BigBird: Big Data Storage and Analytics at Scale in Hybrid Cloud

Abstract

Implementing big data storage at scale is a complex and arduous task that requires an advanced infrastructure. With the rise of public cloud computing, various big data management services can be readily leveraged. As a critical part of Twitter's "Project Partly Cloudy", the cold storage data and analytics systems are being moved to the public cloud. This paper showcases our approach in designing a scalable big data storage and analytics management framework using BigQuery in Google Cloud Platform while ensuring the security, privacy and data protection. The paper also discusses the limitations on the public cloud resources and how they can be effectively overcome when designing a big data storage and analytics solution at scale. Although the paper discusses the framework implementation in Google Cloud Platform, it can easily be applied to all major cloud providers.

Belief-Desire-Intention (BDI) Multi-agent System for Cloud Marketplace Negotiation

“…The paper proposed assigning a BDI agent for every infrastructure service for an enterprise that chooses to autonomously buy or sell cloud resources based on the demand. The author believes that the idea proposed in the paper would be helpful in building an autonomously managed service offering, for example, as mentioned in [15]. While this facilitates the granular control over reducing the cost incurred during the negotiation phase, the paper only focuses on co-ordination and co-operation aspects of the multi-agent system.…”