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Distributed real-time computing system JStrom significantly improves performance on real-time data computing. However, JStorm may lead to a single point of failure, and upgrading JStorm system may cause instability of system. To efficiently solve these problems, we propose a task detection model based on the heartbeat detection and a two-level cluster load balancing model separately. We discover the...
Auto-scaling is a key challenge and benefit in cloud computing infrastructures where applications are deployed on one or more virtual machines (VMs) to balance efficiency in use against delivered performance. In different scenarios, there may be a need for either horizontal or vertical scaling. Therefore, scaling is an important operation of cloud management systems. One way to enable scaling as an...
Guaranteeing the system workload within design bounds is a basic requirement for a real-time system. Design-time bounds are usually based on worst-case activation patterns and worst-case execution time. While using the worst-case assumptions for online monitoring can guarantee the system safety, it also introduces unexplored slacks due to tasks consuming less than their worst-case execution times...
We provide a dynamic programming algorithm for the monitoring of a fragment of Timed Propositional Temporal Logic (TPTL) specifications. This fragment of TPTL, which is more expressive than Metric Temporal Logic, is characterized by independent time variables which enable the elicitation of complex real-time requirements. For this fragment, we provide an efficient polynomial time algorithm for off-line...
As the size and complexity of the system increase, centralized approaches will eventually be insufficient. Recently, distributed fault diagnosis (DFD) methods have been studied, where the global physical system is decomposed into different subsystems, each monitored by a local fault diagnoser (LFD). The performance of the DFD system is largely determined by its decomposition scheme. In a network system...
When a customer uses a service, he might change his initial requirement due to subjective reasons that could not be predicated by service providers. If this happened, service providers need to adjust the current service solution to adapt the new requirement with the objective of minimizing the change amplitude and cost. Placing this problem into AI-planning based service composition (PSC) scenario,...
Existing Big Data streams coming from social and other connected sensor networks exhibit intrinsic inter-dependency enabling unique challenges to scalable graph analytics. Data from these graphs is usually collected in different geographically located data servers making it suitable for distributed processing on clouds. While numerous solutions for large scale static graph analysis have been proposed,...
This minitrack focuses on topics related to the monitoring, control, and protection of electric power systems for real-time operations and short-term operations planning. The minitrack has two sessions.
A reliable traffic flow monitoring and traffic analysis approach using computer vision techniques has been proposed in this paper. The exponential increase in traffic density at urban intersections in the past few decades has raised precious and challenging demands to computer vision algorithms and technological solutions. The focus of this paper is to suggest a statistical based approach to determine...
The thermal-aware service rate assignment problem is a major challenge in cyber-physical systems. This problem is complex because of the severe temperature changes in uncertain physical environments and variable power consumption for each application, and these two effects might cause the system to overheat. This study proposes a dynamic-programming based service rate assignment with a feedback control...
Developments in sensors, miniaturization of low-power microelectronics, and wireless networks are becoming a significant opportunity for improving the quality of health care services. Since the population is growing, the need for high quality and efficient healthcare, both at home and in hospital, is becoming more important. This paper presents the innovative wireless sensor network based Mobile Real-time...
CAN bus systems are used in many industrial control applications, particularly automotive. Due to growing system and functional requirements, the low capacity of the CAN bus and usually strict conditions under which it is used in realtime applications, applicability of CAN bus is severely limited. The paper presents an approach for achieving high utilization and breathes new life to CAN bus based...
A novel structure of dynamic BP neural network (NDBP) with quick-time-variable real-time training-algorithm based on the modern dynamical control theory is developed in the CAD-grid 2# (??China-Austria-Data-Grid??-cooperation-project) and CEFSP 20080 5# (Chinese Education Foundation Science Project) and proposed in this paper. This NDBP suites to real-time modeling for tracking the process the characters...
Flexible signal processing on programmable platforms are increasingly important for consumer electronic applications and others. Scalable video algorithms (SVAs) using novel priority processing can guarantee real-time performance on programmable platforms even with limited resources. Dynamic resource allocation is required to maximize the overall output quality of independent, competing priority processing...
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