9516398
The CenSSIS image database
The CenSSIS image database is a scientific database that enables effective data management and collaboration to accelerate fundamental research. This paper describes the design and use of a state-of-the-art relational image database management system, accessible through a standard Web-browser interface. The application utilizes a robust security architecture and is designed for efficient data submission. Our database query engine provides complex query capabilities to facilitate fast and efficient data retrieval. The system offers a highly extensible metadata schema, with the option of storing data within a hierarchical format.
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.
10467092
Marshalgen: A Package for Semi-Automatic Marshaling of Objects
Marshaling or serialization of objects is an important component of both distributed and parallel computing. Current systems impose a significant burden on the programmer for describing the marshaling of complex, recursive data structures. Marshalgen provides a semi-automatic process for marshaling in C and C++. Marshalgen avoids the need for complex IDLs and auxiliary routines. It is based on annotations of the existing source code.
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.
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.
903722
Mobile telemedicine sensor networks with low-energy data query and network lifetime considerations
In this paper, we use an integrated architecture that takes advantage of the low cost mobile sensor networks and 3G cellular networks to accommodate multimedia medical calls with differentiated Quality-of-Service (QoS) requirements. We propose a low-energy, distributed, and concentric-zone-based data query mechanism that takes advantages of hierarchical ad hoc routing algorithms to enable a medical specialist to collect physiological data from mobile and/or remote patients. The medical specialist uses cellular network to report patients' data to the medical center. Moreover, we propose a transmission scheme among different zones with balance-based energy efficiency, which can extend network lifetime. We evaluate the validity of our proposals through simulations and analyze their performance. Our results clearly indicate the energy efficiency of the proposed sensor network query algorithms and the efficiency of our multiclass medical call admission control scheme in terms of meeting the multimedia telemedicine QoS requirements.
7266719
Two processor scheduling with real release times and deadlines
In a hard real-time system, critical tasks are subject to timing constraints such as release times and deadlines. All timing constraints must be satisfied when tasks are executed. Nevertheless, given a set of tasks, finding a feasible schedule which satisfies all timing constraints is NP-complete even on one processor.In this paper, we study the following special non-pre-emptive two processor scheduling problem: Given a set of UET (Unit Execution Time) tasks with arbitrary precedence constraints, individual real release times and deadlines, find a feasible schedule on two identical processors whenever one exists. The complexity status of this problem has been open for a long time. we propose the first polynomial algorithm for this problem. Our algorithm is underpinned by the key consistency notion: successor-tree-consistency. The time complexity of our algorithm is O(n4), where n is the number of tasks.
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