Crowdsourced Live Streaming over the Cloud

Empowered by today's rich tools for media generation and distribution, and the convenient Internet access, crowdsourced streaming generalizes the single-source streaming paradigm by including massive contributors for a video channel. It calls a joint optimization along the path from crowdsourcers, through streaming servers, to the end-users to minimize the overall latency. The dynamics of the video sources, together with the globalized request demands and the high computation demand from each sourcer, make crowdsourced live streaming challenging even with powerful support from modern cloud computing. In this paper, we present a generic framework that facilitates a cost-effective cloud service for crowdsourced live streaming. Through adaptively leasing, the cloud servers can be provisioned in a fine granularity to accommodate geo-distributed video crowdsourcers. We present an optimal solution to deal with service migration among cloud instances of diverse lease prices. It also addresses the location impact to the streaming quality. To understand the performance of the proposed strategies in the realworld, we have built a prototype system running over the planetlab and the Amazon/Microsoft Cloud. Our extensive experiments demonstrate that the effectiveness of our solution in terms of deployment cost and streaming quality

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa

AN EFFICIENT APPROACH TO IMPLEMENT FEDERATED CLOUDS

Cloud computing is one of the trending technologies that provide boundless virtualized resources to the internet users as an important services through the internet, while providing the privacy and security. By using these cloud services, internet users get many parallel computing resources at low cost. It predicted that till 2016, revenues from the online business management spent $4 billion for data storage. Cloud is an open source platform structure, so it is having more chances to malicious attacks. Privacy, confidentiality, and security of stored data are primary security challenges in cloud computing. In cloud computing, ‘virtualization' is one of the techniques dividing memory into different blocks. In most of the existing systems there is only single authority in the system to provide the encrypted keys. To fill the few security issues, this paper proposed a novel authenticated trust security model for secure virtualization system to encrypt the files. The proposed security model achieves the following functions: 1) allotting the VSM(VM Security Monitor) model for each virtual machine; 2) providing secret keys to encrypt and decrypt information by symmetric encryption.The contribution is a proposed architecture that provides a workable security that a cloud service provider can offer to its consumers. Detailed analysis and architecture design presented to elaborate security model

A Novel Energy Model for Renewable Energy-Enabled Cellular Networks Providing Ancillary Services to the Smart Grid

In this paper, we consider cellular networks powered by the smart grid (SG) and by local renewable energy (RE) sources. While this configuration promises energy savings, usage of cleaner energy, and cost reduction, it has some intrinsic complexity due to the interaction between the network operators and the SG. Motivated by the significant advancement in the SG, we consider the case where cellular networks provide the SG with ancillary services by replying to the grid's explicit requests to increase or decrease their grid consumption. We propose a new approach for configuring and operating base stations (BSs) to provide ancillary services. Based on real data, we model the energy state of a BS as a Markov chain taking into account the proposed energy management policy, randomness of SG requests, and RE generation. We use the model to evaluate the performance of the system, and to decide proper settings of its parameters in order to minimize the energy operational cost. The performance of our proposal is then compared against those of other approaches. Results show that important cost savings, with negligible degradation in quality of service, are possible when RE generation, SG patterns, and storage sizes are properly taken into account