Automated Virtual Cloud Management: The need of future Prof. (Ms) Manisha Shinde-Pawar Faculty of Management (Information Technology), Bharati Vidyapeeth Univerisity, Pune, IMRDA, SANGLI Abstract: With a sound commercialization and standardization concern, Cloud computing providers are offering their services to cloud clients using networked cloud devices, who are relying for all different needs on cloud. To provide these services reliably and to maintain all different numerous collection of clouds in cloud computing, it needs to apply runtime management along with strategic technical tools to track and regulate the cloud computing system. To reach from a haphazard system to more effective, planned, organized system that is in real-time communication cloud need to be planned, adjusted and restructured with entire dynamic behavior as virtual system to optimize resources requirement and to efficiently maximize utilization of the available resources. The researcher can explore that by applying Object Oriented data structure approach to this collection of clouds, the cloud by treating as object which will have and cloud identifier as attribute. Such objects can help to handle runtime behavior and performance of the cloud with more efficient way using OO concepts and generic linked data structures to cloud computing. recognized service categories of a telecommunicationcentric cloud ecosystem. Keywords: Cloud Computing, Object Oriented concept, s, Virtual System. Figure No.1 File: http://en.wikipedia.org/wiki/file:cloud_computing_layers.png 1. INTRODUCTION 1.1 Cloud Computing: Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over a network (typically the Internet). The name comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts remote services with a user's data, software and computation. Cloud computing exhibits agility, API accessibility, reduced cost, device and location independence, virtualization, multitenancy, reliability, scalability and elasticity via dynamic provisioning, performance. Service models: These services are provided according to three fundamental models: infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) where IaaS is the most basic and each higher model abstracts from the details of the lower models. In 2012 network as a service (NaaS) and communication as a service (CaaS) were officially included by ITU (International Telecommunication Union) as part of the basic cloud computing models, 1.2 Cloud Management: A "cloud" is a set of machines and web services that implement cloud computing. The resources are drawn from a "cloud" of resources when they are granted to a user and returned to the cloud when they are released. Cloud types (including public, private, and hybrid) refers to the nature of access and control with respect to use and provisioning of virtual and physical resources. Cloud management means the software and technologies designed for operating and monitoring applications, data and services residing in the cloud. Cloud management tools help ensures a company's cloud computing-based resources are working optimally and properly interacting with users and other services. 1.3 A data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Data structures provide a means to manage large amounts of data efficiently, such as large databases and internet indexing services. Usually, efficient data structures are a key to designing efficient algorithms. The implementation of a data structure usually requires writing a set of procedures that create and manipulate Volume 2, Issue 3 May June 2013 Page 9
instances of that structure. The efficiency of a data structure cannot be analyzed separately from those operations. This observation motivates the theoretical concept of an abstract data type, a data structure that is defined indirectly by the operations that may be performed on it, and the mathematical properties of those operations (including their space and time cost). 1.3 Object Orientation: Object Orientation approach represents object defines its internal structure and properties along with its behavior or functionality to perform. Object can maintain its state of transition and so is always typically applied to real world business objects. Objects once defined, can create new instance with constructor and also can be released or destroyed by using destructor. Instructions are divided into objects Functions that operate on data of an object are together in data structure. Data is hidden and cannot be accessed by external functions. (Data Security). Objects may communicate with each other through functions. New data can be easily added to functions It follows bottom up approach in program designing. 