Sajjad Ahmad Madani

A Survey of Mobile Cloud Computing Application Models

Smart phones are now capable of supporting a wide range of applications, many of which demand an ever increasing computational power. This poses a challenge because smart phones are resource-constrained devices with limited computation power, memory, storage, and energy. Fortunately, the cloud computing technology offers virtually unlimited dynamic resources for computation, storage, and service provision. Therefore, researchers envision extending cloud computing services to mobile devices to overcome the smartphones constraints. The challenge in doing so is that the traditional smartphone application models do not support the development of applications that can incorporate cloud computing features and requires specialized mobile cloud application models. This article presents mobile cloud architecture, offloading decision affecting entities, application models classification, the latest mobile cloud application models, their critical analysis and future research directions.

Towards secure mobile cloud computing: A survey

Mobile cloud computing is gaining popularity among mobile users. The ABI Research predicts that the number of mobile cloud computing subscribers is expected to grow from 42.8 million (1.1% of total mobile users) in 2008 to 998 million (19% of total mobile users) in 2014. Despite the hype achieved by mobile cloud computing, the growth of mobile cloud computing subscribers is still below expectations. According to the recent survey conducted by the International Data Corporation, most IT Executives and CEOs are not interested in adopting such services due to the risks associated with security and privacy. The security threats have become a hurdle in the rapid adaptability of the mobile cloud computing paradigm. Significant efforts have been devoted in research organizations and academia to build secure mobile cloud computing environments and infrastructures. In spite of the efforts, there are a number of loopholes and challenges that still exist in the security policies of mobile cloud computing. This literature review: (a) highlights the current state of the art work proposed to secure mobile cloud computing infrastructures, (b) identifies the potential problems, and (c) provides a taxonomy of the state of the art.

A Survey of Mobile Device Virtualization: Taxonomy and State of the Art

Recent growth in the processing and memory resources of mobile devices has fueled research within the field of mobile virtualization. Mobile virtualization enables multiple persona on a single mobile device by hosting heterogeneous operating systems (OSs) concurrently. However, adding a virtualization layer to resource-constrained mobile devices with real-time requirements can lead to intolerable performance overheads. Hardware virtualization extensions that support efficient virtualization have been incorporated in recent mobile processors. Prior to hardware virtualization extensions, virtualization techniques that are enabled by performance prohibitive and resource consuming software were adopted for mobile devices. Moreover, mobile virtualization solutions lack standard procedures for device component sharing and interfacing between multiple OSSs. The objective of this article is to survey software- and hardware-based mobile virtualization techniques in light of the recent advancements fueled by the hardware support for mobile virtualization. Challenges and issues faced in virtualization of CPU, memory, I/O, interrupt, and network interfaces are highlighted. Moreover, various performance parameters are presented in a detailed comparative analysis to quantify the efficiency of mobile virtualization techniques and solutions.

Clustering-based power-controlled routing for mobile wireless sensor networks

This paper presents two new routing protocols for mobile sensor networks, viz. power-controlled routing (PCR) and its enhanced version, i.e. Enhanced Power-Controlled Routing (EPCR). In both the protocols, fixed transmission power is employed in the clustering phase but when ordinary nodes are about to send their data to their respective cluster-heads, they change their transmission power according to their distance from their cluster-head. While in PCR, the nodes are associated with the cluster-head on the basis of weight, in EPCR it is done on the basis of distance. In addition to the protocols, we are suggesting a packet loss recovery mechanism for the PCR and EPCR. Both protocols work well for both mobile and static networks and are designed to achieve high network lifetime, high packet delivery ratio, and high network throughput. These protocols are extensively simulated using mass mobility model, with different speeds and different number of nodes to evaluate their performance. Simulation results show that both PCR and EPCR are successful in achieving their objectives by using variable transmission powers and smart clustering. Copyright

