Bahman Javadi

• PhD
• Professor (Full) at Western Sydney University

This study evaluates a smartphone-based, deep-learning eye-tracking algorithm by comparing its performance against a commercial infrared-based eye tracker, the Tobii Pro Nano. The aim is to investigate the feasibility of appearance-based gaze estimation under realistic mobile usage conditions. Key sensitivity factors, including age, gender, vision...

Biofeedback therapy is useful for treatment of functional defecation disorders but is not widely available and is labor intensive. We developed an Internet-of-Medical-Things (IoMT) device, enabling self-guided biofeedback therapy. This study assesses the safety and efficacy of self-guided biofeedback therapy using the IoMT device in comparison to s...

Cloud data centers have started utilizing erasure coding in large-scale storage systems to ensure high reliability with limited overhead compared to replication. However, data recovery in erasure coding incurs high network bandwidth consumption compared to replication. Cloud storage systems also play an important role in the energy consumption of d...

In optimization algorithms, there are some challenges, including lack of optimal solution, slow convergence, lack of scalability, partial search space, and high computational demand. Inspired by the process of gold exploration and exploitation, we propose a new meta-heuristic and stochastic optimization algorithm called collaborative gold mining (C...

Eye-tracking is a technique used for determining where users are looking and how long they keep their gaze fixed on a particular location. Developments in mobile technology have made mobile applications pervasive; however, eye tracking on mobile devices is still uncommon. This paper proposes a mobile edge computing architecture for eye tracking. We...

Next generation technologies such as smart healthcare, self-driving cars, and smart cities require new approaches to deal with the network traffic generated by the Internet of Things (IoT) devices, as well as efficient programming models to deploy machine learning techniques. Serverless edge computing is an emerging computing paradigm from the inte...

In recent years, the landscape of computing paradigms has witnessed a gradual yet remarkable shift from monolithic computing to distributed and decentralized paradigms such as Internet of Things (IoT), Edge, Fog, Cloud, and Serverless. The frontiers of these computing technologies have been boosted by shift from manually encoded algorithms to Artif...

Traditionally, network and system administrators are responsible for designing, configuring, and resolving the Internet service requests. Human-driven system configuration and management are proving unsatisfactory due to the recent interest in time-sensitive applications with stringent quality of service (QoS). Aiming to transition from the traditi...

Traditionally, network and system administrators are responsible for designing, configuring, and resolving the Internet service requests. Human-driven system configuration and management are proving unsatisfactory due to the recent interest in time-sensitive applications with stringent quality of service (QoS). Aiming to transition from the traditi...

Eye-tracking provides invaluable insight into the cognitive activities underlying a wide range of human behaviours. Identifying cognitive activities provide valuable perceptions of human learning patterns and signs of cognitive diseases like Alzheimer’s, Parkinson’s, autism. Also, mobile devices have changed the way that we experience daily life an...

Home-based healthcare provides a viable and cost-effective method of delivery for resource- and labour-intensive therapies, such as rehabilitation therapies, including anorectal biofeedback. However, existing systems for home anorectal biofeedback are not able to monitor patient compliance or assess the quality of exercises performed, and as a resu...

Smart homecare utilises advanced technologies to support, improve and promote remote healthcare in homes and communities through collecting and analysing health data and sharing this knowledge with carers and clinicians. With the continuous growth in the world’s older population, smart homecare becomes increasingly crucial in providing in-home care...

Internet of Things applications can be represented as workflows in which stream and batch processing are combined to accomplish data analytics objectives in many application domains such as smart home, health care, bioinformatics, astronomy, and education. The main challenge of this combination is the differentiation of service quality constraints...

With the increasing use of the Internet of Things (IoT) in various fields and the need to process and store huge volumes of generated data, Fog computing was introduced to complement Cloud computing services. Fog computing offers basic services at the network for supporting IoT applications with low response time requirements. However, Fogs are dis...

Mobile devices and their corresponding services have become ubiquitous and vital components of almost every aspect of social and business life. Mobile services enhance collaboration, communication, monitoring, tracking, streaming, and many other applications. This intense and continuous engagement presents significant challenges due to mobile devic...

Born from a need for a pure "pay-per-use" model and highly scalable platform, the "Serverless" paradigm emerged and has the potential to become a dominant way of building cloud applications. Although it was originally designed for cloud environments, Serverless is finding its position in the Edge Computing landscape, aiming to bring computational r...

