246686
Time/utility function decomposition techniques for utility accrual scheduling algorithms in real-time distributed systems
We consider Real-Time CORBA 1.2's distributable threads (DTs), whose time constraints are specified using time/utility functions (TUFs), operating in legacy environments. In legacy environments, system node resources - both physical and logical - are shared among time-critical DTs and local applications that may also be time-critical. Hence, DTs that are scheduled using their propagated TUFs, as mandated by Real-Time CORBA 1.2's Case 2 approach, may suffer performance degradation, if a node utility accrual (UA) scheduler achieves higher locally accrued utility by giving higher eligibility to local threads than to DTs. To alleviate this, we consider decomposing TUFs of DTs into "sub-TUFs" for scheduling segments of DTs. We present five decomposition techniques, called UT, SCEQF, SCALL, OPTCON, and TUFS, which are specific to different classes of UA scheduling algorithms, such as those that use utility density and those that use deadline as their key decision metric. Our experimental studies identify the decomposition technique that performs best for each class of UA scheduling algorithms. In particular, our studies show that OPTCON and TUFS perform best for utility density-based UA algorithms, while SCEQF and SCALL perform best for deadline-based UA algorithms.
15728349
Enhanced End-System Support for Multimedia Transmission over the Differentiated Services Network
Proposed as a scalable solution to provide Quality of Service (QoS) networks, Differentiated Services (DiffServ) architecture enables service providers to offer each customer a range of services that are differentiated on the basis of performance. However, up to now little work discusses how to provide effective communication support for multimedia applications over the differentiated services network. In this paper we present a new enhanced communication approach at the end system to support distributed multimedia applications. Two new mechanisms are highlighted in our approach: enhanced communication stack to support differentiation within one flow, and the network-awareness provision for applications at the end system. Our approach improves the capability of both error resilience and flexible rate control for transmitting compressed multimedia bitstreams, particularly those using scalable coding technologies. We also develop an object-based video transmission system as an application instance to take advantage of the enhanced communication approach. Experimental results demonstrate the effectiveness of our proposed methods.
2473089
Energy-efficient, utility accrual real-time scheduling under the unimodal arbitrary arrival model
We present an energy-efficient real-time scheduling algorithm called EUA*, for the unimodal arbitrary arrival model (or UAM). UAM embodies a "stronger" adversary than most arrival models. The algorithm considers application activities that are subject to time/utility function time constraints, UAM, and the multi-criteria scheduling objective of probabilistically satisfying utility lower bounds, and maximizing system-level energy efficiency. Since the scheduling problem is intractable, EUA* allocates CPU cycles, scales clock frequency, and heuristically computes schedules using statistical estimates of cycle demands, in polynomial-time. We establish that EUA* achieves optimal timeliness during under-loads, and identify the conditions under which timeliness assurances hold. Our simulation experiments illustrate EUA*'s superiority.
6769302
A utility accrual scheduling algorithm for real-time activities with mutual exclusion resource constraints
This paper presents a uni-processor real-time scheduling algorithm called the generic utility scheduling algorithm (which we refer to simply as GUS). GUS solves a previously open real-time scheduling problem-scheduling application activities that have time constraints specified using arbitrarily shaped time/utility functions and have mutual exclusion resource constraints. A time/ utility function are a time constraint specification that describes an activity's utility to the system as a function of that activity's completion time. Given such time and resource constraints, we consider the scheduling objective of maximizing the total utility that is accrued by the completion of all activities. Since this problem is NP-hard, GUS heuristically computes schedules with a polynomial-time cost of O(n/sup 3/) at each scheduling event, where n is the number of activities in the ready queue. We evaluate the performance of GUS through simulation and by an actual implementation on a real-time POSIX operating system. Our simulation studies and implementation measurements reveal that GUS performs close to, if not better than, the existing algorithms for the cases that they apply. Furthermore, we analytically establish several properties of GUS.
