536,617 research outputs found
Conclusions from the European Roadmap on Control of Computing Systems
The use of control-based methods for resource management in real-time computing and communication systems has gained a substantial interest recently. Applications areas include performance control of web-servers, dynamic resource management in embedded systems, traffic control in communication networks, transaction management in database servers, error control in software systems, and autonomic computing. Within the European EU/IST FP6 Network of Exellence ARTIST2 on Embedded System Design a roadmap on Control of Real-Time Computing Systems has recently been completed. The focus of the roadmap is how flexibility, adaptivity, performance and robustness can be achieved in a real-time computing or communication system through the use of control theory. The item that is controlled is in most cases the allocation of computing and communication resources, e.g., the distribution or scheduling of CPU time among different competing tasks, jobs, requests, or transactions, or the communication resources in a network. Due to this, control of computing systems also goes under the name of feedback scheduling. The roadmap is divided into six research areas: control of server systems, control of CPU resources, control of communication networks, error control of software systems, feedback scheduling of control systems, and control middleware. For each area an overview is given and challenges for future research are stated. The aim of this position paper is to summarize the conclusions concerning these research challenges. In this paper, we will only cover the first four of the areas above. A preliminary version of the roadmap can be found on http://www.control.lth.se/user/karlerik/roadmap1.pd
DRS: Dynamic Resource Scheduling for Real-Time Analytics over Fast Streams
In a data stream management system (DSMS), users register continuous queries,
and receive result updates as data arrive and expire. We focus on applications
with real-time constraints, in which the user must receive each result update
within a given period after the update occurs. To handle fast data, the DSMS is
commonly placed on top of a cloud infrastructure. Because stream properties
such as arrival rates can fluctuate unpredictably, cloud resources must be
dynamically provisioned and scheduled accordingly to ensure real-time response.
It is quite essential, for the existing systems or future developments, to
possess the ability of scheduling resources dynamically according to the
current workload, in order to avoid wasting resources, or failing in delivering
correct results on time. Motivated by this, we propose DRS, a novel dynamic
resource scheduler for cloud-based DSMSs. DRS overcomes three fundamental
challenges: (a) how to model the relationship between the provisioned resources
and query response time (b) where to best place resources; and (c) how to
measure system load with minimal overhead. In particular, DRS includes an
accurate performance model based on the theory of \emph{Jackson open queueing
networks} and is capable of handling \emph{arbitrary} operator topologies,
possibly with loops, splits and joins. Extensive experiments with real data
confirm that DRS achieves real-time response with close to optimal resource
consumption.Comment: This is the our latest version with certain modificatio
D-SAR: A Distributed Scheduling Algorithm for Real-time, Closed-Loop Control in Industrial Wireless Sensor and Actuator Networks
Current wireless standards and protocols for industrial applications such as WirelessHART and ISA100.11a typically use centralized network management techniques for communication scheduling and route establishment. However, large-scale centralized systems can have several drawbacks. They have difficulty in coping with disturbances or changes within the network in real-time. Large-scale centralized systems can also have highly variable latencies thus making them unsuitable for closed-loop control applications. To address these problems, this paper describes D-SAR, a distributed resource reservation algorithm which would allow source nodes to meet the Quality-of-Service (QoS) requirements of the application in real-time, when carrying out peer-to-peer communication. The presented solution uses concepts derived from relevant networking-related domains such as circuit switching and Asynchronous Transfer Mode (ATM) networks and applies them to wireless sensor and actuator networks
Digital Twinning in Smart Grid Networks: Interplay, Resource Allocation and Use Cases
Motivated by climate change, increasing industrialization and energy
reliability concerns, the smart grid is set to revolutionize traditional power
systems. Moreover, the exponential annual rise in number of grid-connected
users and emerging key players e.g. electric vehicles strain the limited radio
resources, which stresses the need for novel and scalable resource management
techniques. Digital twin is a cutting-edge virtualization technology that has
shown great potential by offering solutions for inherent bottlenecks in
traditional wireless networks. In this article, we set the stage for various
roles digital twinning can fulfill by optimizing congested radio resources in a
proactive and resilient smart grid. Digital twins can help smart grid networks
through real-time monitoring, advanced precise modeling and efficient radio
resource allocation for normal operations and service restoration following
unexpected events. However, reliable real-time communications, intricate
abstraction abilities, interoperability with other smart grid technologies,
robust computing capabilities and resilient security schemes are some open
challenges for future work on digital twins.Comment: 7 pages, 3 figure
INTELLIGENT AND ADAPTIVE FUZZY CONTROL SYSTEM FOR ENERGY EFFICIENT HOMES
âSmart housesâ have widely established their position as a research field during the last decade. Nowadays the technical solutions related to energy resource management are being rapidly developed and integrated into the daily lives of people. The energy resource management systems use sensor networks for receiving and processing information during the realia time. Smart house adaptive and intelligent solutions has advanced towards common environment, which can take care of the inhabitantsâ well-being in numerous ways. This paper propose to use a context sensitive and proactive fuzzy control system for controlling the automation processes in smart house environment. The designed monitoring system has adaptive and intelligent options, and it can operate using real time information received from sensors. The system is designed to operate fully in the background and can be installed to any exiting working system. This paper describes a central heating boiler control system implemented using the fuzzy control system designed. Author concentrates on the basic operation of such systems and present findings from the design process and initial tests
Quadratic nonseparable resource allocation problems with generalized bound constraints
We study a quadratic nonseparable resource allocation problem that arises in
the area of decentralized energy management (DEM), where unbalance in
electricity networks has to be minimized. In this problem, the given resource
is allocated over a set of activities that is divided into subsets, and a cost
is assigned to the overall allocated amount of resources to activities within
the same subset. We derive two efficient algorithms with
worst-case time complexity to solve this problem. For the special case where
all subsets have the same size, one of these algorithms even runs in linear
time given the subset size. Both algorithms are inspired by well-studied
breakpoint search methods for separable convex resource allocation problems.
Numerical evaluations on both real and synthetic data confirm the theoretical
efficiency of both algorithms and demonstrate their suitability for integration
in DEM systems
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