Muhammad T. Anan

Scenario-based requirements analysis techniques for real-time software systems: a comparative evaluation

One of the most critical phases of software engineering is requirements elicitation and analysis. Success in a software project is influenced by the quality of requirements and their associated analysis since their outputs contribute to higher level design and verification decisions. Real-time software systems are event driven and contain temporal and resource limitation constraints. Natural-language-based specification and analysis of such systems are then limited to identifying functional and non-functional elements only. In order to design an architecture, or to be able to test and verify these systems, a comprehensive understanding of dependencies, concurrency, response times, and resource usage are necessary. Scenario-based analysis techniques provide a way to decompose requirements to understand the said attributes of real-time systems. However they are in themselves inadequate for providing support for all real-time attributes. This paper discusses and evaluates the suitability of certain scenario-based models in a real-time software environment and then proposes an approach, called timed automata, that constructs a formalised view of scenarios that generate timed specifications. This approach represents the operational view of scenarios with the support of a formal representation that is needed for real-time systems. Our results indicate that models with notations and semantic support for representing temporal and resource usage of scenario provide a better analysis domain.

An architecture-centric software maintainability assessment using information theory

A robust model reference controller which supplies manipulated variables for controlling a multi-input multi-output process of the type which may not be modelled perfectly consists of a pre-compensator, a diagonal filter, and a post-compensator. The input signals to the robust model reference controller are first projected dynamically into decoupled signals by the pre-compensator. The diagonal filters then filter the decoupled signals individually. The filtered signals are projected back dynamically to the manipulated variables for the controlled process. The filter can easily be tuned to attain the optimal response of the closed-loop system with a given bound of model uncertainty.

Smart grid opportunities and challenges of integrating renewable sources: A survey

The smart grid is a new and improved power grid that seems to have all the solutions to our energy problems. The technology for the smart grid is still in the research and development phase but it is rapidly growing. There are many opportunities to be taken advantage of when talking about the smart grid. The possibility for the seamless integration of renewable energy resources and ushering in a new era of consumer choice is evident. However, there are still many challenges to be overcome in the pursuit of the smart grid. Energy storage is one of the biggest hurdles engineers face today along with the communication needed for the smart grid. The most ideal and efficient way to set up the smart grid is still a mystery with standards not fully in place. This paper will help uncover some of these issues and review available solutions, projects, and technologies to address them.

A fault tolerant ATM switching architecture

This paper proposes a new fault-tolerant, self-routing, and high performance switching architecture for ATM networks based on multistage interconnection networks (MINs). It consists of two closely linked Banyan networks. Links are provided at every stage to allow cells to transfer to and from each plane. Reliability analysis shows that this architecture has a much fault-tolerance than some of the fault-tolerant ATM networks found in the literature. Simulation results also indicate that the proposed architecture offers better performance in terms of cell loss rates with or without the presence of faults in the network. The proposed architecture offers high throughput with acceptable cell delay time, low cost, simple routing, and priority of messages. Furthermore, the proposed switch architecture is modular in its design making it ideal for VLSI implementation.

A fuzzy-based collaborative localization algorithm for wireless sensor networks

Wireless Sensor Networks (WSNs) are being deployed in a variety of location-dependent applications, where the measurement of data is meaningless without accurate location. Many range-free algorithms were proposed in order to minimize the extra cost that appears in the ranged-based algorithms. Fuzzy logic provides a simple, fast and cost efficient way that can be used in range-free algorithms. In this paper, we propose a fuzzy-based collaborative localization algorithm for wireless sensor networks. Our proposed algorithm implements a Sugeno-type fuzzy system using a collaborative feedback communication scheme. The proposed algorithm provides more accurate localization estimation without any additional hardware implementation. The simulation results demonstrate the effectiveness of the proposed approach.

