Accessing Data From Multiple Heterogeneous Distributed Database Systems

This chapter describes the method to retrieve data from multiple heterogeneous distributed relational database management systems such as MySQL, PostgreSQL, MS SQL Server, MS Access, etc. into Oracle RDBMS using Oracle's Heterogeneous Gateway Services. The complete process starting from downloading and installation of required software, creation of data source names using open database connectivity, modification of system parameter files, checking connections, creation of synonyms for tables of remote databases into oracle, creation of database links and accessing data from non-oracle databases using database links is explained in great detail. Apart from this, data manipulation in remote databases from Oracle and execution of PL/SQL procedures to manipulate data residing on remote databases is discussed with examples. Troubleshooting common errors during this process is also discussed.

A P2P Architecture for Social Networking

Social networking systems are usually huge centralized systems owned by a single company. However, this solution has many drawbacks (e.g., lack of privacy, lack of anonymity, risks of censorship, and operating costs). This chapter proposes a novel P2P system that leverages existing, widespread, and stable technologies such as DHTs and BitTorrent. In particular, it introduces a key-based identity system and a model of social relations for distributing content efficiently among interested readers. The proposed system, called Blogracy, is a micro-blogging social networking system focused on (1) anonymity and resilience to censorship, (2) authenticatable content, and (3) semantic interoperability using activity streams. This chapter presents the model and the implementation of the Blogracy system, discusses the experimentations to study its behavior, and presents their results regarding (1) communication delays for some simulations of node churn, (2) delays measured in test operations over PlanetLab in direct communication, and (3) through the I2P anonymizing network.

Enhancing Security in a Big Stream Cloud Architecture for the Internet of Things Through Blockchain

The Internet of Things (IoT) paradigm is foreseeing the development of our environment towards new enriched spaces in most areas of modern living, such as digital health, smart cities, and smart agriculture. Several IoT applications also have real-time and low-latency requirements and must rely on specific architectures. The authors refer to the paradigm that best fits the selected IoT scenario as “Big Stream” because it considers real-time constraints. Moreover, the blockchain concept has drawn attention as the next-generation technology through the authentication of peers that share encryption and the generation of hash values. In addition, the blockchain can be applied in conjunction with Cloud Computing and the IoT paradigms, since it avoids the involvement of third parties in a broker-free way. In this chapter, an analysis on mechanisms that can be adopted to secure Big Stream data in a graph-based platform, thus delivering them to consumers in an efficient and secure way, and with low latency, is shown, describing all refinements required employing federation-based and blockchain paradigms.

Trust Management in Fog Computing

Fog computing is an encouraging computational model that extends distributed cloud computing to the edge of systems. It varies to cloud computing with some of the attributes. Fog computing has new challenges while building and maintaining the trust among the fog nodes and with edge devices. The solutions applied for the various cloud challenges cannot be directly applied for fog computing. This chapter gives an overview of these difficulties and relates solutions in a concise way. It also highlights the open challenges that still exist in fog computing.

Transparent Throughput Elasticity for Modern Cloud Storage

Storage elasticity on the cloud is a crucial feature in the age of data-intensive computing, especially when considering fluctuations of I/O throughput. In this chapter, the authors explore how to transparently boost the I/O bandwidth during peak utilization to deliver high performance without over-provisioning storage resources. The proposal relies on the idea of leveraging short-lived virtual disks of better performance characteristics (and more expensive) to act during peaks as a caching layer for the persistent virtual disks where the application data is stored during runtime. They show how this idea can be achieved efficiently at the block-device level, using a caching mechanism that leverages iterative behavior and learns from past experience. Second, they introduce a corresponding performance and cost prediction methodology. They demonstrate the benefits of our proposal both for micro-benchmarks and for two real-life applications using large-scale experiments. They conclude with a discussion on how these techniques can be generalized for increasingly complex landscape of modern cloud storage.

Security Challenges and Resolution in Cloud Computing and Cloud of Things

Cloud computing is a developing zone of computing innovation that shapes the handling power and the computing assets of many associated, topographically separated PCs associated by means of internet. Cloud computing wipes out the need of having a total framework of equipment and programming to meet clients' prerequisites and applications. It very well may be thought of as a total or an incomplete outsourcing of equipment and programming assets. To get to cloud applications, a great internet association and a standard internet program are required. Cloud computing has its own particular downside from the security perspective; this chapter addresses the vast majority of these dangers and their conceivable arrangements. Cloud computing gives its client numerous abilities like getting to an expansive number of utilizations without the requirement for having a permit, acquiring, introducing, or downloading any of these applications.

Failure Detectors of Strong S and Perfect P Classes for Time Synchronous Hierarchical Distributed Systems

Present failure detection algorithms for distributed systems are designed to work in asynchronous or partially synchronous environments on mesh (all-to-all) connected systems and maintain status of every other process. Several real-time systems are hierarchically connected and require working in strict synchronous environments. Use of existing failure detectors for such systems would generate excess computation and communication overhead. The chapter describes two suspicion-based failure detectors of Strong S and Perfect P classes for hierarchical distributed systems working in time synchronous environments. The algorithm of Strong S class is capable of detecting permanent crash failures, omission failures, link failures, and timing failures. Strong completeness and weak accuracy properties of the algorithm are evaluated. The failure detector of Perfect P class is capable of detecting crash failures, crash-recovery failures, omission failures, link failures, and timing failures. Strong completeness and strong accuracy properties of the failure detector are evaluated.

Topology Optimization for Heterogeneous DHT-Based Multicast

Since the deployment of IP multicast remains restricted due to many practical and political issues, researchers have shifted focus to exploiting application-layer multicast for multicast data delivery. Recently there has been considerable interest in applying DHT routing algorithms to application-level multicast. However, early DHT-based multicast protocols are insufficient in addressing a number of technical issues such as heterogeneous capacity of nodes or node churn. In this chapter, the author describes a solution called BAM-Chord (i.e., Bandwidth Adaptive Multicast over Chord) that optimizes the topology of a multicast tree based on node bandwidth. In the proposed solution, node position (i.e., node identifier) on a BAM-Chord ring will be decided based on node bandwidth capacity such that it can build a wide and balanced multicast tree rooted at the source node. As a result, BAM-Chord protocol can utilize network resources of every node to reduce the depth of the multicast tree and take advantages of DHTs in maintaining the multicast tree.

Convergence of Manufacturing Cloud and Industrial IoT

The manufacturing cloud (CMfg) covers the use of three key technologies including cloud computing, the industrial internet of things (IIoT), and collaborative engineering for achieving the productivity and quality challenges in the big manufacturing, which is enabled due to the communication, mobile, and broadcasting network. It is necessary to establish a flexible and adaptive infrastructure for manufacturing industry to share and use various manufacturing resources and services on-demand under the dynamic, complicated, and large-scale business environment. The CMfg makes the industry more agile, responsive, and reconfigurable for exposure to the industry as a global manufacturing enterprise. The chapter considers the CMfg facets and IIoT, use cases in the manufacturing industry, and explains IIoT and CMfg as a complementary technology.

Cloud Computing and Innovations

Cloud computing ignited many innovations and disruptions in the traditional way of doing business. The innovations in cloud computing are countable, and innovations due to cloud computing are endless, as there are several applications where cloud computing has proven its usefulness. The discussion starts with innovation records by software companies that happened due to cloud computing. This chapter illuminates an amalgamation of advanced concepts, products, and services in cloud computing. The chapter further discusses the conceptual innovations of API management, serverless computing, content delivery network, storage services, data center technologies, all-flash arrays, and digital twin due to cloud computing.