Comparative study of trust and reputation systems for wireless sensor networks

Wireless sensor networks (WSNs) are emerging as useful technology for information extraction from the surrounding environment by using numerous small-sized sensor nodes that are mostly deployed in sensitive, unattended, and (sometimes) hostile territories. Traditional cryptographic approaches are widely used to provide security in WSN. However, because of unattended and insecure deployment, a sensor node may be physically captured by an adversary who may acquire the underlying secret keys, or a subset thereof, to access the critical data and/or other nodes present in the network. Moreover, a node may not properly operate because of insufficient resources or problems in the network link. In recent years, the basic ideas of trust and reputation have been applied to WSNs to monitor the changing behaviors of nodes in a network. Several trust and reputation monitoring (TRM) systems have been proposed, to integrate the concepts of trust in networks as an additional security measure, and various surveys are conducted on the aforementioned system. However, the existing surveys lack a comprehensive discussion on trust application specific to the WSNs. This survey attempts to provide a thorough understanding of trust and reputation as well as their applications in the context of WSNs. The survey discusses the components required to build a TRM and the trust computation phases explained with a study of various security attacks. The study investigates the recent advances in TRMs and includes a concise comparison of various TRMs. Finally, a discussion on open issues and challenges in the implementation of trust-based systems is also presented. Copyright

Quantitative comparisons of the state-of-the-art data center architectures

Data centers are experiencing a remarkable growth in the number of interconnected servers. Being one of the foremost data center design concerns, network infrastructure plays a pivotal role in the initial capital investment and ascertaining the performance parameters for the data center. Legacy data center network (DCN) infrastructure lacks the inherent capability to meet the data centers growth trend and aggregate bandwidth demands. Deployment of even the highest‐end enterprise network equipment only delivers around 50% of the aggregate bandwidth at the edge of network. The vital challenges faced by the legacy DCN architecture trigger the need for new DCN architectures, to accommodate the growing demands of the ‘cloud computing’ paradigm. We have implemented and simulated the state of the art DCN models in this paper, namely: (a) legacy DCN architecture, (b) switch‐based, and (c) hybrid models, and compared their effectiveness by monitoring the network: (a) throughput and (b) average packet delay. The presented analysis may be perceived as a background benchmarking study for the further research on the simulation and implementation of the DCN‐customized topologies and customized addressing protocols in the large‐scale data centers. We have performed extensive simulations under various network traffic patterns to ascertain the strengths and inadequacies of the different DCN architectures. Moreover, we provide a firm foundation for further research and enhancement in DCN architectures. Copyright

Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers

Cloud computing has emerged as the leading paradigm for information technology businesses. Cloud computing provides a platform to manage and deliver computing services around the world over the Internet. Cloud services have helped businesses utilize computing services on demand with no upfront investments. The cloud computing paradigm has sustained its growth, which has led to increase in size and number of data centers. Data centers with thousands of computing devices are deployed as back end to provide cloud services. Computing devices are deployed redundantly in data centers to ensure 24/7 availability. However, many studies have pointed out that data centers consume large amount of electricity, thus calling for energy-efficiency measures. In this survey, we discuss research issues related to conflicting requirements of maximizing quality of services (QoSs) (availability, reliability, etc.) delivered by the cloud services while minimizing energy consumption of the data center resources. In this paper, we present the concept of inception of data center energy-efficiency controller that can consolidate data center resources with minimal effect on QoS requirements. We discuss software- and hardware-based techniques and architectures for data center resources such as server, memory, and network devices that can be manipulated by the data center controller to achieve energy efficiency.

Energy-efficient data centers

Energy consumption of the Information and Communication Technology (ICT) sector has grown exponentially in recent years. A major component of the today’s ICT is constituted by the data centers which have experienced an unprecedented growth in their size and population, recently. The Internet giants like Google, IBM and Microsoft house large data centers for cloud computing and application hosting. Many studies, on energy consumption of data centers, point out to the need to evolve strategies for energy efficiency. Due to large-scale carbon dioxide (

On Architecture of Low Power Wireless Sensor Networks for Container Tracking and Monitoring Applications

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