Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly important area.

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Cloud computing: state-of-the-art and research challenges

Information Theory and Reliable Communication

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

人教版高中英语新课程教材中,语言运用（Using Language）是每个单元必不可少的部分,提供了围绕单元中心话题的听、说、读、写的综合性练习,是单元中心话题的延续和升华.如何设计Using Language部分的教学,使自己的教学模式既不落俗套,又能真正体现新课程标准所倡导的教学理念,正是广大一线英语教师一直努力探索的问题.

打磨Using Language,倡导新理念

Cloud computing environments allow customers to dynamically scale their applications. The key problem is how to lease the right amount of resources, on a pay-as-you-go basis. Application re-dimensioning can be implemented effortlessly, adapting the resources assigned to the application to the incoming user demand. However, the identification of the right amount of resources to lease in order to meet the required Service Level Agreement, while keeping the overall cost low, is not an easy task. Many techniques have been proposed for automating application scaling. We propose a classification of these techniques into five main categories: static threshold-based rules, control theory, reinforcement learning, queuing theory and time series analysis. Then we use this classification to carry out a literature review of proposals for auto-scaling in the cloud.

A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments

Virtualizing the x86-based data center creates a dynamic environment for server application deployment and resource sharing. Resource management in this environment is challenging as applications are under fluctuating workloads causing diverse resource demands across their tiers. Resource allocation adaptation is essential for high performance machine utilization. This paper presents feedback controllers that dynamically adjust the CPU allocations of multi-tier applications in order to adapt to workload changes by considering the resource coupling between utilizations of application components. Our experimental evaluation on a virtualized 3-tier Rubis server application shows that our techniques work effectively.

Resource Provisioning for Multi-Tier Virtualized Server Applications

Dynamic resource provisioning for virtualized server applications is integral to achieve efficient cloud and green computing. In server applications unpredicted workload changes occur frequently. Resource adaptation of the virtual hosts should dynamically scale to the updated demands (cloud computing) as well as co-locate applications to save on energy consumption (green computing). Most importantly, resource transitions during workload surges should occur while minimizing the expected loss due to mismatches of the resource predictions and actual workload demands. Our approach is to minimize the maximum expected loss using the same techniques as in two-person zero-sum games. We develop an ℋ ∞ filter that minimizes the worst-case estimation and allocate resources fast. Through simulations our ℋ ∞ filter demonstrates its effectiveness and good performance when compared against Kalman-based controllers.

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A min-max framework for CPU resource provisioning in virtualized servers using ℋ ∞ Filters

This paper studies the robustness of the well known Foschini-Miljanic power control algorithm with respect to time-varying delays. Since delays are omnipresent in wireless networks, this problem is of practical importance. It has been proven in the past that no matter how large the delays are, the Foschini-Miljanic algorithm still converges. However, this was based on the assumption that the delays are constant over time, which is not always met in practice. Therefore, the problem addressed in this paper is how the algorithm behaves under the time-varying delays case. Firstly, we provide the conditions under which the system is stable by means of a Linear Matrix Inequality (LMI) and using a semi-definite optimization solver we show the validity of our results through illustrative examples.

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On the stability of a power control algorithm for wireless networks in the presence of time-varying delays

In this work, we propose a buffer-aided successive opportunistic relaying scheme that aims to improve the average capacity of the network when inter-relay interference arises between relays that are selected for transmission and reception. In order to exploit the benefits of buffering at the relays, we propose a relay-pair selection policy that decouples the receiving relay at the previous time slot from being the transmitting relay at the next slot. Furthermore, we impose an interference cancellation threshold allowing the relay that is selected for reception, to decode and subtract the inter-relay interference. The proposed relaying scheme selects the relaying pair that maximizes the average capacity of the relay network. The performance of the proposed scheme is evaluated via simulation and comparisons with other state-of-the-art half and full-duplex relay selection schemes, in terms of outage probability, average capacity and average delay. The results reveal the need for a tradeoff between improving the outage on the cost of reduced capacity and increased delay, and vice versa. Finally, conclusions are drawn and future directions are discussed, including the need for a hybrid scheme incorporating both half and full-duplex characteristics.

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Capacity improvement through buffer-aided successive opportunistic relaying

We study a cooperative network with a buffer-aided multi-antenna source, multiple half-duplex (HD) buffer-aided relays and a single destination. Such a setup could represent a cellular downlink sce ...

Themistoklis Charalambous

Papers

Resource Provisioning for Multi-Tier Virtualized Server Applications

A min-max framework for CPU resource provisioning in virtualized servers using ℋ ∞ Filters

On the stability of a power control algorithm for wireless networks in the presence of time-varying delays

Capacity improvement through buffer-aided successive opportunistic relaying

Relay-pair selection in buffer-aided successive opportunistic relaying using a multi-antenna source