective method for load balancing and prolonging the network lifetime. However, a serious drawback of the clustering approach is the imposed energy overhead caused by the "global" clustering operations in every round of the Global Round-Based Policy (GRBP). To mitigate this problem, this...

Clustering is one of the effective approaches for prolonging the lifetime of a wireless sensor network and increasing its scalability. In current clustering protocols, load balancing is achieved by rotating the costly role of the cluster head among the sensors. To achieve this, the network operation is divided into fixed time durations called round...

Prolonging the network life cycle is an essential requirement for many types of Wireless Sensor Network (WSN) applications. Dynamic clustering of sensors into groups is a popular strategy to maximize the network lifetime and increase scalability. In this strategy, to achieve the sensor nodes’ load balancing, with the aim of prolonging lifetime, net...

Huge energy consumption in cloud infrastructure has turned into a challenging problem. Virtualization technology, which can be regarded as the first step in energy conservation by offering benefits like on-demand resource provisioning and live migration, creates a platform on which different resource allocation and scheduling policies can be define...

Workflows are adopted as a powerful modeling technique to represent diverse applications in different scientific fields as a number of loosely coupled tasks. Given the unique features of cloud technology, the issue of cloud workflow scheduling is a critical research topic. Users can utilize services on the cloud in a pay-as-you-go manner and meet t...

Nowadays, Cloud Computing is considered one of the important fields in both research and industry. Users enjoy membership of cloud providing effective services called time-limited services. This paper addresses time-limited services offering an attribute-based access control method and time-limited attributes providing users' time-limited membershi...

Efficient energy use has become a critical issue for resource management in Cloud data centers. Virtualization is a key technology for reducing energy cost and improving resource utilization in data centers. One of the challenges faced by virtualized data centers is to decide how to pack VMs on the least number of hosts. This paper presents a decen...

Clustering is a promising solution to conserve sensor energy levels and to organize tasks among nodes. This paper presents a distributed energy efficient protocol to cluster wireless sensor networks using two techniques: local re-clustering and multi-criteria cluster formation. When a Cluster Head (CH) maintains an acceptable part of its remaining...

The advent of Cloud computing as a new model of service provisioning in distributed systems encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as workflows. One of the most challenging problems in Clouds is workflow scheduling, i.e., the problem of satisfying the QoS requirements of the user a...

Recently, utility Grids have emerged as a new model of service provisioning in heterogeneous distributed systems. In this model, users negotiate with service providers on their required Quality of Service and on the corresponding price to reach a Service Level Agreement. One of the most challenging problems in utility Grids is workflow scheduling,...

The advent of Cloud computing as a new model of service provisioning in distributed systems, encourages researchers to investigate its benefits and drawbacks in executing scientific applications such as workflows. In this model, the users request for available services according to their desired Quality of Service, and they are charged on a pay-per...

Workflow scheduling on utility Grids is a com-plex multi-objective optimization problem which tries to optimize several scheduling criteria such as execution time and cost. One common approach to the problem is to optimize only one criterion, while other criteria are con-strained within fixed thresholds. In this paper, we propose a new scheduling a...

Recently, utility grids have emerged as a new model of service provisioning in heterogeneous distributed systems. In this model, users negotiate with providers on their required Quality of Service and on the corresponding price to reach a Service Level Agreement. One of the most challenging problems in utility grids is workflow scheduling, i.e., th...

Scientists increasingly rely on the execution of workflows in grids to obtain results from complex mixtures of applications. However, the inherently dynamic nature of grid workflow scheduling, stemming from the unavailability of scheduling information and from resource contention among the (multiple) workflows and the non-workflow system load, may...

Software testing is a difficult task for web based applications due to their special features like multi-tier structure and emergence of new technologies (e.g. Ajax). In recent years, automatic testing of web based applications has been emerged as a promising technique to tackle the difficulties of testing these types of applications and several fr...

Vast majority of computer users are generously willing to share their computer resources with needy organizations and individuals to solve their computational, data storage, and communicational problems. The recently emerging Grid technology is providing the required platform for the coordinated resource sharing and problem solving among individual...

In this paper we present a hybrid method for face recognition task, which covers both the important information in the high order relationships among the image pixels and low dimensional representation of the image. This system is feature based, and analyzes local facial features, which are located by a meta-version of the sparsification algorithm...