| Description |
1 online resource (210 p.) |
| Series |
Chapman and Hall/CRC Distributed Sensing and Intelligent Systems Ser |
|
Chapman and Hall/CRC Distributed Sensing and Intelligent Systems Ser
|
| Contents |
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- List of Tables and Figures -- Preface -- Editors -- Contributors -- About This Book -- Chapter 1: Analysis of Biological Information Using Statistical Techniques in Cloud Computing -- 1.1 What Is Bioinformatics? -- 1.1.1 A Brief History -- 1.1.2 Tools and Techniques -- 1.1.3 Future Scope -- 1.2 Cloud Analytics -- 1.2.1 Analytic Services -- 1.2.2 Bioinformatics Cloud -- 1.3 Bioinformatics Cloud Computing Services -- 1.3.1 Data as a Service (DaaS) -- 1.3.1.1 EMBOSS -- 1.3.1.2 J-GLOBAL |
|
1.3.1.3 Gene Set Builder -- 1.3.1.4 BioDWH -- 1.3.1.5 AWS Public Datasets -- 1.3.1.6 SeqHound -- 1.3.2 Software as a Service (SaaS) -- 1.3.2.1 Lhasa Cloud -- 1.3.2.2 eCEO -- 1.3.2.3 StormSeq -- 1.3.2.4 Crossbow -- 1.3.2.5 CloudBurst -- 1.3.3 Platform as a Service (PaaS) -- 1.3.3.1 DNAnexus -- 1.3.3.2 Magallanes -- 1.3.3.3 Google Genomics -- 1.3.3.4 Syapse -- 1.3.3.5 BioServices -- 1.3.3.6 Eoulsan -- 1.3.4 Infrastructure as a Service (IaaS) -- 1.3.4.1 Google Compute Engine -- 1.3.4.2 GoGrid -- 1.3.4.3 HP Helion -- 1.3.4.4 Joyent -- 1.4 CSIM Architecture -- 1.5 Implementation Challenges |
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1.5.1 Security and Privacy -- 1.5.2 Legal Aspects -- References -- Chapter 2: Intelligent Cloud Computing and Bioinformatics Data Analysis -- 2.1 Introduction -- 2.1.1 Introduction to Intelligent Cloud Computing -- 2.1.2 Contemporary Advancements in Bioinformatics Data Analysis -- 2.1.3 Reasons for the Use of Intelligent Cloud Computing in Bioinformatics -- 2.1.4 Terminology and Abbreviations -- 2.2 Principal Disciplines of Intelligent Cloud Computing and Bioinformatics Data Analysis -- 2.2.1 Intelligent Cloud Computing Architecture -- 2.2.2 Current Frameworks in Bioinformatics Data Analysis |
|
2.2.2.1 MapReduce with Hadoop for Big Data Analysis -- 2.2.2.2 Applications of Service Models -- 2.2.2.3 Cloud Developments in Translational Biomedical Sciences -- 2.3 Bioinformatics Data Analysis Methodologies Compared -- 2.3.1 AiNET (Artificial Immune NETwork) -- 2.3.2 Microarray Data Analysis -- 2.4 Challenges and Opportunities -- 2.4.1 Technical Challenges and Scope for Improvement -- 2.4.1.1 Workload Factoring -- 2.4.1.2 Network Bandwidth -- 2.4.1.3 Heterogeneous Distributed Database System -- 2.4.2 Implementations and Applications -- 2.5 Further Advancements -- 2.6 Conclusion -- References |
|
Chapter 3: Cloud Computing Service Models: Traditional and User-Centric Approaches -- 3.1 Introduction -- 3.2 Traditional Cloud Computing Service Models -- 3.2.1 Types of Traditional Cloud Computing Service Models -- 3.2.1.1 Infrastructure as a Service -- 3.2.1.2 Platform as a Service -- 3.2.1.3 Software as a Service -- 3.2.2 Security Issues in Traditional Cloud Computing Service Models -- 3.2.2.1 Security Problems of SaaS -- 3.2.2.2 Security Problems of PaaS -- 3.2.2.3 Security Problems of IaaS -- 3.2.2.4 Current Security Solutions -- 3.2.3 Summary |
| Notes |
Description based upon print version of record |
|
3.3 A User-Centric Approach to a Mobile Cloud Computing Service Model |
| Subject |
Cloud computing.
|
| Form |
Electronic book
|
| Author |
Sharma, Moolchand
|
|
Elhoseny, Mohamed
|
| ISBN |
9781000214468 |
|
100021446X |
|
