During the past few years, enterprises have been increasingly aggressive in moving mission-critical and performance-sensitive applications to the cloud, while at the same time many new mobile, social, and analytics applications are directly developed and operated on cloud computing platforms. These two movements are encouraging the shift of the value proposition of cloud computing from cost reduction to simultaneous agility and optimization. These requirements (agility and optimization) are driving the recent disruptive trend of software defined computing, for which the entire computing infrastructureVcompute, storage and networkVis becoming software defined and dynamically programmable. The key elements within software defined environments include capability-based resource abstraction, goal-based and policy-based workload definition, and outcome-based continuous mapping of the workload to the available resources. Furthermore, software defined environments provide the tooling and capabilities to compose workloads from existing components that are then continuously and autonomously mapped onto the underlying programmable infrastructure. These elements enable software defined environments to achieve agility, efficiency, and continuous outcome-optimized provisioning and management, plus continuous assurance for resiliency and security. This paper provides an overview and introduction to the key elements and challenges of software defined environments. focuses on identifying better outcomes within a cloud environment with respect to the value of the service, the cost of the required resources, and the risk of failure in an unpredictable environment and under constant usage changes. This requires a high degree of automation and programmability of the infrastructure itself. Hence, this shift led to the recent disruptive trend of software defined computing for which the entire system infrastructureVcompute, storage and networkVis becoming software defined and dynamically programmable. Software defined computing receives considerable focus across academia and enterprises [1-7]. Software defined computing originated from the compute environment in which the computing resources are virtualized and managed as virtual machines [8-11]. This enabled mobility and higher resource utilization as several virtual machines are collocated on the same server,

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Heap is an important shared resource in Java virtual machine. A problem with memory management in one component can affect the whole system and even result in crashing the virtual machine. In this paper, we propose an partition-based approach to manage heap in an application server. In our approach, the shared heap is divided into logical partitions, in which instances of application components and server components are allocated separately.

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Preface: Software defined environmentsThe significant growth and diversity in information-processing applications and domains require a rethinking of how IT is to be delivered as solutions and services, meeting a variety of requirements that include performance, resilience, security, and agility. Cloud-computing platforms are becoming one of the preferred deployment platforms for both traditional applications and a new generation of mobile, social, and analytics applications. Changes are evident at all layers of the platform stack. At the infrastructure level, the network, compute, and storage are becoming more software