1.4 OOP Concepts: Polymorphism-more than one form using a uniform interface Inheritance- Encapsulation-bundling of data with the methods with restricting access Abstraction-reduces complexity by hiding irrelevant details Classes-user defined data type which specifies a data structure for the object Objects-particular items belong to the class. Instance Method Message Passing 2. Methodology: The essential requirement of cloud management is to provide ways to dynamically allocate portions/services/resources of clouds to programs at their request, and freeing it for reuse when no longer needed. This is critical to the computer system. It uses different methods/api/software to do so, which can be improved for its effectiveness by applying standard methods with generic linked s. Compared to arrays, linked data structures allow more flexibility in organizing the data and in allocating space for it. In arrays, the size of the array must be specified precisely at the beginning, this can be a potential waste of memory. A linked data structure is built dynamically and never needs to be bigger than the programmer requires. It also requires no guessing in terms of how much space you must allocate when using a linked data structure. This is a feature in saving wasted memory. By using protocol, a connection must first be established between the instance of client and instance of cloud object. Cloud object will listen to request for connection to have utilization account on cloud from client. By applying thread life cycle such requesting client sessions along with their current state will be handled to efficiently use cloud resources and to avoid idle cloud time. Virtual systems separate the cloud product/service Id used by a usage from actual physical resources, allowing separation of resources and their Identification number and increasing the effectively available amount of resource using dynamic allocation, separation and utilization of resources. Virtual System will help to identify state of cloud and active connections so as to provide services and resources to active state requests. At the same time such virtual system will efficiently keep the other inactive and blocked cloud requests to improve performance of system in integration of loosely coupled real time systems. The quality of the virtual cloud manager can have an extensive effect on overall system performance. Furthermore, algorithmic applications of such real time data structure can improve the virtual management to support policy based strategic management of clouds by automated systems. Fragmentation and swapping, congestion control mechanisms can be focused to set the strategies for smoothen the criticality of network based connection request and response. Independent of physical resources organization, integration, sharing or protection virtual system will perform based on virtual identifiers and virtual processes. In this way virtual manager will have control over access, sharing, and for other usage of resources. As shown in above Figure No. 1, the virtual Object Space For cloud A and Cloud B virtual identifiers. This identifier will be logical group of collection of bits representing (pointing) to scattered physical resources which needed to be included to or excluded from cloud system scope. Such structure can implement algorithmic complexity to provide required functionality. The Figure No.2 illustrates that physical organization may be any combination referring to hardware, services and required objects, but logically it will be a unique virtual space component identified and referred by the unique identifier. Volume 2, Issue 3 May June 2013 Page 10
2.1 Cloud Map table: functionality and similarity and difference establishes in virtual environment. Access modifiers and inheritance mechanism behavior for such dynamically designed packages can help to improve connection response and quality of services. As a package implementation deployment becomes easy and with fewer part of transaction can minimize load on resources. 2.2.5) Resource Management Virtual modification for combination allows changing the definition of data structure any time, if any resource fails or need to allocate or need make free or resource plan changes due to any reason, such changes can be easily adapted by virtual object space table to change the identifier pointers. Figure No.2 2.2 Such Virtual System can be designed to provide: 2.2.1) Automatic Cloud Allocation: When Client request comes (enters to cloud) and leaves the scope of connection in cloud computing system cloud instance gets created and allocated automatically and then also de-allocated while leaving connection. By sing stack or linked data structure it can be initiated as unique cloud identifier and then updated every time automatically. 2.2.2) Dynamic linked data structure and Priority Ranking and Scheduling Policies Getting/ setting, inserting and removing or updating middle cloud identifiers becomes easy as dynamically connection is added or released without reallocation or reorganization of the entire structure. Automated Virtual Cloud Management System also can aim to prioritize ranks of request and process transactions; this can be used to decide scheduling policies of tasks. 2.2.3) Resource Pool As those implementations suffer from fragmentation because of variable need based sizes, it can be impossible to use them in a real time system due to performance. A more effici ent solution is pre-allocating a number of cloud resource blocks with the same size called the resource pool. The application can allocate, access, and free cloud represented by handles at run time. 2.2.4) Logical Packaging, Connection and Deployment Object Oriented package which allows to group, organize and store similar kind of classes in form of JAR files, can be restructured and reorganized as 2.2.6) Improved efficiency of cloud stack API compatibility, VM Network, Usage Metering, Load Balancing, Virtual routers all these are parameters based on which cloud performance efficiency is dependent. In automated system change in configuration and availability and functionality of these parameters can be treated as state of object and can be communicated to other parameters, so intelligent strategy shifting can be implemented to achieve required functionality. Ultimately Automated Virtual Cloud Management System will improve the efficiency and reliability of cloud stack. 