Sajib Mistry

The University of Sydney · School of Information Technologies

We propose a novel framework to detect conflicts among IoT services in a multi-resident smart home. A novel IoT conflict model is proposed considering the functional and non-functional properties of IoT services. We design a conflict ontology that formally represents different types of conflicts. A hybrid conflict detection algorithm is proposed by...

We propose a novel approach to select IaaS cloud services for a long-term period where the service providers offer limited QoS information. The proposed approach leverages free short-term trials to obtain the previously undisclosed QoS information. A new significance-based trial scheme is proposed using frequency distribution analysis to test a con...

We propose a novel framework for composing crowdsourced wireless energy services to satisfy users' energy requirements in a crowdsourced Internet of Things (IoT) environment. A new energy service model is designed to transform the harvested energy from IoT devices into crowdsourced services. We propose a new energy service composability model that...

We propose a novel Drone-as-a-Service (DaaS) composition framework considering the recharging constraints and the stochastic arrival of drone services. We develop a service model and a quality model for drone delivery services. A skyline approach is proposed that selects the optimal set of candidate drone services to reduce the search space. We pro...

We propose a novel approach to select privacy-sensitive IaaS providers for a long-term period. The proposed approach leverages a consumer’s short-term trial experiences for long-term selection. We design a novel equivalence partitioning based trial strategy to discover the temporal and unknown QoS performance variability of an IaaS provider. The co...

We propose a novel composition framework for drone-based package delivery services termed as Drone-as-a-Service (DaaS). The proposed framework includes a spatio-temporal service model and a quality model for DaaS. A drone service selection algorithm is designed using 3D Rtree. We develop a Dijkstra-based and a heuristic-based drone service composit...

We present a new spatio-temporal incentive-based approach to achieve a geographically balanced coverage of crowdsourced services. The proposed approach is based on a new spatio-temporal incentive model that considers multiple parameters including location entropy, time of day, and spatio-temporal density to encourage the participation of crowdsourc...

We propose a novel CP-Net based composition approach to qualitatively select an optimal set of consumers for an IaaS provider. The IaaS provider’s and consumers’ qualitative preferences are captured using CP-Nets. We propose a CP-Net composability model using the semantic congruence property of a qualitative composition. A greedy-based and a heuris...

Numerous reports predict that global cloud services will increase from $180B in 2015 to $390B in 2020, attaining a Compound Annual Growth Rate (CAGR) of 17%. SaaS-based applications are predicted to grow at 18% CAGR, and IaaS or PaaS is predicted to grow at 27% CAGR [114]. To further build and capitalize on this trend, further innovations in the cl...

One of the key characteristic of a cloud service is its flexibility [8]. It is a key catalyst for the economic growth of the cloud market. Cloud consumers usually observe three desired properties in a flexible cloud service: a) on-demand provision, b) elasticity, and c) flexible pricing [21]. In the on-demand provision model, computing resources ar...

User preferences are one of the key research subjects in developing personalized applications [126]. In many real life service composition scenarios, the target is to achieve the desired functional goal while ensuring user-provided preferences. For example, a travel planner usually composes services from different transportation and accommodation s...

It is natural for different providers to compete in the cloud market to maximize their profits using their individual economic models. The performance index of a provider can be calculated using the information of resource utilization, price fairness, consumers’ satisfactions and providers’ profits [71]. It is necessary for a provider to compare it...

An introduction to the research fields related to the management of services in cloud environments is given in this chapter to help readers gain a better understanding of the work described in this book. In particular, an overview of cloud service composition and economic models are presented in this chapter. Furthermore, we discuss existing predic...

The authors introduce both the quantitative and qualitative economic models as optimization tools for the selection of long-term cloud service requests. The economic models fit almost intuitively in the way business is usually done and maximize the profit of a cloud provider for a long-term period. The authors propose a new multivariate Hidden Mark...

We propose a new social-sensor cloud services selection framework for scene reconstruction. The proposed research represents social media data streams, i.e., images’ metadata and related posted information, as social sensor cloud services. The functional and non-functional aspects of social sensor cloud services are abstracted from images’ metadata...

We propose a qualitative similarity measure approach to select an optimal set of probabilistic Infrastructure-as-a-Service (IaaS) requests according to the provider’s probabilistic preferences over a long-term period. The long-term qualitative preferences are represented in probabilistic temporal CP-Nets. The preferences are indexed in a k-d tree t...

Mapping out the challenges and strategies for the widespread adoption of service computing.

We present a new two-level composition model for crowdsourced Sensor-Cloud services based on dynamic features such as spatio-temporal aspects. The proposed approach is defined based on a formal Sensor-Cloud service model that abstracts the functionality and non-functional aspects of sensor data on the cloud in terms of spatio-temporal features. A s...

We propose a new qualitative economic model based optimization approach to compose an optimal set of infrastructure service requests over a long-term period. The economic model is represented as a temporal CP-Net to capture the provider's dynamic business strategies in qualitative service provisions. The multidimensional qualitative preferences are...

We propose a novel dynamic metaheuristic optimization approach to compose an optimal set of IaaS service requests to align with an IaaS provider's long-term economic expectation. This approach is designed for the context that the IaaS provisioning subjects to resource and QoS constraints. In addition, the IaaS service requests have the features of...

We propose a new economic model based optimization approach to compose an optimal set of infrastructure service requests over a long-term period. The service requests have the features of variable arrival time and dynamic resource and QoS requirements. A new economic model is proposed that incorporates dynamic pricing and operation cost modeling of...

We propose a novel composition framework for an Infrastructure-as-a-Service (IaaS) provider that selects the optimal set of long-term service requests to maximize its profit. Existing solutions consider an IaaS provider's economic benefits at the time of service composition and ignore the dynamic nature of the consumer requests in a long-term perio...

We propose a cloud service composition framework that selects the optimal composition based on an end user’s long-term Quality of Service (QoS) requirements. In a typical cloud environment, existing solutions are not suitable when service providers fail to provide the long-term QoS provision advertisements. The proposed framework uses a new multiva...

The increasing numbers of web services impose automatic discovery process in Service Oriented Architecture (SOA). But the existing SOA enables only syntactic discovery which produces coarse irrelevant results or sometimes no results. Different researches challenge this problem by introducing semantic discovery process in SOA to enable relevant and...