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Abstract-Smartphones are now capable of supporting a wide range of applications, many of which demand an ever increasing computational power. This poses a challenge because smartphones 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.

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.Index Terms-Controller design, data centers, energy efficiency.

Mobile ad hoc networks (MANETs) are infrastructureless and distributed communication systems that require sophisticated approaches to routing to cope with node mobility and heterogeneous application requirements. In the past few years, distributed hash table (DHT) has come forth as a useful additional technique to the design and specification of spontaneous and self-organized networks. Researchers have exploited its advantages by implementing it at the network layer and developing scalable routing protocols for MANETs. The implementation of DHT-based routing in a MANET requires different algorithms and specifications compared to routing in the Internet because a MANET has its unique characteristics, such as node mobility, spontaneous networking, decentralized architecture, limited transmission range, dynamic topology, and frequent network partitioning/merging. In this article, we present a comprehensive survey of research related to DHT-based routing that aims at enhancing the scalability of MANETs. We present a vivid taxonomy of DHT-based routing protocols and the guidelines to design such protocols for MANETs. We compare the features, strengths, and weaknesses of existing DHT-based routing protocols and highlight key research challenges that are vital to address. The outcome of the analysis serves as a guide for anyone willing to delve into research on DHT-based routing in MANETs.