M Tech Dissertations
Permanent URI for this collectionhttp://ir.daiict.ac.in/handle/123456789/3
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Item Open Access SQL-GQL inter-query translation for Google App engine datastore(Dhirubhai Ambani Institute of Information and Communication Technology, 2012) Kotecha, Shyam; Bhise, MinalOn demand services, usage based pricing, and scalability features of cloud computing has attracted many customers to move their applications into cloud. But different cloud service providers are using different standards & frameworks to host applications & data. Customers have to follow these standards and frameworks. When customer wants to migrate application and/or data to another cloud service provider, application code and database structure must be modified according to the standard of new cloud service provider. This modification is very costly and as a consequence, changing cloud service provider becomes difficult. This situation is called vendor lock-in in cloud. Focusing on database, complete database migration requires migration of data, database schema, and query. This thesis work concentrates on migration of query. Automation in migration process is achieved by translation algorithms. This thesis work introduces inter-query translation algorithms. These algorithms translate SQL (Structured Query Language) query and GQL (Google Query Language) query into each other. The implementation of these algorithms is demonstrated for MySQL Sakila databaseItem Open Access Policy based resource allocation on infrastructure as a service cloud(Dhirubhai Ambani Institute of Information and Communication Technology, 2011) Vora, Dhairya; Chaudhary, Sanjay; Bise, MinalCloud computing refers to the provision of computational resources on demand. Resource allocation is an important aspect in cloud computing. Cloud user asks for resources in terms of a lease. Lease stores the information about required resources and the time at which these resources are required. Cloud provider accepts the lease if it can provide guarantee for assigning resources at asked time to the cloud user. Better scheduling algorithm can accept more number of leases and hence give better resource utilization. Cloud provides four types of leases: immediate, advance reservation, best effort and deadline sensitive. Immediate allocation policy accepts the lease if resources are available, else it rejects the lease. Advance reservation policy accepts the lease if resources are available at the asked time, else it rejects the lease. Best effort allocation policy accepts the lease as soon as the resources are available. Deadline sensitive leases have parameters like required resources, startTime, endTime and duration. Scheduler can accept such lease by providing required resources for the asked duration of time between given startTime and endTime. Haizea is a resource lease manager which handles the scheduling of the lease. Proposed algorithm extends the current scheduling algorithm of Haizea for deadline sensitive type of leases. Aim of the thesis is to improve resource utilization by extending the current scheduling algorithms of Haizea. Proposed scheduling algorithm accepts more number of leases by dividing a deadline sensitive lease into multiple slots and by back filling already.Item Open Access Migration of database from one cloud to other clouds(Dhirubhai Ambani Institute of Information and Communication Technology, 2011) Bhatt, Shreyansh; Chaudhary, SanjayOn demand services and scalability features of cloud computing has attracted many customers to move their applications into cloud. Cloud service providers are following di erent standards to host applications and data. Data must be stored according the schema of a particular cloud service provider. A need can arise to migrate cloud application and/or data to another cloud service provider. In that case, the relevant code, and structure of database must be modi ed based on newly identi ed cloud service provider. Which is a costly deal and as a consequence, chang ing cloud service provider becomes di cult. This issue is regarded as vendor lock-in in terms of cloud computing. Current study will help to identify issues of migrating database between two clouds and development of novel techniques, which would facilitate this migration. For this, RDF /RDFS (Resource Description Framework/Resource Description Framework Schema) is used as an intermediate model. Automation in migration process is achieved by transformation algorithms. Bigtable, Google App Engine datastore, is taken as a cloud datastore and algorithms are developed and implemented to convert RDF/RDFS data into data that can be stored in Bigtable and vice versa. Results are shown for the same. Subsequently, the same algorithm is generalized to store RDF/RDFS data into any cloud datastore.Item Open Access Resource allocation on infrastructure as a service cloud using policies(Dhirubhai Ambani Institute of Information and Communication Technology, 2010) Nathani, Amit; Divakaran, SrikrishnanConventionally, a cloud refers to an Infrastructure as a service cloud. Infrastructure as a service cloud providers manage a large set of computing resources. These resources can be provided to cloud users on demand in the form of virtual machines. Cloud consumers do not need to manage resources and be worried about the performance issues because they are handled by cloud providers. Resource allocation in the context of infrastructure as a service cloud means allocating virtual resources namely computing capacity, storage etc. to competing requests based on pre-defined resource allocation policies. In real world most of the Infrastructure as a service clouds rely on simple resource allocation policies like immediate and best effort. Immediate means the resources are allocated if they are available or the request is rejected and best effort means the requested resources are allocated if they are available or the request is placed in first come first serve queue. Sometimes it is not possible for a cloud provider to satisfy all the requests which come to them immediately because of lack of resources. In this case cloud providers can benefit from more complex resource allocation policies. Haizea is a resource lease manager that