2.2.7) Demand based Dynamic Decomposition and Integration As client request of processing demands resources and services can be integrated, if they are separate and if grouped functionality is required cloud structure and scope will be reshaped. As well as if request demands for transaction based on separation concern then such decomposition can be achieved on demand due to virtual object space table physical organizing on reorganizing can be achieved easily. 2.2.8) Runtime Middleware Configuration- Knowledge Management, Data and services Integration, Modeling and Repository configuration is focused with dynamic changes to preserve consistency, integrity and to avoid redundancy in repository. 2.2.9) Hiding Physical Fragmentation- Different Components may be inter-related and fragmented to achieve organized functionality but as logical identifier will be used for cloud components for set of different physical segments, it will hide the physical fragmentation from client requests. 2.2.10) Wizard based corporate cloud business: Volume 2, Issue 3 May June 2013 Page 11
By providing automated system, corporate world can find investment opportunities in such cloud management services and then IT enabled wizard based corporate cloud products, services and infrastructure can be next generation of cloud computing. 2.3 Cloud Objects and Cloud Stack: perfect hash function also can be applied and if need of changing runtime, it can serve with collision resolution strategies of separate chaining method. Incremental resizing can be best option to provide dynamic relevance by resizing gradually to ensure new entries with low price. 2.5 Interaction with cloud architecture: Cloud Object: Cloud methods: CL_A CL_B CL_C CL_D CL_E Figure No.3 Cloud Stack provides infrastructure clouds using web services API, which can be enhanced to level of wizard for corporate providers to manage their services or automated control through handles of virtual cloud objects. Server and Machines deployment, maintenance, configuration, storage tasks are basic requirements for infrastructure clouds. Cloud Objects and Cloud stacks can be level of abstraction for all integrated infrastructures. Cloud B CL_B Cloud A CL_A. Attributes. cloud () Cloud C CL_C Cloud D cloud () 2.4 Applying Hashing to Cloud : Cloud Unique ID hash Function Bucket Cloud E CL_A CL_ B 521-8769 523-6598 521-8889 521-8766 Figure No.5 Memory management, state management, runtime behavior, and data structures integration leads in Automated Virtual Cloud Management System. CL_C Figure No.4 523-9876 A basic requirement is that the function should provide a uniform distribution of hash values. The distribution needs to be uniform only for table sizes s that occurs in the application. In particular, if cloud is restructured, then it uses dynamic resizing with exact doubling and halving of s, the hash function needs to be uniform only when s is a power of two. On the other hand, some hashing algorithms provide uniform hashes only when s is a prime number. So to create hash function with no collisions New or derived classes from base classes can be instantiated as dynamic call request comes for specified services, specific specialized sub class can be instantiated, or else if request call demands to logically integrate two or more classes then it can be achieved through interface designing and implementation. Such relationship management and data structure are combined to strengthen the coupling and de-coupling mechanism to provide services, products and infrastructure over cloud. 3. Conclusion: In this paper, different strategies to manage and maintain computing technology applying object oriented data structure approach have addressed numerous challenges. In future research of cloud computing with different on demand needs cloud computing need to increase its scope Volume 2, Issue 3 May June 2013 Page 12
of services with different corporate providers, to provide value added services which may make it difficult to manage. The demand of cloud computing and cloud management the important future aspect will be to maintain data about data of clouds that is metadata, so Object Oriented data structure approach to metadata may be future research domain. Above methods discussed can help in real time reformation and restructuring of clouds as objects and manage it using automated virtual system and to get all advantages of Object Oriented data structure approach mainly to provide automated cloud control system to improve the efficiency of network. References: [1] Cloud Computing, http://en.wikipedia.org/wiki/cloud_computing [2] CloudStack, http://en.wikipedia.org/wiki/cloudstack [3], http://en.wikipedia.org/wiki/data_structure Note: All Internet links referred here are active as on March 23, 2013. AUTHOR Manisha Shinde received the B.Sc. in Computer Science degree in 2003 and MBA degree in Information of Technology and Management in 2008. She has joined BVDU, IMRDA, Sangli as Assistant Professor in Information Technology. Volume 2, Issue 3 May June 2013 Page 13