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.
13992284
CPU scheduling for statistically-assured real-time performance and improved energy efficiency
We present a CPU scheduling algorithm, called Energy-efficient Utility Accrual Algorithm (or EUA), for battery-powered, embedded real-time systems. We consider an embedded software application model where repeatedly occurring application activities are subject to deadline constraints specified using step time/utility functions. For battery-powered embedded systems, system-level energy consumption is also a primary concern. We consider CPU scheduling that (1) provides assurances on individual and collective application timeliness behaviors and (2) maximizes system-level timeliness and energy efficiency. Since the scheduling problem is intractable, EUA heuristically computes CPU schedules with a polynomial-time cost. Several properties of EUA are analytically established, including timeliness optimality during under-load situations and statistical assurances on timeliness behavior. Further, our simulation results confirm EUA's superior performance.
8343325
Instruction Scheduling with Release Times and Deadlines on ILP Processors
ILP (instruction level parallelism) processors are being increasingly used in embedded systems. In embedded systems, instructions may be subject to timing constraints. An optimising compiler for ILP processors needs to find a feasible schedule for a set of time-constrained instructions. In this paper, we present a fast algorithm for scheduling instructions with precedence-latency constraints, individual integer release times and deadlines on an ILP processor with multiple functional units. The time complexity of our algorithm is O(n2 logd)+min{O(de), O(ne)}+min{O(ne), O(n2.376)}, where n is the number of instructions, e is the number of edges in the precedence graph and d is the maximum latency. Our algorithm is guaranteed to find a feasible schedule whenever one exists in the following special cases: 1) one functional unit, arbitrary precedence constraints, latencies in {0,1}, integer release times and deadlines; 2) two identical functional units, arbitrary precedence constraints, latencies of 0, integer release times and deadlines; 3) multiple identical functional units or multiple functional units of different types, monotone interval-ordered graph, integer release times and deadlines; 4) multiple identical functional units, in-forest, equal latencies, integer release times and deadlines. In case 1) our algorithm improves the existing fastest algorithm from O(n2 logn)+min{O(ne), O(n2.376)} to min{O(ne), O(n2.376)}. In case 2) our algorithm improves the existing fastest algorithm from O(ne+n2 logn) to min{O(ne), O(n2.376)}. In case 3) no polynomial time algorithm for multiple functional units of different types was known before
44791044
A Generalization of a Theorem of Dirac
In this paper, we give a generalization of a well-known result of Dirac that given any k vertices in a k-connected graph where k?2, there is a circuit containing all of them. We also generalize a result of Haggkvist and Thomassen. Our main result partially answers an open matroid question of Oxley.
35704952
Automatic Geometry-driven Ofdm Quality-of-service Analysis for Indoor Environments
This paper introduces a novel geometry-based simulation technique for the arbitrary indoor OFDM quality-of-service (QoS) analysis. This automatic geometry-driven approach integrates electromagnetic radio propagation modeling, channel characterization, and OFDM interference analysis to quantify the indoor OFDM performance through the off-site computer–aided procedures. Essential OFDM quality-of-service measures, such as signal-to-interference ratios (SIR) and bit error rates (BER) can be generated by this new analysis tool. The resulting QoS measure contours can be used by service providers and OFDM communication system designers to quantify the system performance and determine the optimal accessing locations for any indoor geometry.
16314153
A New Fragile Mesh Watermarking Algorithm for Authentication
In this paper, we propose a new fragile watermarking algorithm based on the global characteristics of the mesh geometry to authenticate 3D mesh models. In our method, a sequence of data bits is adaptively embedded into the mesh model by properly adjusting the vertex positions, and the bit information can be blindly extracted from the watermarked mesh model using a key. The embedding process is adaptive to the mesh model so that the watermarked mesh is perceptually indistinguishable from the original. We show that the embedded watermark is invariant to affine transformation but sensitive to other operations. Besides, the embedding strength is adjustable and can be controlled to a certain extent that even a trivial tampering with the watermarked mesh would lead the watermark signal to change. Therefore, unauthorized modifications of the mesh models can be detected and estimated.
452018
Online event-driven subsequence matching over financial data streams
Subsequence similarity matching in time series databases is an important research area for many applications. This paper presents a new approximate approach for automatic online subsequence similarity matching over massive data streams. With a simultaneous on-line segmentation and pruning algorithm over the incoming stream, the resulting piecewise linear representation of the data stream features high sensitivity and accuracy. The similarity definition is based on a permutation followed by a metric distance function, which provides the similarity search with flexibility, sensitivity and scalability. Also, the metric-based indexing methods can be applied for speed-up. To reduce the system burden, the event-driven similarity search is performed only when there is a potential event. The query sequence is the most recent subsequence of piecewise data representation of the incoming stream which is automatically generated by the system. The retrieved results can be analyzed in different ways according to the requirements of specific applications. This paper discusses an application for future data movement prediction based on statistical information. Experiments on real stock data are performed. The correctness of trend predictions is used to evaluate the performance of subsequence similarity matching.