Growth in adoption of various technologies including smartphones and Internet of Things (IoT) [1] has been unprecedented in recent years and as a result a vast amount of public and private data sources are available for organizations, which leverage them in the form of smart applications [2, 3]. These applications incorporate data-driven, actionabl...

Dependence of computing resources on each other in cloud computing systems (CCS) makes them prone to fail in correlated manner which significantly impacts their service reliability and energy efficiency. Focusing on these two metrics of CCS while considering correlated failures remained an open question, which is the focus of this work. This paper...

Mobile cloud computing helps to overcome the challenges of mobile computing by allowing mobile devices to migrate computation-intensive and data-intensive tasks to high-performance and scalable computation resources. However, emerging data-intensive applications pose challenges for mobile cloud computing platforms because of high latency, cost and...

Blockchain is a new approach to create a distributed network which was first introduced in 2008. By the help of this disruptive technology a peer-to-peer network can be formed where nodes have to reach a consensus and form a chain from accepted blocks, while no central party or trusted controller is required. Among all the existing uses of this tec...

Artificial Intelligence (AI) is a machine intelligence tool providing enormous possibilities for smart industrial revolution. Internet of Things (IoT) is the axiom of industry 4.0 revolution, including a worldwide infrastructure for collecting and processing of the data/information from storage, actuation, sensing, advanced services and communicati...

While privacy and security concerns dominate public cloud services, Homomorphic Encryption (HE) is seen as an emerging solution that can potentially assure secure processing of sensitive data by third-party cloud vendors. It relies on the fact that computations can occur on encrypted data without the need for decryption, although there are major st...

The United Nations has developed 17 Sustainable Development Goals (SDGs) to transform our world. Smart Computing aims to combine advances in Information and Communication Technologies including Internet of Things, cloud computing, mobile computing and social computing to create smart systems to make human life better. Smart Computing is providing a...

Mobile cloud computing is a platform that has been used to overcome the challenges of mobile computing. However, emerging data-intensive applications, such as face recognition and natural language processing, imposes more challenges on mobile cloud computing platforms because of high bandwidth cost and data location issues. To overcome these challe...

A number of homomorphic encryption application areas could be better enabled if there existed a general solution for combining sufficiently expressive logical and numerical circuit primitives. This paper examines accelerating binary operations on real numbers suitable for somewhat homomorphic encryption. A parallel solution based on SIMD can be use...

This chapter provides background on big data analytics and describes how fog‐engine (FE) can be deployed in the traditional centralized data analytics platform and how it enhances existing system capabilities. The FE provides on‐premise data analytics as well as the capabilities for Internet‐of‐Things (IoT) devices to communicate with each other an...

VM consolidation is an important technique used in cloud computing systems to improve energy efficiency. It migrates the running VMs from under utilized physical resources to other resources in order to reduce the energy consumption. But in a cloud computing environment with failure prone resources, focusing solely on energy efficiency has adverse...

Poor nutrition impairs the health and wellbeing of the population and increases the risk of chronic diseases such as obesity and type 2 diabetes. Chronic diseases that require dietary management can be better managed if food and nutrition intake is monitored. Existing methods for measurement are inaccurate and not scalable as they are based on a pe...

The Cloud computing paradigm has revolutionized the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytim...

Volunteer computing systems are large-scale distributed systems with large number of heterogeneous and unreliable Internet-connected hosts. Volunteer computing resources are suitable mainly to run High-Throughput Computing (HTC) applications due to their unavailability rate and frequent churn. Although they provide Peta-scale computing power for ma...

Reliability and Energy-efficiency is one of the biggest trade-off challenges confronting cloud service providers. This paper provides a mathematical model of both reliability and energy consumption in cloud computing systems and analyses their interplay. This paper also proposes a formal method to calculate the finishing time of tasks running in a...

The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anyti...

Cloud storage systems are now mature enough to handle a massive volume of heterogeneous and rapidly changing data, which is known as Big Data. However, failures are inevitable in cloud storage systems as they are composed of large scale hardware components. Improving fault tolerance in cloud storage systems for Big Data applications is a significan...

Virtualization as one of the leading technologies has assisted datacenters to cloudify their products and provide versatile platforms and variety of Internet services. This technology also has facilitated agile deployment of complex Internet services such as Cloud-based multi-tier applications. However implementing multi-tier applications assists p...

