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
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
17279570
Protocol Design and Optimization for Delay/Fault-Tolerant Mobile Sensor Networks
While extensive studies have been carried out in the past several years for many sensor applications, they cannot be applied to the network with extremely low and intermittent connectivity, dubbed the delay/fault-tolerant mobile sensor network (DFT-MSN). Without end-to-end connections due to sparse network density and sensor node mobility, routing in DFT-MSN becomes localized and ties closely to medium access control, which naturally calls for merging Layer 3 and Layer 2 protocols in order to reduce overhead and improve network efficiency. DFT-MSN is fundamentally an opportunistic network, where the communication links exist only with certain probabilities and become the scarcest resource. At the same time, the sensor nodes in DFT-MSN have very limited battery power like those in other sensor networks. Clearly, there is a tradeoff between link utilization and energy efficiency. To address this tradeoff, we develop a cross-layer data delivery protocol for DFT-MSN, which includes two phases, i.e., the asynchronous phase and the synchronous phase. In the first phase, the sender contacts its neighbors to identify a set of appropriate receivers. Since no central control exists, the communication in the first phase is contention-based. In the second phase, the sender gains channel control and multicasts its data message to the receivers. Furthermore, several optimization issues in these two phases are identified, with solutions provided to reduce the collision probability and to balance between link utilization and energy efficiency. Our results show that the proposed cross-layer data delivery protocol for DFT-MSN achieves a high message delivery ratio with low energy consumption and an acceptable delay.
2876560
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
38263878
A Longest Cycle Version of Tutte's Wheels Theorem
An edgeeof a minimally 3-connected graphGis non-essential if and only if the graph obtained by contractingefromGis both 3-connected and simple. Suppose thatGis not a wheel. Tutte's Wheels Theorem states thatGhas at least one non-essential edge. We show that each longest cycle ofGcontains at least two non-essential edges. Moreover, each cycle ofGwhose edge set is not contained in a fan contains at least two non-essential edges. We characterize the minimally 3-connected graphs which contain a longest cycle containing exactly two non-essential edges.
10888393
Subsequence matching on structured time series data
Subsequence matching in time series databases is a useful technique, with applications in pattern matching, prediction, and rule discovery. Internal structure within the time series data can be used to improve these tasks, and provide important insight into the problem domain. This paper introduces our research effort in using the internal structure of a time series directly in the matching process. This idea is applied to the problem domain of respiratory motion data in cancer radiation treatment. We propose a comprehensive solution for analysis, clustering, and online prediction of respiratory motion using subsequence similarity matching. In this system, a motion signal is captured in real time as a data stream, and is analyzed immediately for treatment and also saved in a database for future study. A piecewise linear representation of the signal is generated from a finite state model, and is used as a query for subsequence matching. To ensure that the query subsequence is representative, we introduce the concept of subsequence stability, which can be used to dynamically adjust the query subsequence length. To satisfy the special needs of similarity matching over breathing patterns, a new subsequence similarity measure is introduced. This new measure uses a weighted L1 distance function to capture the relative importance of each source stream, amplitude, frequency, and proximity in time. From the subsequence similarity measure, stream and patient similarity can be defined, which are then used for offline and online applications. The matching results are analyzed and applied for motion prediction and correlation discovery. While our system has been customized for use in radiation therapy, our approach to time series modeling is general enough for application domains with structured time series data.
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.