Abstract-Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users' physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

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Abstract-With the confluence of the growing market for mobile Internet devices, and users' expectations of instant access to high-quality multimedia content, the delivery of video over wireless networks has become the challenge of the decade. Dynamic Adaptive Streaming over HTTP (DASH) and WebRTC are new and evolving standards that have been developed specifically to meet this demand and enable a high-quality experience for mobile users of video on demand and real time communication services, respectively. However, there has been no systematic study of how these services are experienced by users in a realistic mobile setting. In this work, we describe measurements collected from DASH and WebRTC implementations while moving at walking speeds through an 802.16e WiMAX network. Using data from the application, network, and physical layers, in different wireless environments, we identify characteristics of the cellular data network that directly impact the quality of video service, and suggest areas for further improvement.

Network virtualization allows multiple logical networks to coexist on the same physical infrastructure. A key problem that needs to be solved in this context is management of substrate network resources, in particular when mapping virtual network requests to the substrate. Several efficient algorithms have been proposed to provide effective solutions, but they assume that the virtual network request topology is given. In this paper, we show that the use of these topologybased requests may limit the efficiency of physical network usage. As an alternative, we propose a problem formulation and mapping algorithm that is based on traffic matrices to specify virtual network requests.

Summary Efficient and fair resource allocation for multitudinous virtual networks running cloud‐based applications is crucial to archive dynamic resources multi‐tenancy in cloud computing. In order to solve the problem, we propose a novel virtual network embedding (VNE) algorithm to increase revenue and utilization of substrate network as well as to improve acceptance fairness of virtual networks. First, we present a virtual topology pre‐transformation mechanism leveraging reusable technology to reduce topology difference and achieve acceptance fairness. Then, because of the Non‐deterministic polynomial‐time (NP)‐hard characteristics of VNE, we model the problem as an integer linear programming problem and solve the VNE problem with a discrete particle swarm optimization‐based algorithm. The operations and parameters of particles are well redefined according to the VNE context. Finally, an incentive convergence mechanism is proposed to reduce mapping complexity, which can be used to accelerate convergence and to save more bandwidth by exploiting individual candidate nodes' lists. Simulation results prove that our proposed method is superior to the existing similar algorithms in terms of physical resource utilization, acceptance fairness, revenue/cost ratio, and searching efficiency. Copyright © 2016 John Wiley & Sons, Ltd.

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