Suresh Chand Gupta

Probe mechanism for object-oriented software testing

This paper presents a probe-based testing technique that facilitates observing internal details of execution at different levels of abstraction-unit, integration and system levels, during testing of object-oriented software. Our technique adapts probe, an observability measure, to suit the testing needs of object-oriented software. It uses source-code instrumentation, which requires probes to be pre-determined and pre-built in the software during the development phase. Test coverage reports are generated from the information gathered by the executed probes. It includes coverage of probes at probe, method, class, inheritance, regression and dynamic binding levels. During regression testing, our technique helps in the selection of test cases that must be re-executed. Furthermore, the log generated by active probes can be used for post-analysis.

Controllability mechanism for object-oriented software testing

We present a controllability mechanism that facilitates creation of difficult-to-achieve states, for execution of state specific tests, during object-oriented software testing. Provisions are made in the software during the design phase and coded during the coding phase of software development. The mechanism requires creating the control environment and incorporating control commands in the software during software development. We illustrate the control mechanism using three examples, each requiring a unique control environment to attain the difficult-to-create states.

Comparing Infrastructure Monitoring with CloudStack Compute Services for Cloud Computing Systems

CloudStack is an open source IaaS cloud that provides compute, network and storage services to the users. Efficient management of available resources in the cloud is required in order to improve resource utilization and offer predictable performance to the customers. To facilitate providing of better quality of service, high availability and good performance; a comprehensive, reliable, centralized and accurate monitoring system is required. For this, the data needs to be collected from the components of CloudStack and analyzed in an efficient manner. In this paper, we present a detailed list of attributes required for monitoring the infrastructure associated with CloudStack. We identify the processes related with the compute services and its associated parameters that need to be monitored. We categorize the infrastructure monitoring, and list the parameters for monitoring parameters. Further, the proposed list is applied to three monitoring software that are commonly used for monitoring resources and processes associated with CloudStack. Developers and system administrators can benefit from this list while selecting the monitoring software for their system. The list is useful during the development of new monitoring software for CloudStack, as the functionality to be monitored can be selected from the list.

Cloud service orchestration based architecture of OpenStack Nova and Swift

OpenStack Nova and Swift are responsible for provisioning and management of compute and storage resources, respectively, in a need based manner. These cloud software are widely adopted by several popular organizations for deploying their compute and storage services. To have a cloud platform that is easily upgradable, modifiable and maintainable, there is a need for a well defined detailed architecture. For this, there is a need of identifying the internal components and processes required for the functioning of the software. In this paper, we present architecture of OpenStack Nova and Swift in conformance to layered architecture defined for service orchestration component of the NIST cloud computing reference architecture. The proposed architecture identifies the components, sub-components and their interaction, at the layers defined for service orchestration component and provides insight into internal working and associated processes of Nova and Swift. The proposed architecture is beneficial for cloud provider and system administrator in maintaining and improving quality of the system.

Monitoring List for Compute Infrastructure in Eucalyptus Cloud

Compute services in IaaS cloud perform the task of provisioning and managing virtual machines requested by the users. The ever increasing demand for compute services in cloud has led to an associated large scale infrastructure that is complex to manage. An efficient and fine-tuned monitoring mechanism is required to manage the large scale and complex compute infrastructure. Eucalyptus is an open source cloud platform that provides compute services to the users. This paper presents an infrastructure monitoring list for compute services in Eucalyptus that elicits the details of infrastructure to be monitored. The list is useful to the system administrator for selecting parameters that need to be monitored. Developers benefit from the list by selecting requirements from the list during the update and development of tools.

Monitoring Checklist for Ceph Object Storage Infrastructure

Object storage cloud is widely used to store unstructured data like photo, emails, video etc. generated from use of digital technologies. The number of object storage services has increased rapidly over the years and so is increased the complexity of the infrastructure behind it. Effective and efficient monitoring is constantly needed to properly operate and manage the complex object storage infrastructure. Ceph is an open source cloud storage platform that provides object storage as a service. Several works have discussed ways to collect the data for monitoring. However, there is little mention of what needs to be monitored. In this paper, we provide an infrastructure monitoring list for Ceph object storage cloud. We analyze the Ceph storage infrastructure and its processes for identifying the proposed lists. The infrastructure monitoring list allows selecting requirements, in contrast to, specifying fresh requirements, for monitoring. The monitoring list helps developer during requirement elicitation of the monitoring functionality when developing a new tool or updating an existing one. The checklist is also useful during monitoring activity for selecting parameters that need to be monitored by the system administrator.

CoSEL: Control-plane Only Scalable Efficient and Lightweight SDN Debugger

Network debugging has always been a challenging task primarily because the original design of the Internet architecture gave little importance to debugging and management. In addition, the Internet makes forwarding decisions in a distributed manner, which is hard to track. With the advent of Software Defined Networks (SDNs), network debugging has potentially become easier because solely the control plane makes forwarding decisions, which is often centrally located. In this paper, we propose Control-plane Only Scalable Efficient and Lightweight SDN Debugger (CoSEL), which is to the best of our knowledge the first control-plane only, network debugger for SDN. Unlike earlier proposed debuggers, which rely on information specially obtained from the data-plane or a combination of the data and control planes, CoSEL does not require the use of any additional network bandwidth for its operation and hence outperforms existing schemes in terms of scalability. In terms of completeness, however, CoSEL does not perform as well as some existing schemes, although this loss in completeness does not prevent it from capturing most of the bugs in the network, which have1 been observed to be caused mainly by the control plane. We implement CoSEL on the Floodlight controller as a network application and present results of CoSEL in action over a network emulated by mininet. However, CoSEL is controller independent and utilizes a common programming API provided by POX, NOX and OpenDaylight. In addition, the control plane debugging of CoSEL enables it to be an effective debugging tool for network applications that are built on top of controllers utilizing Northbound APIs and interacting with network by injecting rules.

Software Defined Storage Technology.

I. TUTORIAL OBJECTIVE The objective of the tutorial is to discuss the emerging concept of Software Defined Storage (SDS) with practical example. The overall objective of the tutorial: Participants can view a complete picture of storage–the traditional storage, storage in the cloud and the emerging Software Defined Storage. • Providers of storage hardware and software solutions can understand the software defined storage architecture which will help in designing and providing SDS based more cost effective systems. • Researchers can understand key concepts and challenges of software defined storage and contribute in evolving this technology further. • Educators can understand the emerging view of storage in the cloud. • Providers of cloud storage services will become aware of the emerging storage technology of the future for the data centres; which is more cost effective alternative to traditional storage systems.