SLA-Based Optimization of Energy Efficiency for Green Cloud Computing

Rapid growth and demand for computational power by scientific, business and web-applications has led to the creation of large-scale datacenters consuming enormous amounts of power. Improving the efficiency of datacenters, with a focus on power consumption and carbon emission, is a topical theme on which we are witnessing an increasing amount of academic and industrial research. The objective of this paper is to design and implement an energy efficient computing framework for green cloud datacenters that improves energy efficiency, reduces operational costs, and meets required Quality of Service (QoS). A dynamic migration algorithm is proposed to minimize the cost of energy in consideration of SLAs. The proposed approach utilizes one of the most promising technologies in the areas of server virtualization research area, namely Software Defined Networking (SDN) using OpenFlow technology. Obtained results demonstrate that the efficiency of the resource usage and reduced power consumption of the cloud can coexist with Service Level Agreements (SLAs) while keeping the cost of penalties and power consumption to a minimum.

Empowering networking research and experimentation through Software-Defined Networking

Software-Defined Networking (SDN) is an evolving network architecture influenced by the increasing popularity in the deployment of Network Virtualization, cloud computing technologies, and the network ossification trend. It represents a new approach to managing, defining and building networks in order to fulfill the needs of the dynamic nature of present days networking capabilities. In recent years, SDN has emerged as an exciting area of research challenging the current networking paradigm of designing and managing computer networks. SDN represents an extraordinary opportunity to rethink computer networks, enabling the design and deployment of a future Internet. This paper reviews SDN technologies, architectures, applications, underlying protocols, and deployments. It provides taxonomy of recent research works on SDN and highlights some recent practical experiments, with the goal of inspiring new applications and improving the future networking capabilities.

Energy efficient data dissemination in wireless sensor networks based on natural selection

The goal of this paper is to design and implement an efficient data dissemination algorithm for wireless sensor networks. The proposed approach requires nodes in a network to publish their characteristics to their neighboring nodes. Each node selects its parent node for data forwarding using a method similar to natural selection. Fitness score for selection is locally calculated considering several characteristics of a neighboring node such as: battery level, distance, and hierarchy level. The main goal of this algorithm is to extend the wireless sensor network lifetime by distributing the traffic load among the nodes that have higher probabilities of predicted survival, which is identified by their fitness score. In addition, this approach can provide a framework to study the emergent behaviors of networks when different local rules for node selection are applied.

An efficient artificial landmark-based system for indoor and outdoor identification and localization

Current technologies for localization such as Global Positioning Systems (GPS) and Inertial Measurement Unit (IMU) have limitations in terms of accuracy, cost, signal attenuation and need for re-calibration over time, which leads to a compromise in performance and accuracy. In this paper, we present a novel Artificial Landmark-Based Identification System (ALIS), which can be used in both indoor and outdoor localization applications. ALIS is a multi-part landmark-based localization approach, which uses template matching techniques to find multiple landmark patterns in an image to estimate distance from the landmark.

An identification and prevention of theft-of-service attack on cloud computing

Cloud computing, an emerging paradigm, has shifted the shape of computing models from technology to a utility. However, data integrity, privacy, trust and secure cloud infrastructure are amongst the major issues which can subvert the wide benefits and deployment of cloud computing. Cloud computing uses virtualization to provide scalable, efficient and low cost IT services to users. The back bone of virtualization is hypervisor which mapped logical hardware with physical hardware and make one computer appear as many. Hypervisor vulnerabilities can favor the attacker to use the VM (virtual machine) for a longer period and pay less amount by resetting/manipulating the variables (i.e. which store CPU and memory etc. usage of VM, used by user, to charge him at the end) resulting in an attack called theft-of-service attack. This attack, caused by stealing VM, can affect the cloud infrastructure financially as well as there will be no record of users activity during his stay on cloud which lead to a greater risk to success of cloud computing. In this paper, we investigated the limitations of Kernel Virtual Machine together with the QEMU emulator in private cloud and provided the solution, in term of an API based VMs power consumption that will identify and prevent theft-of-service attack. This solution has been implemented in a private cloud to determine the efficiency of proposed API. We concluded that our API can detect and prevent theft-of-service attack in cloud with respect to different scenarios.