Ismaeel Al Ridhawi

Location-aware data replication in cloud computing systems

With the increase in the number of mobile devices and the emergence of a plethora of cloud services, mobile cloud computing users require reliable and continuous access to data from cloud service providers. To support such continuous data access, we propose a location prediction method that provides a mechanism for identifying potential high user density locations. A partial data replication algorithm is used to exclusively replicate user requested data within third party cloud servers in advance. The proposed method aims to minimize the data access time, which is particularly subject to the location of the cloud server and the network bandwidth. Simulation experiments are performed to demonstrate the effectiveness of the proposed system for data access and replication.

A Policy-Based Simulator for Assisted Adaptive Vertical Handover

This paper proposes a new framework for future policy-based adaptive vertical handover (VHO) in heterogeneous wireless networks. In contrast to existing, statically configured, schemes that lack the ability to quickly adapt to changing network loads, the proposed framework continuously derives optimal configuration policies with respect to handover initiation and network selection. To achieve this goal, the proposed work relies on the interactions between two components: a policy-based real-time simulator and a VHO manager. Triggered by indications of VHO performance degradation, the former enacts a set of VHO scenarios, selected based on a predefined set of simulation policies, to evaluate possible new VHO configurations before actually applying them to the real network. Based on the outcome of the simulation and the monitored network performance, a set of VHO configuration policies is communicated to the VHO manager to reconfigure and/or fine-tune the running VHO scheme. Preliminary performance evaluation results demonstrate the significant enhancement of the outcome of the proposed VHO framework in terms of reducing the ping-pong phenomenon and the handover delay.

Client-Side Partial File Caching for Cloud-Based Systems

Distributed cloud applications acquire, generate tremendous amounts of stored information. The data associated with such applications are distributed widely in geographical terms. Replication services are designed to facilitate, support such cloud applications. A replication service aims to replicate data, select the most appropriate data replica from those available in order to minimize application access time. Current replica services can also exhibit an increase in data acquisition by clients resulting in slower data access. This paper proposes a Partial File Cache (PFC) strategy that minimizes the volume of data transfers under a limited cache space, provides faster data access simultaneously. Traditional caching approaches work well on networks with high latency, however, they can be expensive if an application only requires access to a small part of a large file. To improve cache utilization, our solution makes use of different techniques when caching, such as caching sections or parts of files. The system identifies user hotspots so that fit clients are selected for partial data caching to assist third party cloud storage sites. Results show significant improvement over traditional caching techniques when implemented in geographically spatial cloud environments.

Simulator-Assisted Joint Service-Level-Agreement and Vertical-Handover Adaptation for Profit Maximization

This paper presents a novel paradigm to jointly fine-tune service-level-agreements (SLAs) offered to mobile users and adapt accompanied vertical-handover (VHO) operations in future multi-technology wireless environments. In contrast to existing, statically configured, VHO schemes that lack the ability to quickly adapt to changing network loads, the proposed framework continuously derives optimal VHO configuration policies with respect to handover initiation and network selection. In addition, the proposed work reconfigures the newly created SLA instances offered to the new users according to network conditions with the objective of maximizing the service provider monetary profit. To achieve these goals, we derive a new model for VHO-based SLA that incorporates service guarantees during the transient phase of the VHO operation. Next, we present a generic model for the control and adaptation of any VHO scheme through the adoption of various types of policies. These models are incorporated in a novel architecture that relies on a policy-based real-time simulator as its core component for system adaptability. Performance evaluation results are presented to demonstrate the effectiveness of the proposed framework.

A context-aware and location prediction framework for dynamic environments

Context based dynamic adaptation of autonomous services and applications require the acquisition of an array of contextual information. Context dissemination mechanisms may result in network flooding, unrestricted access to private context information, and the inability of consumers to limit or personalize received context. Adapting context information disseminated to users is linked to direct contextual requests made by users. This paper describes policy- and ontology-based, context-aware system architecture. A Context Level Agreements is proposed to help deliver contextual information to users according to their needs. The paper illustrates use of the negotiation protocol through design and implementation of context-aware system architecture capable of acquiring, modeling, reasoning and disseminating context through ontologies.

Workflow-Net Based Service Composition Using Mobile Edge Nodes

Content delivery through cloud networks has gained popularity due to the cloud’s ability to provide on-demand services. However, composite services, such as customized multimedia content, introduce both delays and resource limitations if traditional cloud solutions are used. With recent advances in mobile edge computing, customized media delivery can be achieved through compositions of service specific overlays (SSOs). This paper presents a workflow-net-based mechanism for mobile edge node cooperation in fog-cloud networks to form guaranteed SSOs. The proposed solution uses a mathematical cooperation operator to turn the SSO composition problem expressed as workflow nets into algebraic representations. In turn, the minimal cost cooperative path from the workflow net is determined such that it guarantees the delivery of the requested composite media services to clients. Experimental results show that the composition process can be adequately established and carried out in a timely manner.

Policy-Based Personalized Context Dissemination for Location-Aware Services

This paper presents a policy-based context-level negotiation protocol and context-aware system architecture to personalize consumer-received context information through negotiations. Location tracking and prediction empower the system to shape contextual information delivered to users according to their expected needs.

Minimizing delay in IoT systems through collaborative fog-to-fog (F2F) communication

The recent advances in IoT technologies have led to the introduction of a plethora of networking, storage and computing systems. Today, the cloud computing system has evolved into the so-called fog-cloud computing paradigm to include computation, storage, and data exchange capabilities of edge devices. Although this rapid pace of evolution has led to the introduction of many IoT smart scenarios, many low-latency high-rate service scenarios are still considered impractical to be implemented. In this paper, we introduce a fog-to-fog (F2F) communication algorithm that allows fogs to communicate with each other to process job requests. In this type of communication paradigm, fogs are not limited to either execute a task or forward it to the cloud but also have the capability to collaborate with other neighboring fogs. This will minimize the overall end-to-end (e2e) latency. Case studies are considered in this paper to demonstrate that the adopted strategy may be applied to the Fog-Cloud system to reduce the overall e2e delay.

A policy-based location-aware framework for personalized services in cloud computing systems

Autonomous service adaptation in cloud environments requires both location-awareness and the acquisition and utilization of contextual information. Statically configured service adaptation frameworks lack the ability to adapt to changing network conditions and geographical locations. This paper presents a framework that continuously derives updated configuration policies with respect to service selection and handover to third party cloud service providers. Location tracking and prediction empower the system to provide ongoing robust services for cloud service subscribers. To achieve this goal, the proposed work relies on a policy-based real-time simulator to evaluate possible new service provider handover configurations before actually applying them to the real network. Preliminary performance evaluation results demonstrate the significant enhancement of the outcome of the proposed framework in terms of continuous services for subscribers and load balancing for service providers.

An Adaptive Vertical Handover in Service Specific Overlay Networks

This paper proposes a new vertical handover (VHO)-enhanced mobile service discovery and composition method over a hybrid service overlay network (H-SON). The overlay considers the dynamic characteristics of mobile nodes in the decision for node placement as well as the types of services provided and Quality of Service (QoS) levels. The mobile nature of media clients provokes a necessity to consider VHO operations to meet the requirements of offered service level agreements (SLAs). The integrated framework continuously derives optimal VHO configuration policies with respect to handover initiation and network selection for service specific overlay network (SSON) node migration. The VHO-enhanced service composition method allows for efficient, accurate, and QoS-aware component service discovery, composition, and execution. We demonstrate that our approach provides better performance and reduced composition delay in heterogeneous network environments when compared to other service-composition solutions.