10090646
On Multiprocessor Utility Accrual Real-Time Scheduling with Statistical Timing Assurances
We present the first Utility Accrual (or UA) real-time scheduling algorithm for multiprocessors, called gMUA. The algorithm considers an application model where real-time activities are subject to time/utility function time constraints, variable execution time demands, and resource overloads where the total activity utilization demand exceeds the total capacity of all processors. We establish several properties of gMUA including optimal total utility (for a special case), conditions under which individual activity utility lower bounds are satisfied, a lower bound on system-wide total accrued utility, and bounded sensitivity for assurances to variations in execution time demand estimates. Our simulation experiments confirm our analysis and illustrate the algorithm's effectiveness
61408369
Utility Accrual Real-Time Scheduling under Variable Cost Functions
We present a utility accrual real-time scheduling algorithm called CIC-VCUA for tasks whose execution times are functions of their starting times (and, potentially, other factors). We model such variable execution times using variable cost functions (or VCFs). The algorithm considers application activities that are subject to time/utility function time constraints, execution times described using VCFs, and mutual exclusion constraints on concurrent sharing of non-CPU resources. We consider the twofold scheduling objective of 1) assuring that the maximum interval between any two consecutive, successful completions of job instances in an activity must not exceed the activity period (an application-specific objective) and 2) maximizing the system's total accrued utility while satisfying mutual exclusion resource constraints. Since the scheduling problem is intractable, CIC-VCUA is a polynomial-time heuristic algorithm. The algorithm statically computes worst-case task sojourn times, dynamically selects tasks for execution based on their potential utility density, and completes tasks at specific times. We establish that CIC-VCUA achieves optimal timeliness during underloads, and tightly upper bounds inter and intratask completion times. Our simulation experiments confirm the algorithm's effectiveness and superiority
19790752
Classification of Battlefield Ground Vehicles Using Acoustic Features and Fuzzy Logic Rule-Based Classifiers
In this paper, we demonstrate, through the multicategory classification of battlefield ground vehicles using acoustic features, how it is straightforward to directly exploit the information inherent in a problem to determine the number of rules, and subsequently the architecture, of fuzzy logic rule-based classifiers (FLRBC). We propose three FLRBC architectures, one non-hierarchical and two hierarchical (HFLRBC), conduct experiments to evaluate the performances of these architectures, and compare them to a Bayesian classifier. Our experimental results show that: 1) for each classifier the performance in the adaptive mode that uses simple majority voting is much better than in the non-adaptive mode; 2) all FLRBCs perform substantially better than the Bayesian classifier; 3) interval type-2 (T2) FLRBCs perform better than their competing type-1 (T1) FLRBCs, although sometimes not by much; 4) the interval T2 nonhierarchical and HFLRBC-series architectures perform the best; and 5) all FLRBCs achieve higher than the acceptable 80% classification accuracy
546715
Minimising the Energy Consumption of Real-Time Tasks with Precedence Constraints on a Single Processor
Energy-aware task scheduling is critical for real-time embedded systems. Although dynamic power has traditionally been a primary source of processor power consumption, leakage power is becoming increasingly important. In this paper, we present two optimal energy-aware polynomial-time algorithms for scheduling a set of tasks with release times, deadlines and precedence constraints on a single processor with continuous voltages. Our algorithms are guaranteed to minimise the total energy consumption of all tasks while minimising their maximum lateness under two power models: the dynamic power model where the dynamic power dominates the processor power consumption and the dynamic and leakage power model where both dynamic power and leakage power are significant sources of the processor power consumption. The time complexities of both algorithms are O(n3) , where n is the number of tasks
9249562
A robust structure-adaptive hybrid vector filter for color image restoration
A robust structure-adaptive hybrid vector filter is proposed for digital color image restoration in this paper. At each pixel location, the image vector (i.e., pixel) is first classified into several different signal activity categories by applying a modified quadtree decomposition to luminance component (image) of the input color image. A weight-adaptive vector filtering operation with an optimal window is then activated to achieve the best tradeoff between noise suppression and detail preservation. Through extensive simulation experiments conducted using a wide range of test color images, the filter has demonstrated superior performance to that of a number of well known benchmark techniques, in terms of both standard objective measurements and perceived image quality, in suppressing several distinct types of noise commonly considered in color image restoration, including Gaussian noise, impulse noise, and mixed noise.
12829985
Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 2, Inverse Problems
In Part 1 of this two-part paper, we bounded the centroid of a symmetric interval type-2 fuzzy set (T2 FS), and consequently its uncertainty, using geometric properties of its footprint of uncertainty (FOU). We then used these bounds to solve forward problems, i.e., to go from parametric interval T2 FS models to data. The main purpose of the present paper is to formulate and solve inverse problems, i.e., to go from uncertain data to parametric interval T2 FS models, which we call type-2 fuzzistics. Given interval data collected from people about a phrase, and the inherent uncertainties associated with that data, which can be described statistically using the first- and second-order statistics about the end-point data, we establish parametric FOUs such that their uncertainty bounds are directly connected to statistical uncertainty bounds. These results should find applicability in computing with words
306090
VMNet: Realistic Emulation of Wireless Sensor Networks
Many research activities on wireless sensor networks (WSNs) need detailed performance statistics about protocols, systems, and applications; however, current simulation tools and testbeds lack mechanisms to report these statistics realistically and conveniently. To address this need, we have developed a WSN emulator, VMNet. VMNet emulates networked sensor nodes at the level of CPU clock cycles and executes the binary code of real applications directly. It emulates the radio channel with loss and noise as well as emulates the peripherals in sufficient detail. Moreover, VMNet takes parameter values from the real world and logs detailed runtime information of emulated nodes. Consequently, the application performance, both in response time and in power consumption, is reported realistically in VMNet, as demonstrated by our comparison studies with real sensor networks