Academic Cloud Computing Research: Five Pitfalls and Five Opportunities

This discussion paper argues that there are five fundamental pitfalls, which can restrict academics from conducting cloud computing research at the infrastructure level, which is currently where the vast majority of academic research lies. Instead academics should be conducting higher risk research, in order to gain understanding and open up entirely new areas. We call for a renewed mindset and argue that academic research should focus less upon physical infrastructure and embrace the abstractions provided by clouds through five opportunities: user driven research, new programming models, PaaS environments, and improved tools to support elasticity and large-scale debugging. The objective of this paper is to foster discussion, and to define a roadmap forward, which will allow academia to make longer-term impacts to the cloud computing community.Comment: Accepted and presented at the 6th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'14

Survey on Various Trust Management Issues in Cloud Environments

Over the past few years, trust management has been one of the hot topics especially in the area of cloud computing. Well-known benefits resulting from cloud computing adoption, several issues have emerged during its evolution: most of them relate to security, privacy and trust management. In particular, its proliferation has placed even more attention to trust management, representing one of the key challenges in the adoption of cloud computing technologies. This paper proposes a survey of existing trust management models addressing collaboration agreements in cloud computing scenarios. Main limitations of current approaches are outlined and possible improvements are traced, as well as a future research path

3rd workshop on hot topics in cloud computing performance (HotCloudPerf'20):Performance variability

The organizers of the Third Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf 2020) are delighted to welcome you to the workshop proceedings as part of the ICPE conference companion. The HotCloudPerf 2020 workshop is a full-day workshop on Tuesday, April 21, taking place jointly with WOSP-C as part of the ICPE conference week in Edmonton, Canada. Each year, the workshop chooses a focus theme to explore; for 2020, the theme is "Performance variability of cloud datacenters and the implications of such phenomena on application performance" Cloud computing is emerging as one of the most profound changes in the way we build and use IT. The use of global services in public clouds is increasing, and the lucrative and rapidly

DCCast: Efficient Point to Multipoint Transfers Across Datacenters

Using multiple datacenters allows for higher availability, load balancing and reduced latency to customers of cloud services. To distribute multiple copies of data, cloud providers depend on inter-datacenter WANs that ought to be used efficiently considering their limited capacity and the ever-increasing data demands. In this paper, we focus on applications that transfer objects from one datacenter to several datacenters over dedicated inter-datacenter networks. We present DCCast, a centralized Point to Multi-Point (P2MP) algorithm that uses forwarding trees to efficiently deliver an object from a source datacenter to required destination datacenters. With low computational overhead, DCCast selects forwarding trees that minimize bandwidth usage and balance load across all links. With simulation experiments on Google's GScale network, we show that DCCast can reduce total bandwidth usage and tail Transfer Completion Times (TCT) by up to $50\%$ compared to delivering the same objects via independent point-to-point (P2P) transfers.Comment: 9th USENIX Workshop on Hot Topics in Cloud Computing, https://www.usenix.org/conference/hotcloud17/program/presentation/noormohammadpou

Turning down the lamp: Software specialisation for the cloud

© USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2010.All right reserved. The wide availability of cloud computing offers an unprecedented opportunity to rethink how we construct applications. The cloud is currently mostly used to package up existing software stacks and operating systems (e.g. LAMP) for scaling out websites. We instead view the cloud as a stable hardware platform, and present a programming framework which permits applications to be constructed to run directly on top of it without intervening software layers. Our prototype (dubbed Mirage) is unashamedly academic; it extends the Objective Caml language with storage extensions and a custom run-time to emit binaries that execute as a guest operating system under Xen. Mirage applications exhibit significant performance speedups for I/O and memory handling versus the same code running under Linux/Xen. Our results can be generalised to offer insight into improving more commonly used languages such as PHP, Python and Ruby, and we discuss lessons learnt and future directions

Fog Computing Architecture for Indoor Disaster Management

Most people spend their time indoors. Indoors have a higher complexity than outdoors. Moreover, today's building structures are increasingly sophisticated and complex, which can create problems when a disaster occurs in the room. Fire is one of the disasters that often occurs in a building. For that, we need disaster management that can minimize the risk of casualties. Disaster management with cloud computing has been extensively investigated in other studies. Traditional ways of centralizing data in the cloud are almost scalable as they cannot cater to many latency-critical IoT applications, and this results in too high network traffic when the number of objects and services increased. It will be especially problematic when in a disaster that requires a quick response. The Fog infrastructure is the beginning of the answer to such problems. This research started with an analysis of literature and hot topics related to fog computing and indoor disasters, which later became the basis for creating a fog computing-based architecture for indoor disasters. In this research, fog computing is used as the backbone in disaster management architecture in buildings. MQTT is used as a messaging protocol with the advantages of simplicity and speed. This research proposes a disaster architecture for indoor disasters, mainly fire disasters

Human-Centric Cyber Social Computing Model for Hot-Event Detection and Propagation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Microblogging networks have gained popularity in recent years as a platform enabling expressions of human emotions, through which users can conveniently produce contents on public events, breaking news, and/or products. Subsequently, microblogging networks generate massive amounts of data that carry opinions and mass sentiment on various topics. Herein, microblogging is regarded as a useful platform for detecting and propagating new hot events. It is also a useful channel for identifying high-quality posts, popular topics, key interests, and high-influence users. The existence of noisy data in the traditional social media data streams enforces to focus on human-centric computing. This paper proposes a human-centric social computing (HCSC) model for hot-event detection and propagation in microblogging networks. In the proposed HCSC model, all posts and users are preprocessed through hypertext induced topic search (HITS) for determining high-quality subsets of the users, topics, and posts. Then, a latent Dirichlet allocation (LDA)-based multiprototype user topic detection method is used for identifying users with high influence in the network. Furthermore, an influence maximization is used for final determination of influential users based on the user subsets. Finally, the users mined by influence maximization process are generated as the influential user sets for specific topics. Experimental results prove the superiority of our HCSC model against similar models of hot-event detection and information propagation