Dynamic CPU management for real-time, middleware-based systems

technical reportMany real-world distributed, real-time, embedded (DRE) systems, such as multi-agent military applications, are built using commercially available operating systems, middleware, and collections of pre-existing software. The complexity of these systems makes it difficult to ensure that they maintain high quality of service (QoS). At design time, the challenge is to introduce coordinated QoS controls into multiple software elements in a non-invasive manner. At run time, the system must adapt dynamically to maintain high QoS in the face of both expected events, such as application mode changes, and unexpected events, such as resource demands from other applications. In this paper we describe the design and implementation of a CPU Broker for these types of DRE systems. The CPU Broker mediates between multiple real-time tasks and the facilities of a real-time operating system: using feedback and other inputs, it adjusts allocations over time to ensure that high application-level QoS is maintained. The broker connects to its monitored tasks in a non-invasive manner, is based on and integrated with industry-standard middleware, and implements an open architecture for new CPU management policies. Moreover, these features allow the broker to be easily combined with other QoS mechanisms and policies, as part of an overall end-to-end QoS management system. We describe our experience in applying the CPU Broker to a simulated DRE military system. Our results show that the broker connects to the system transparently and allows it to function in the face of run-time CPU resource contention

Dynamic CPU management for real-time, middleware-based systems

Journal ArticleMany real-world distributed, real-time, embedded (DRE) systems, such as multi-agent military applications, are built using commercially available operating systems, middleware, and collections of pre-existing software. The complexity of these systems makes it difficult to ensure that they maintain high quality of service (QOS). At design time, the challenge is to introduce coordinated QOS controls into multiple software elements in a non-invasive manner. At run time, the system must adapt dynamically to maintain high QOS in the face of both expected events, such as application mode changes, and unexpected events, such as resource demands from other applications. In this paper we describe the design and implementation of a CPU Broker for these types of DRE systems. The CPU Broker mediates between multiple real-time tasks and the facilities of a real-time operating system: using feedback and other inputs, it adjusts allocations over time to ensure that high application-level QOS is maintained. The broker connects to its monitored tasks in a non-invasive manner, is based on and integrated with industry-standard middleware, and implements an open architecture for new CPU management policies. Moreover, these features allow the broker to be easily combined with other QOS mechanisms and policies, as part of an overall end-to-end QOS management system. We describe our experience in applying the CPU Broker to a simulated DRE military system. Our results show that the broker connects to the system transparently and allows it to function in the face of run-time CPU resource contention

Architecture Supporting Computational Trust Formation

Trust is a concept that has been used in computing to support better decision making. For example, trust can be used in access control. Trust can also be used to support service selection. Although certain elements of trust such as reputation has gained widespread acceptance, a general model of trust has so far not seen widespread usage. This is due to the challenges of implementing a general trust model. In this thesis, a middleware based approach is proposed to address the implementation challenges. The thesis proposes a general trust model known as computational trust. Computational trust is based on research in social psychology. An individual’s computational trust is formed with the support of the proposed computational trust architecture. The architecture consists of a middleware and middleware clients. The middleware can be viewed as a representation of the individual that shares its knowledge with all the middleware clients. Each application uses its own middleware client to form computational trust for its decision making needs. Computational trust formation can be adapted to changing circumstances. The thesis also proposed algorithms for computational trust formation. Experiments, evaluations and scenarios are also presented to demonstrate the feasibility of the middleware based approach to computational trust formation

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels. Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load. To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions. The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments. The proposed InterCloud environment supports scaling of applications across multiple vendor clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape

Egocentric Context-Aware Programming in Ad Hoc Mobile Environments

Some of the most dynamic systems being built today consist of physically mobile hosts and logically mobile agents. Such systems exhibit frequent configuration changes and a great deal of resource variability. Applications executing under these circumstances need to react continuously and rapidly to changes in operating conditions and must adapt their behavior accordingly. The development of such applications demands a reexamination of the very notion of context and of the mechanisms used to manage the application response to contextual changes. This paper introduces EgoSpaces, a coordination model and middleware for ad hoc mobile environments. EgoSpaces focuses on the needs of application development in ad hoc environments by proposing an agent-centered notion of context, called a view, whose scope extends beyond the local host to data and resources associated with hosts and agents within an entire subnet surrounding the agent of interest. An agent may operate over multiple views whose definitions may change over time. An agent uses declarative specifications to constrain the contents of each view by employing a rich set of constraints that take into consideration properties of the individual data items, of the agents that own them, the hosts on which the agents reside, and of the physical and logical topology of the ad hoc network. This paper formalizes the concept of view, explores the notion of programming against views, and discusses possible implementation strategies for transparent context maintenance. We include examples to illustrates the expressive power of the view abstraction and to related it to other research on coordination models and middleware

Semantic-based policy engineering for autonomic systems

This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

Combining Mobile Agents and Process-based Coordination to Achieve Software Adaptation

We have developed a model and a platform for end-to-end run-time monitoring, behavior and performance analysis, and consequent dynamic adaptation of distributed applications. This paper concentrates on how we coordinate and actuate the potentially multi-part adaptation, operating externally to the target systems, that is, without requiring any a priori built-in adaptation facilities on the part of said target systems. The actual changes are performed on the fly onto the target by communities of mobile software agents, coordinated by a decentralized process engine. These changes can be coarse-grained, such as replacing entire components or rearranging the connections among components, or fine-grained, such as changing the operational parameters, internal state and functioning logic of individual components. We discuss our successful experience using our approach in dynamic adaptation of a large-scale commercial application, which requires both coarse and fine grained modifications

Model-based provisioning and management of adaptive distributed communication in mobile cooperative systems

Adaptation of communication is required to maintain the reliable connection and to ensure the minimum quality in collaborative activities. Within the framework of wireless environment, how can host entities be handled in the event of a sudden unexpected change in communication and reliable sources? This challenging issue is addressed in the context of Emergency rescue system carried out by mobile devices and robots during calamities or disaster. For this kind of scenario, this book proposes an adaptive middleware to support reconfigurable, reliable group communications. Here, the system structure has been viewed at two different states, a control center with high processing power and uninterrupted energy level is responsible for global task and entities like autonomous robots and firemen owning smart devices act locally in the mission. Adaptation at control center is handled by semantic modeling whereas at local entities, it is managed by a software module called communication agent (CA). Modeling follows the well-known SWRL instructions which establish the degree of importance of each communication link or component. Providing generic and scalable solutions for automated self-configuration is driven by rule-based reconfiguration policies. To perform dynamically in changing environment, a trigger mechanism should force this model to take an adaptive action in order to accomplish a certain task, for example, the group chosen in the beginning of a mission need not be the same one during the whole mission. Local entity adaptive mechanisms are handled by CA that manages internal service APIs to configure, set up, and monitors communication services and manages the internal resources to satisfy telecom service requirements