tries to address above issues. It uses resource leases as resource allocation abstraction and implements these leases as virtual machines. Currently, it supports four kinds of resource allocation policies: immediate, best-effort, advance reservation and deadline sensitive. The aim of thesis is to extend the current scheduling algorithm of Haizea to support deadline leases in an efficient manner. A dynamic planning based scheduling algorithm is proposed which will admit new leases and prepare the schedule whenever a new lease can be accommodated. The proposed algorithm is implemented in Haizea. Experiments are performed to demonstrate the effectiveness of it. The results show that it maximizes resource utilization and acceptance of leases compared to the existing algorithm of Haizea.Item Open Access Negotiation for resource allocation on infrastructure as a service cloud(Dhirubhai Ambani Institute of Information and Communication Technology, 2010) Akhani, Janki; Divakaran, SrikrishnanThe Cloud is a computing platform that provides dynamic resource pools, virtualization, and high availability. Cloud computing infrastructures can allow enterprises to achieve more efficient use of their IT hardware and software investments. Infrastructure As A Service (IAAS) cloud providers manage a large set of computing resources. These resources can be provided to cloud consumers on demand in the form of virtual machines. Cloud consumers do not need to manage resources and be worried about the performance issues because they are handled by cloud providers. Open Nebula is an open source cloud toolkit which can be used to setup an IAAS cloud. It has three components: Open Nebula Core, Virtual Machine Scheduler and Cloud Drivers. Haizea is an open-source resource lease manager, and can act as a virtual machine scheduler for Open Nebula or used on its own as a simulator to evaluate the performance of different scheduling strategies. Haizea supports four kinds of resource allocation policies: immediate, best-effort, advance reservation and deadline sensitive. To reserve resources in advance using Haizea, consumer submits parameters like amount of resources, start time and duration of a reservation as a request. If one or more parameters can not be satisfied, then Haizea will reject the request. This method is very rigid method because it does not allow negotiation of any parameter. Consumer can resubmit new requests by modifying previously submitted request parameters. Consumer will not be aware of the current resource allocation on provider side so, the chances of new requests getting rejected are more. Thus, it will increase communication overhead between cloud provider and consumer as well as it will decrease resource utilization on provider’s side. It will also degrade the performance of a provider in managing many incoming requests due to previously rejected ones. To overcome the above problems, negotiation can be provided. Negotiation process consists of three components which are negotiation protocol, negotiation objectives and agents’ decision making algorithm. The proposed algorithm to generate set of counter offers is a part of decision making model at provider side. It provides set of counter offers to consumer when his advance reservation request gets rejected. It provides set of counter offers considering parameters’ flexibilities to maximize the chances of their acceptance. The proposed algorithm for User selection policy is a part of decision making model at consumer side. Consumer can get best suitable offer from set of counter offers using the algorithm of user selection policy. Ranking algorithm is a partof algorithm for user selection policy. Using this ranking algorithm, consumers will get suitable offers sorted according to their needs. It will reduce consumers’ efforts to go through all the provided counter offers and choose best suitable one. These algorithms are implemented in Haizea. Experiments are performed to demonstrate the effectiveness of algorithms. The results show that the proposed algorithm to generate counter offers maximizes resource utilization and acceptance of requests compared to rigid and exact methods.Item Open Access Bidirectional service composition(Dhirubhai Ambani Institute of Information and Communication Technology, 2010) Khakhkhar, Sandip; Chaudhary, SanjayService is a network addressable software component to perform a specific task. A service consumes given input parameters, performs specific task based on input parameters and returns the result in terms of output parameters. A service request specifies required task in terms of input parameters that can be provided and output parameters that are required. A service discovery mechanism can be used to find services that can be executed to satisfy service request. Service and service request is match by comparing their input/output parameters. A service request may be complex enough that it can not be satisfied by an individual service. It might be possible to execute a chain of services in a particular order to satisfy service request. This chain of services is referred as composition plan and service offered by executing this composition plan is referred as composite service. The aim of service composition algorithm is to generate a composition plan and generate composite service to satisfy service request. Services involved in composition plan are selected manually while designing composite service in static composition process. This process consumes considerable amount of time and effort. It is also vulnerable to changes in input/output of services. A dynamic composition algorithm is required that can automatically select services involved in composite plan and generate a composite service on-the-fly. Main issue with dynamic composition algorithms is composition time taken by algorithm to generate a composite service. Composition time indicates duration of the time at which the service request was submitted to the algorithm till the algorithm generate a composite service that can satisfy service request. Composition time depends upon the number of services required to explore in order to find services that can take part in composite plan. Dynamic composition algorithms presented in previous work mainly follows either forward chaining