8218476
A resource allocation model for QoS management
Quality of service (QoS) has been receiving wide attention in many research communities including networking, multimedia systems, real-time systems and distributed systems. In large distributed systems such as those used in defense systems, on-demand service and inter-networked systems, applications contending for system resources must satisfy timing, reliability and security constraints as well as application-specific quality requirements. Allocating sufficient resources to different applications in order to satisfy various requirements is a fundamental problem in these situations. A basic yet flexible model for performance-driven resource allocations can therefore be useful in making appropriate tradeoffs. We present an analytical model for QoS management in systems which must satisfy application needs along multiple dimensions such as timeliness, reliable delivery schemes, cryptographic security and data quality. We refer to this model as Q-RAM (QoS-based Resource Allocation Model). The model assumes a system with multiple concurrent applications, each of which can operate at different levels of quality based on the system resources available to it. The goal of the model is to be able to allocate resources to the various applications such that the overall system utility is maximized under the constraint that each application can meet its minimum needs. We identify resource profiles of applications which allow such decisions to be made efficiently and in real-time. We also identify application utility functions along different dimensions which are composable to form unique application requirement profiles. We use a video-conferencing system to illustrate the model.
5320438
On quality of service optimization with discrete QoS options
We present a QoS management framework that enables us to quantitatively measure QoS, and to analytically plan and allocate resources. In this model, end users' quality preferences are considered when system resources are apportional across multiple applications such that the net utility that accrues to the end-users is maximized. We previously worked with continuous QoS dimensions, and assumed that the utility gained by improvements along a QoS dimension were always representable by concave functions. In this paper we relax both assumptions. One, we support discrete QoS operating points. Two, we make no assumptions about the concavity of the utility functions. Using these as the basis, we tackle the problem of maximizing system utility by allocating a single finite resource to satisfy the QoS requirements of multiple applications along multiple QoS dimensions. We present two near-optimal algorithms to solve this problem. The first yields an allocation within a known bounded distance from the optimal solution, and the second yields an allocation whose distance from the optimal solution can be explicitly controlled by the QoS manager, We compare the run-times of these near-optimal algorithms and their solution quality relative to the optimal allocation, which in turn is computed using dynamic programming. These detailed evaluations provide practical insight into which of these algorithms can be used online in real-time systems.
203663688
Practical Solutions for QoS-Based Resource Allocation
An apparatus and method is disclosed for forming a liquid-tight container having a rectangular cross-section formed from a one-piece, T-shaped blank of paperboard material. The carton preferably includes an access flap and straw element on one side thereof which, when manually lifted, exposes an end of the straw element from which the contents of the carton may be consumed by a user. The apparatus is compact in nature, possessing relatively few transport mechanisms which advance the T-shaped carton blank through a plurality of work stations. A novel method and apparatus for serially applying the straw element and access panel to the carton blank is disclosed, wherein the straw element and a length of polyethylene coated Mylar tape is automatically bonded to the carton blank upon a rotating heat sealing and alignment drum. A conveyor for collating a plural number of the carton blanks about a forming mandrel is also provided, and is positioned transversely to the remainder of the apparatus thereby significantly reducing the overall size of the apparatus. An ultrasonic welder bonds the side seams and end closure panels of the container upon a rotating crossbar mandrel which eliminates any misalignment during the sealing process. A substantially rigid conveyor transport carries a plurality of the carton blanks through pre-form, filler, and end closure work stations, and includes plural anvils for the ultrasonic welding process. An ejector mechanism is additionally provided which ejects the filled carton blanks from the rigid conveyor along a dual direction path, thereby eliminating the possibility of creasing or puncturing the filled and sealed container. The apparatus of the present invention additionally accommodates the production of differing size containers with only minor adjustments.
8167367
Online QoS Optimization Using Service Classes in Surveillance Radar Systems
Many application level qualities are functions of available computation resources. Recent studies have handled the computation resource allocation problem to maximize the overall application quality. However, such QoS problems are fundamentally multi-dimensional optimization problems that require extensive computation. Therefore, online usage of optimization procedures may significantly reduce the computation resource available for applications. This raises the question of how to best use the optimization procedures for dynamic real-time task sets. In dynamic real-time systems, it is important to improve the performance by re-allocating the resources adapting to dynamic situations. However, the overhead of changing task parameters (i.e., algorithms and frequencies) for resource re-allocation is non-negligible in many applications. Thus, too frequent change of resource allocation may not be desirable. This paper proposes a method called service classes configuration to address the QoS problem with dynamic arrival and departure of tasks. The method avoids online usage of optimization procedures by offline designing templates (called service classes) of resource allocation, which will be adaptively used depending on online situations. The service classes are designed by best trading-off the accuracy of dynamic adaptation against the overhead of resource re-allocation. A simplified radar application is used as an illustrative example.
10459627
Ab initio molecular orbital calculations of 3, 4-dihydro-1, 2-dioxin, 3, 6-dihydro-1, 2-dioxin, 4H-1, 3-dioxin (1, 3-diox-4-ene), and 2, 3-dihydro-1, 4-dioxin (1, 4-dioxene)
44631758
Agent-based forwarding strategies for reducing location management cost in mobile networks
A major issue with location management in mobile wireless networks is the high cost associated with location updates and searches. A search occurs when a caller needs to connect to a mobile user whose location is unknown to the caller and the network must locate the callee. An update occurs when a mobile user moves into a new registration area and the network is informed of the location change. We propose and analyze a class of new agent-based forwarding strategies with the objective to reduce the location management cost in mobile wireless networks. We develop analytical Markov models to compare the performance of the proposed strategies with existing location management schemes to demonstrate their feasibility and also to reveal conditions under which the proposed schemes are superior to existing ones.
40821829
Service class based online QoS management in surveillance radar systems
Many application level qualities are functions of available computation resources. Recent studies have handled the computation resource allocation problem to maximize the overall application quality. However such QoS problem is fundamentally a multi-dimensional optimization problem that requires extensive computation. Therefore, online usage of optimization procedures may significantly reduce the computation resource available for applications. This raises the question of how to best use the optimization procedures for dynamic real-time task sets. This paper proposes a method called service classes configuration to address the QoS problem with dynamic arrival and departure of tasks. A simplified radar application is used as an illustrative example.
16722634
Scaling applications to massively parallel machines using Projections performance analysis tool
Some of the most challenging applications to parallelize scalably are the ones that present a relatively small amount of computation per iteration. Multiple interacting performance challenges must be identified and solved to attain high parallel efficiency in such cases. We present case studies involving NAMD, a parallel classic molecular dynamics application for large biomolecular systems, and CPAIMD, Car-Parrinello ab initio molecular dynamics application, and efforts to scale them to large number of processors. Both applications are implemented in Charm++, and the performance analysis was carried out using Projections, the performance visualization/analysis tool associated with Charm++. We showcase a series of optimizations facilitated by Projections. The resultant performance of NAMD led to a Gordon Bell award at SC 2002 with unprecedented speedup on 3000 processors with teraflops level peak performance. We also explore the techniques for applying the performance visualization/analysis tool on future generation extreme-scale parallel machines and discuss the scalability issues with Projections.