Resource Distribution Estimation for Data-Intensive Workloads: Give Me My Share &amp; No One Gets Hurt!

Khoshkbarforoushha, Alireza; Ranjan, Rajiv; Strazdins, Peter

doi:10.1007/978-3-319-33313-7_17

Cited by 2 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model will be applied in the context of autonomic management of cloud resources to adapt to variations in the application workload [40]. In addition, we have developed a number of algorithms to select, optimise, provision/schedule and monitor cloud resources for different scenarios and resources (refer to [41][42][43][44][45][46][47][48][49][50][51][52][53][54][55]).…”

Section: Scalable Cloud Computingmentioning

confidence: 99%

Internet of Things (IoT) and Cloud Computing Enabled Disaster Management

Gaire

Sriharsha

Puthal

et al. 2020

Scalable Computing and Communications

Self Cite

View full text Add to dashboard Cite

Disaster management demands a near real-time information dissemination so that the emergency services can be provided to the right people at the right time. Recent advances in information and communication technologies enable collection of real-time information from various sources. For example, sensors deployed in the fields collect data about the environment. Similarly, social networks like Twitter and Facebook can help to collect data from people in the disaster zone. On one hand, inadequate situation awareness in disasters has been identified as one of the primary factors in human errors with grave consequences such as loss of lives and destruction of critical infrastructure. On the other hand, the growing ubiquity of social media and mobile devices, and pervasive nature of the Internet-of-Things means that there are more sources of outbound traffic, which ultimately results in the creation of a data deluge, beginning shortly after the onset of disaster events, leading to the problem of information tsunami. In addition, security and privacy has crucial role to overcome the misuse of the system for either intrusions into data or overcome the misuse of the information that was meant for a specified purpose. These problems can be addressed by processing the collected data in real-time and extracting meaningful and actionable information for emergency providers while taking care of security and privacy aspects. Such situationawareness applications demand a large amount of computing resources. The cloud, which provides elastic and scalable infrastructure, becomes the natural choice for such applications. In this chapter, we provide such a situation aware application to support disaster management data lifecycle, i.e. from data ingestion and processing to alert dissemination. We utilize cloud computing, Internet of Things and social computing technologies to achieve a scalable, efficient, and usable situation-aware application called Cloud4BigData.

show abstract