The Experts below are selected from a list of 129597 Experts worldwide ranked by ideXlab platform
Patricia Morreale - One of the best experts on this subject based on the ideXlab platform.
-
end to end qos measurement analytic methodology of Application Response Time vs tunable latency in ip networks
Network Operations and Management Symposium, 2000Co-Authors: E S H Tseau, Patricia MorrealeAbstract:In this paper, we discuss one aspect of the measurement issue: how to measure end-to-end Application Response Time (ART) relative to aggregated "tunable" network latency, or tunable latency. The goal is to enhance our understanding of the relationship between these two metrics for database access Applications. Tunable latency is defined as follows: the sum of the "round trip" queuing delay and data transmission/insertion delay from beginning to end of the Application transmission. Our problem space concentrates on developing a methodology to graphically characterize Response Time as a function of tunable latency for existing database access Applications in a wired, single-threaded, multi-user, post-deployment client/server environment. A number of tools were used in developing this methodology which was not obvious from the tools' documentation. To test its feasibility before actual field use, we used an experimental setup to emulate the real user environment. In so doing, we now have two proposed methodologies: one for the experimental setup version (of the in-service scenario) and one for the "actual" in-service scenario. We present results obtained from the experimental method. The resulting graphs can be a consultation tool for network tuning and control, classification of user Applications by priority class-of-service, SLA negotiation and manual QoS provisioning.
Muhammad Shoaib - One of the best experts on this subject based on the ideXlab platform.
-
Bringing Computation Closer toward the User Network: Is Edge Computing the Solution?
IEEE Communications Magazine, 2017Co-Authors: Ejaz Ahmed, Arif Ahmed, Ibrar Yaqoob, Junaid Shuja, Abdullah Gani, Muhammad Imran, Muhammad ShoaibAbstract:The virtually unlimited available resources and wide range of services provided by the cloud have resulted in the emergence of new cloud-based Applications, such as smart grids, smart building control, and virtual reality. These developments, however, have also been accompanied by a problem for delay-sensitive Applications that have stringent delay requirements. The current cloud computing paradigm cannot realize the requirements of mobility support, location awareness, and low latency. Hence, to address the problem, an edge computing paradigm that aims to extend the cloud resources and services and enable them to be nearer the edge of an enterprise's network has been introduced. In this article, we highlight the significance of edge computing by providing real-life scenarios that have strict constraint requirements on Application Response Time. From the previous literature, we devise a taxonomy to classify the current research efforts in the domain of edge computing. We also discuss the key requirements that enable edge computing. Finally, current challenges in realizing the vision of edge computing are discussed.
E S H Tseau - One of the best experts on this subject based on the ideXlab platform.
-
end to end qos measurement analytic methodology of Application Response Time vs tunable latency in ip networks
Network Operations and Management Symposium, 2000Co-Authors: E S H Tseau, Patricia MorrealeAbstract:In this paper, we discuss one aspect of the measurement issue: how to measure end-to-end Application Response Time (ART) relative to aggregated "tunable" network latency, or tunable latency. The goal is to enhance our understanding of the relationship between these two metrics for database access Applications. Tunable latency is defined as follows: the sum of the "round trip" queuing delay and data transmission/insertion delay from beginning to end of the Application transmission. Our problem space concentrates on developing a methodology to graphically characterize Response Time as a function of tunable latency for existing database access Applications in a wired, single-threaded, multi-user, post-deployment client/server environment. A number of tools were used in developing this methodology which was not obvious from the tools' documentation. To test its feasibility before actual field use, we used an experimental setup to emulate the real user environment. In so doing, we now have two proposed methodologies: one for the experimental setup version (of the in-service scenario) and one for the "actual" in-service scenario. We present results obtained from the experimental method. The resulting graphs can be a consultation tool for network tuning and control, classification of user Applications by priority class-of-service, SLA negotiation and manual QoS provisioning.
Erik Elmroth - One of the best experts on this subject based on the ideXlab platform.
-
a hybrid cloud controller for vertical memory elasticity
Future Generation Computer Systems, 2016Co-Authors: Soodeh Farokhi, Ewnetu Bayuh Lakew, Ivona Brandic, Pooyan Jamshidi, Erik ElmrothAbstract:Web-facing Applications are expected to provide certain performance guarantees despite dynamic and continuous workload changes. As a result, Application owners are using cloud computing as it offers the ability to dynamically provision computing resources (e.g., memory, CPU) in Response to changes in workload demands to meet performance targets and eliminates upfront costs. Horizontal, vertical, and the combination of the two are the possible dimensions that cloud Application can be scaled in terms of the allocated resources. In vertical elasticity as the focus of this work, the size of virtual machines (VMs) can be adjusted in terms of allocated computing resources according to the runTime workload. A commonly used vertical resource elasticity approach is realized by deciding based on resource utilization, named capacity-based. While a new trend is to use the Application performance as a decision making criterion, and such an approach is named performance-based. This paper discusses these two approaches and proposes a novel hybrid elasticity approach that takes into account both the Application performance and the resource utilization to leverage the benefits of both approaches. The proposed approach is used in realizing vertical elasticity of memory (named as vertical memory elasticity), where the allocated memory of the VM is auto-scaled at runTime. To this aim, we use control theory to synthesize a feedback controller that meets the Application performance constraints by auto-scaling the allocated memory, i.e., applying vertical memory elasticity. Different from the existing vertical resource elasticity approaches, the novelty of our work lies in utilizing both the memory utilization and Application Response Time as decision making criteria. To verify the resource efficiency and the ability of the controller in handling unexpected workloads, we have implemented the controller on top of the Xen hypervisor and performed a series of experiments using the RUBBoS interactive benchmark Application, under synthetic and real workloads including Wikipedia and FIFA. The results reveal that the hybrid controller meets the Application performance target with better performance stability (i.e., lower standard deviation of Response Time), while achieving a high memory utilization (close to 83%), and allocating less memory compared to all other baseline controllers. A feedback controller for vertically scale the memory of cloud Applications is proposed.The controller is able to tune the memory in order to meet the desired performance.The Application performance and memory utilization are used as decision making criteria.The feedback controller guarantees the stability of the cloud Application.The results show the efficiency in memory usage when the feedback controller is used.
John Zahorjan - One of the best experts on this subject based on the ideXlab platform.
-
the implications of cache affinity on processor scheduling for multiprogrammed shared memory multiprocessors
Symposium on Operating Systems Principles, 1991Co-Authors: Raj Vaswani, John ZahorjanAbstract:In a shared memory multiprocessor with caches, executing tasks develop "affinity" to processors by filling their caches with data and instructions during execution. A scheduling policy that ignores this affinity may waste processing power by causing excessive cache refilling.Our work focuses on quantifying the effect of processor reallocation on the performance of various parallel Applications multiprogrammed on a shared memory multiprocessor, and on evaluating how the magnitude of this cost affects the choice of scheduling policy.We first identify the components of Application Response Time, including processor reallocation costs. Next, we measure the impact of reallocation on the cache behavior of several parallel Applications executing on a Sequent Symmetry multiprocessor. We also measure, the performance of these Applications under a number of alternative allocation policies. These experiments lead us to conclude that on current machines processor affinity has only a very weak influence on the choice of scheduling discipline, and that the benefits of frequent processor reallocation (in Response to the changing parallelism of jobs) outweigh the penalties imposed by such reallocation. Finally, we use this experimental data to parameterize a simple analytic model, allowing us to evaluate the effect of processor affinity on future machines, those containing faster processors and larger caches.