With the popularity of cloud computing, it has become crucial to provide on-demand services dynamically according to the user's requirements. Reliability and energy efficiency are two key challenges in cloud computing systems (CCS) that need careful attention and investigation. The recent survey articles are either focused on the reliability techni...

The volume of generated data increases by the rapid growth of Internet of Things, leading to the big data proliferation and more opportunities for datacenters. Highly virtualized cloud-based datacenters are currently considered for big data analytics. However, big data requires datacenters with promoted infrastructure capable of undertaking more re...

Virtual machine technology facilitates implementation of modern Internet services, especially multi-tier applications. Server virtualization aims to reduce the cost of service provisioning and improve fault tolerance, portability and security of virtualized services by sharing the resources amongst consolidated servers. Although designing applicati...

With the popularity of cloud computing, it becomes crucial to provide on-demand services dynamically according to the user's requirements. Reliability and energy efficiency are two big challenges in cloud computing systems that need careful attention and investigation. This paper first presents a review of existing techniques for reliability and en...

Volunteer computing systems offer high computing power to the scientific communities to run large data intensive scientific workflows. However, these computing environments provide the best effort infrastructure to execute high performance jobs. This work aims to schedule scientific and data intensive workflows on hybrid of the volunteer computing...

Volunteer computing systems exploiting large amounts of geographically dispersed resources on the Internet for solving complex scientific problems. However, scheduling scientific workflows in a fully decentralised way and low overhead is a challenging task in these environments. To counter this challenge, this paper presents a fully decentralised p...

A grid computing environment provides a type of distributed computation that is unique because it is not centrally managed and it has the capability to connect heterogeneous resources. A grid system provides location-independent access to the resources and services of geographically distributed machines. An essential ingredient for supporting locat...

Cloud computing provides more reliable and flexible access to IT resources, which differentiates it from other distributed computer paradigms. Managing the applications efficiently in cloud computing motivates the challenge of provisioning and allocating resource on demand in response to dynamic workloads. Most of investigations have been focused o...

Resource provisioning is one of the main challenges in large-scale distributed systems such as federated Grids. Recently, many resource management systems in these environments have started to use the lease abstraction and virtual machines (VMs) for resource provisioning. In the large-scale distributed systems, resource providers serve requests fro...

Resource allocation is one of the main influential factors to provide efficient and economical processing of resources in the infrastructure as a service Clouds. While there are many challenges in providing an efficient resource allocator, maximizing the utilization of physical resources is of great importance. There are several works focused on op...

Several analytical models of interconnection networks of multi-cluster systems under uniform traffic pattern have been proposed in the literature. However, there has been hardly any work reported yet that deals with other important non-uniform traffic patterns found in many parallel applications. In this paper we propose a new analytical model of a...

Volunteer computing systems are large-scale distributed systems with large number of heterogeneous and unreliable Internet-connected hosts. Volunteer computing resources are suitable mainly to run High-Throughput Computing (HTC) applications due to their unavailability rate and frequent churn. Although they provide Peta-scale computing power for ma...

Plug-in Electric Vehicles (PEVs) provide new opportunities to reduce fuel consumption and exhaust emission. PEVs need to draw and store energy from an electrical grid to supply propulsive energy for the vehicle. As a result, it is important to know when PEVs batteries are available for charging and discharging. Furthermore, battery energy managemen...

Data-centric and service-oriented workflows are commonly used in scientific research to enable the composition and execution of complex analysis on distributed resources. Although there are a plethora of orchestration frameworks to implement workflows, most of them are unsuitable for executing (enacting) data-centric workflows since they are based...

Volunteer computing which benefits from idle cycles of volunteer resources over the Internet can integrate the power of hundreds to thousands of resources to achieve high computing power. In such an environment the resources are heterogeneous in terms of CPU speed, RAM, disk capacity, and network bandwidth. So finding a suitable resource to run a p...

With the increasing presence, scale, and complexity of distributed systems, resource failures are becoming an important and practical topic of computer science research. While numerous failure models and failure-aware algorithms exist, their comparison has been hampered by the lack of public failure data sets and data processing tools. To facilitat...

One of the main challenges in peer-to-peer-based volunteer computing systems is an efficient resource discovery algorithm. Load balancing is a part of resource discovery algorithm and aims to minimize the overall response time of the system. This paper introduces an analytical model based on distributed parallel queues to optimize the average respo...