approach or backward chaining approach to find a composite service. Performance of algorithms based on forward chaining approach or backward chaining approach suffers for certain cases to generate a composite service where number of services explored increases exponentially as number of iterations increases. This work proposes a dynamic composition algorithm that gives consistent performance across all the cases. Proposed algorithm approaches from two directions alternatively, one follows forward chaining approach and other follows backward chaining approach. Composition algorithm following only forward chaining approach or backward chaining approach performs all the iterations in one direction only where as proposed algorithm requires only half number of iterations in both directions. Algorithm uses two types of matching strategy to compare input/output parameters. First one is based on keyword matching and second one based on semantic matching strategy. Performance of proposed algorithm is evaluated by performing relevant experiments and results are compared with algorithms based on only forward chaining approach or backward chaining approach. Proposed algorithm explores less number of services and takes less composition time compared to algorithms based on only forward chaining approach or backward chaining approach.Item Open Access Scheduling and isolation in virtualization(Dhirubhai Ambani Institute of Information and Communication Technology, 2009) Somani, Gaurav; Chaudhary, SanjayVirtual machine (VM) based server implementation is popular for numerous advantages like fault isolation, efficient hardware utilization, security and ease of management. Virtual machine monitor (VMM) like Xen is a popular virtualization software to manage virtual machines by scheduling them to use resources such as CPU, memory and network. Performance isolation is desirable in virtual machine based infrastructures to meet Service Level Objectives (SLO). In performance isolation, no virtual machine should affect performance of other co hosted virtual machine, which shares the same hardware. Virtual machine schedulers are the key operators in allocating resources among virtual machines. This requires special attention towards scheduling as fairness and resource isolation are the key requirements for which any user virtualizes servers. I/O models are the main bottlenecks in sharing resources among virtual machines. To evaluate isolation property, we need to analyze resource sharing and utilization among virtual machines.The thesis aims to evaluate the performance isolation achieved by Xen in different scheduler configurations. Experiments are performed using different resource intensive applications to get an insight into isolation. These tests include CPU, Network and Disk I/O intensive benchmarks. Considering the equal importance of I/O applications in virtualized environment, tests for interactive applications in conjunction with CPU intensive applications are also performed. Experiment results show that Isolation is critical when we run I/O application in conjunction with CPU intensive applications. But effective parameter and scheduler configuration can lead towards better isolation as well as utilization. Global balancing of load across all the available physical processors in a physical machine is important characteristic of a scheduler. Xen’s Credit scheduler aims to achieve global load balancing on multiprocessor systems. Xen’s Simple Earliest Deadline First (SEDF) scheduler can not be used in production environment due to unavailability of this important feature of load balancing. Many applications requires scheduler like SEDF in their implementation to fulfill the requirement of interactive applications. This thesis investigates requirements of this feature and discusses algorithmic design and implementation of a developed user space load balancing program. Experiments show a balance among number of physical processors with better utilization of
Item Open Access Web services policy in grid(Dhirubhai Ambani Institute of Information and Communication Technology, 2008) Desai, Amee Anilbhai; Chaudhary, SanjayService-oriented computing enables service providers to publish their business functionalities in the form of abstract contracts, which can be discovered by service consumers based on open and standard protocols. Enterprise may be running a number of multiple business processes in parallel, which may require different services to fulfil the functionality. There are number of factors that both service provider and service consumer should consider before they interact with each other. Web services standards are used for acquiring interoperability among services for large scale adoption of architecture. In Web service selection phase without the use of policy, a service consumer selects the Web service which matches the functional requirements. For satisfying non-functional requirements of a service consumer, policy is used in Web service selection phase. This thesis proposes an approach and architecture to select Web services based on WS-Policy in grid. Service selection depends on metadata and policy. There is a need for dynamic selection services based on runtime environment such as content (semantics), and contract (policy). This thesis proposes an approach and architecture for dynamic selection of services based on policy and semantic .To provide better search, query, composition, and management, there is a need for mechanism to group these services based on the requirements of clients and business processes. This thesis proposes context and location based approach for service grouping and group notification. Context and location provide powerful mechanism for the better search, query, grouping and group notification to the services, and it allows customization based on user preferences, role, and location to improve personalization. The thesis proposes context and location driven grid business process to aggregate information from multiple sources according to the preferences of clients. A policy based service grouping approach is used to aggregate services. For achieving location driven approach, this thesis develops virtual organization and for specifying preferences in virtual organization, a policy is used.