Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> Cloud computing provides on-demand comput- ing services and data. The cloud infrastructure can be owned by a private organization, a group of organizations, or the public. In this work, the feasibility of using cloud computing for the optimization of machining processes is explored. A web system is developed in which a main server keeps the repository of data and carries out optimization. The main server can provide the optimized process parameters on demand to various clients. The clients can use the optimized data and fine-tune them if necessary. The clients send the feedback to the server, which is utilized with the help of a probability-based approach. The case examples show the feasibility of using the system for helping in agile manufacturing. <s> BIB001 </s> Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> The evolution of technologies of informatics and telecommunications has improved significantly the way water distribution systems can be managed. The use of quasi real-time information is becoming a desired standard in many water utilities. Nevertheless, tools for water distribution system analysis and for supporting decision making havent been integrated with the same speed. This research uses cloud computing capabilities for supporting analysis and decision making in water distribution systems. It includes the development of evolutionary algorithms ready to run in a cloud environment for searching the best possible decisions considering a set of objectives. The evaluation of solutions profits from the scalability of the cloud for making faster the solution search process. <s> BIB002 </s> Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> By leveraging and modifying ciphertext-policy attribute based encryption (CP-ABE) and OAuth, we propose a new authorization scheme, called fuzzy authorization , to facilitate an application registered with one cloud party to access data residing in another cloud party. The new proposed scheme enables the fuzziness of authorization to enhance the scalability and flexibility of file sharing by taking advantage of the one-to-one correspondence between linear secret-sharing scheme (LSSS) and generalized Reed Solomon (GRS) code. Furthermore, by conducting attribute distance checking and distance adjustment, operations like sending attribute sets and satisfying an access tree are eliminated. In addition, the automatic revocation is realized with update of $TimeSlot$ attribute when data owner modifies the data. The security of the fuzzy authorization is proved under the d-BDHE assumption. In order to measure and estimate the performance of our scheme, we have implemented the protocol flow of fuzzy authorization with OMNET $++$ $4.2.2$ and realized the cryptographic part with pairing-based cryptography (PBC) library. Experimental results show that fuzzy authorization can achieve fuzziness of authorization among heterogeneous clouds with security and efficiency. <s> BIB003 </s> Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> Multiple query optimization (MQO) in the cloud has become a promising research direction due to the popularity of cloud computing, which runs massive data analysis queries (jobs) routinely. These CPU/IO intensive analysis queries are complex and time-consuming but share common components. It is challenging to detect, share and reuse the common components among thousands of SQL-like queries. Previous solutions to MQO, heuristic or genetic based, are not appropriate for the large growing query set situation. In this paper, we develop a sharing system called LSShare using our proposed Lineage-Signature approach. By LSShare, we can efficiently solve the MQO problem in a recurring query set situation in the cloud. Our system has been prototyped in a distributed system built for massive data analysis based on Alibaba's cloud computing platform ( http://www.alibaba.com/ ). Experimental results on real data sets demonstrate the efficiency and effectiveness of the proposed approach. <s> BIB004 </s> Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> Introducing and implementing the Expert Cloud to find, share, exploit, manage and employ the HR.Presenting EaaS as a new service in Cloud computing.Virtualizing the HR as well as sharing his/her skill, knowledge and experiences. Human resources (HRs) as the most important asset of any organizations play a significant role in their success; but, HR virtualization and sharing her/his knowledge and skills was not studied in detail. In this paper, we present a new framework named Expert Cloud to enable the Cloud users for requesting the human expertise and skills without any knowledge of their location and to share the skill, knowledge and experiences of HRs. Also, we analyze, design and implement the Expert Cloud employing Internet infrastructures and Cloud computing concepts. The results show that the Expert Cloud improves the HR utilization, decreases customer response time and task completion time in order to achieve high level of customers' satisfaction and better performance of HR in organization. We conclude the paper with some suggestions for future researches and practices. <s> BIB005 </s> Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> Server Consolidation is one of the foremost concerns associated with the effective management of a Cloud Data Center as it has the potential to accomplish significant reduction in the overall cost and energy consumption. Most of the existing works on Server Consolidation have focused only on reducing the number of active physical servers (PMs) using Virtual Machine (VM) Live Migration. But, along with reducing the number of active PMs, if a consolidation approach reduces residual resource fragmentation, the residual resources can be efficiently used for new VM allocations, or VM reallocations, and some future migrations can also be reduced. None of the existing works have explicitly focused on reducing residual resource fragmentation along with reducing the number of active PMs to the best of our knowledge. We propose RFAware Server Consolidation, a heuristics based server consolidation approach which performs residual resource defragmentation along with reducing the number of active PMs in cloud data centers. We model residual resource fragmentation in cloud data centers.We examine feasibility of residual resource defragmentation with server consolidation.Proposed approach performs defragmentation with low energy cost and SLA violations.Controlled defragmentation with consolidation reduces VM migrations.A good mix of cloud applications ensures better defragmentation. <s> BIB006 </s> Emphasis on Cloud Optimization and Security Gaps: A Literature Review <s> S i n g h, J u n e j a and M a l h o t r a [19] <s> CSSICA is proposed to find the lowest service time for cloud composite services.PROCLUS is used to divide service providers into 3 categories based on service time.Selection probability of categories is calculated using their average service time.Utilizing achieved categories CSSICA has been able to make more conscious selections. Aiming to provide satisfying and value-added cloud composite services, suppliers put great effort into providing a large number of service providers. This goal, achieved by providing the "best" solutions, will not be guaranteed unless an efficient composite service composer is employed to choose an optimal set of required unique services (with respect to user-defined values for quality of service parameters) from the large number of provided services in the pool. Facing a wide service pool, user constraints, and a large number of required unique services in each request, the composer must solve an NP-hard problem. In this paper, CSSICA is proposed to make advances toward the lowest possible service time of composite service; in this approach, the PROCLUS classifier is used to divide cloud service providers into three categories based on total service time and assign a probability to each provider. An improved imperialist competitive algorithm is then employed to select more suitable service providers for the required unique services. Using a large real dataset, experimental and statistical studies are conducted to demonstrate that the use of clustering improved the results compared to other investigated approaches; thus, CSSICA should be considered by the composer as an efficient and scalable approach. <s> BIB007
 -M a m u n et al.  Speech-signal processing A r a n g o a et al. BIB002 Decision-making system Huo et al.  Facing large number of cloud application service S u g u n a and S u h a s i n i  Cloud efficient disaster recovery N a v i m i p o u r et al. BIB005 Hr visualization and sharing data Z h u and G o n g BIB003 Scalability & Flexibility of file sharing P a l m i e r i et al.  Re-optimization problem R a o and T h i l a g a m BIB006 Residual resource fragmentation and number of active physical servers reduction J u l a, O t h m a n, and S u n d a r a r a j a n BIB007 Service time optimization G e et al. BIB004 Multiple query optimization problem C h a n d r a s e k a r a n, M u r a l i d h a r and D i x i t BIB001 Feasibility of using cloud computing Y i l d i r i m, K i m b and K o s a r  Cloud optimization service