The surge in demand for utilizing public Cloud resources has introduced many trade-offs between price, performance and recently reliability. Amazon’s Spot Instances (SIs) create a competitive bidding option for public Cloud users at lower prices without providing reliability on services. It is generally believed that SIs reduce monetary cost to the...

In this paper, we investigate Cloud computing resource provisioning to extend the computing capacity of local clusters in the presence of failures. We consider three steps in the resource provisioning including resource brokering, dispatch sequences, and scheduling. The proposed brokering strategy is based on the stochastic analysis of routing in d...

The inherent dynamicity in grid computing has made it extremely difficult to come up with near-optimal solutions to efficiently schedule tasks in grids. Task Scheduling plays crucial role in Grid computing. It is a challengeable issue among scientists to achieve better results especially in makespan based on various AI methods. Nowadays, non determ...

Resource provisiomng is an important and challenging problem in the large-scale distributed systems such as Cloud computing environments. Resource management issues such as Quality of Service (QoS) further exacerbate the resource provisioning problem. Furthermore, with the increasing functionality and complexity of Cloud computing, resource failure...

Hybrid Cloud computing is receiving increasing attention in recent days. In order to realize the full potential of the hybrid Cloud platform, an architectural framework for efficiently coupling public and private Clouds is necessary. As resource failures due to the increasing functionality and complexity of hybrid Cloud computing are inevitable, a...

In this paper, we investigate Cloud computing resource provisioning to extend the computing capacity of local clusters in the presence of failures. We consider three steps in the resource provisioning including resource brokering, dispatch sequences, and scheduling. The proposed brokering strategy is based on the stochastic analysis of routing in d...

In the age of cloud, Grid, P2P, and volunteer distributed computing, large-scale systems with tens of thousands of unreliable hosts are increasingly common. Invariably, these systems are composed of heterogeneous hosts whose individual availability often exhibit different statistical properties (for example stationary versus non-stationary behaviou...

Data-centric and service-oriented workflows are commonly used in scientific research to enable the composition and execution of complex analysis on distributed resources. Although there are a plethora of orchestration frameworks to implement workflows, most of them are not suitable to execute data-centric workflows. The main issue is transferring o...

Multicluster systems have emerged as a promising infrastructure for provisioning of cost-effective high-performance computing and communications. Analytical models of communication networks in cluster systems have been widely reported. However, for tractability and simplicity, the existing models are based on the assumptions that the network traffi...

Many applications in federated Grids have quality-of-service (QoS) constraints such as deadline. Admission control mechanisms assure QoS constraints of the applications by limiting the number of user requests accepted by a resource provider. However, in order to maximize their profit, resource owners are interested in accepting as many requests as...

In the age of cloud, Grid, P2P, and volunteer distributed computing, large-scale systems with tens of thousands of unreliable hosts are increasingly common. Invariably, these systems are composed of heterogeneous hosts whose individual availability often exhibit different statistical properties (for example stationary versus nonstationary behavior)...

In multi-cluster Grids each cluster serves requests from external (Grid) users along with their own local users. The problem arises when there is not sufficient resources for local users (which have high priority) to be served urgently. This problem could be solved by preempting resources from Grid users and allocating them to the local users. Howe...

Resource provisioning is one of the main challenges in resource sharing environments such as InterGrid. Recently, many resource management systems in re-source sharing environments use lease abstraction and virtual machines for provisioning. In resource shar-ing environments resource providers serve requests from external (grid) users along with th...

This paper addresses the problem of interconnection networks performance modeling of large-scale distributed systems with emphases on multi-cluster computing systems. The study of interconnection networks is important because the overall performance of a distributed system is often critically hinged on the effectiveness of its interconnection netwo...

Resource provisioning is one of the main challenges in resource sharing environments such as InterGrid. Recently, many resource management systems in resource sharing environments use lease abstraction and virtual machines for provisioning. In resource sharing environments resource providers serve requests from external (grid) users along with thei...

Distributed systems such as grids, peer-to-peer systems, and even Internet DNS servers have grown significantly in size and complexity in the last decade. This rapid growth has allowed distributed systems to serve a large and increasing number of users, but has also made resource and system failures inevitable. Moreover, perhaps as a result of syst...

Grid system provides the sharing, selection and aggregation on distributed autonomous resources while it is an error prone environment. So, grid component like scheduler must provide the user's Quality of Service (QoS) requirements by selecting the appropriate resources for user's jobs. In this paper, we have proposed a fault-aware economy scheduli...