Design of distributed energy management systems composed of several agents such as factories and buildings is important for realizing smart cities. In addition, demand response for saving the power consumption is also...
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Design of distributed energy management systems composed of several agents such as factories and buildings is important for realizing smart cities. In addition, demand response for saving the power consumption is also important. In this paper, we propose a design method of distributed energy management systems with real-time demand response, in which both electrical energy and thermal energy are considered. Here, we use ADMM (Alternating Direction Method of Multipliers), which is well known as one of the powerful methods in distributed optimization. In the proposed method, demand response is performed in real-time, based on the difference between the planned demand and the actual value. Furthermore, utilizing a blockchain is also discussed. The effectiveness of the proposed method is presented by a numerical example. The importance of introducing a blockchain is pointed out by presenting the adverse effect of tampering the actual value.
We rigorously analyze load sharing (LS) in a distributedreal-time system, called HARTS (Hexagonal Architecture for real-timesystems), while considering LS-related communication activities, such as task transfers and...
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We rigorously analyze load sharing (LS) in a distributedreal-time system, called HARTS (Hexagonal Architecture for real-timesystems), while considering LS-related communication activities, such as task transfers and state-change broadcasts. First, we give an overview of the general distributedreal-time LS approach described in [1], [2], and then adapt it to HARTS by exploiting the topological properties of HARTS. Second, we model task arrival/completion/transfer activities in HARTS as a continuous-time Markov chain from which we derive the distribution of queue length and the rate of generating LS-related traffic-task transfer-out rate and state-region change broadcast rate. Third, we derive the distribution of packet delivery time as a function of LS-related traffic rates by characterizing the hexagonal mesh topology and the virtual cut-through capability of HARTS. Finally, we derive the distribution of task waiting time (the time a task is queued for execution plus the time it would spend if the task is to be transferred), from which the probability of a task failing to complete in time, called the probability of dynamic failure, can be computed. The results obtained from our analytic models are verified through event-driven simulations, and can be used to study the effects of varying various design parameters on the performance of LS while considering the details of LS-related communication activities.
The delivery delay in a point-to-point packet switching network is difficult to control due to the contention among randomly-arriving packets at each node and multihops a packet must travel between its source and dest...
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The delivery delay in a point-to-point packet switching network is difficult to control due to the contention among randomly-arriving packets at each node and multihops a packet must travel between its source and destination. Despite this difficulty, there are an increasing number of applications that require packets to be delivered reliably within prespecified delay bounds. This paper shows how this can be achieved by using real-time channels which make "soft" reservation of network resources to ensure the timely delivery of real-time packets. We first present theoretical results and detailed procedures for the establishment of real-time channels and then show how the basic real-time channels can be enhanced to be fault-tolerant using the multiple disjoint paths between a pair of communicating nodes. The contribution of the former is a tighter schedulability condition which makes more efficient use of network resources than any other existing approaches, and that of the latter is a significant improvement in fault tolerance over the basic real-time channel, which is inherently susceptible to component failures.
We present a proactive resource allocation algorithm, called BEA, for fault-tolerant asynchronous real-timedistributedsystems. BEA considers an application model where trans-node application timeliness requirements ...
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We present a proactive resource allocation algorithm, called BEA, for fault-tolerant asynchronous real-timedistributedsystems. BEA considers an application model where trans-node application timeliness requirements are expressed using benefit functions, and anticipated workload during future time intervals are expressed using adaptation functions. Furthermore, BEA considers an adaptation model where subtasks of application tasks are replicated at run-time for tolerating failures as well as for sharing workload increases. Given such models, the objective of the algorithm is to maximize the aggregate real-time benefit and the ability to tolerate host failures during the time window of adaptation functions. Since determining the optimal solution is computationally intractable, BEA heuristically computes suboptimal resource allocations in polynomial-time. We show that BEA can achieve almost the same fault-tolerance ability as full replication, and accrue most of real-time benefit that full replication can accrue. In the meanwhile, BEA requires much fewer replicas than full replication, and hence is cost effective. (C) 2004 Elsevier B.V. All rights reserved.
parallel high-performance computing is gaining momentum as a computing platform for many applications. In recent years, the research in software support for parallel computers has mainly addressed scientific and infor...
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Incremental, parallel development of distributedreal-timesystems is difficult. Architectural techniques and software tools developed at the Jet Propulsion Laboratory's (JPL's) Flight System Testbed (FST) mak...
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This paper presents a new language that integrates the real-time and distributed paradigms within the framework of a concurrent logic language. Concurrent logic languages (CLLs) are capable of expressing concurrence, ...
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This paper presents a new language that integrates the real-time and distributed paradigms within the framework of a concurrent logic language. Concurrent logic languages (CLLs) are capable of expressing concurrence, communication and nondeterminism in a natural way. That is, the intrinsic parallel semantics of the concurrent logic languages makes them well-suited for distributed programming. The proposed language is particularly suitable for loosely coupled systems and it contains mechanisms for distributed and real-time process control. A new execution model for concurrent logic languages is presented, which enables efficient distributed execution and real-time control. The model is introduced by giving an operational semantics for the language and the new model's implementation is discussed, including the definition of a new abstract machine and its implementation on a network of Unix workstations. Although the sequential core is not optimized, some previous results are discussed, showing the feasibility of the language's execution model for distributedreal-timesystems. The language is currently being used as the kernel language for a distributed simulation and validation tool for communication protocols. (C) 1997 Elsevier Science Ltd. All rights reserved.
Of critical importance to any real-time system is the issue of predictability. We divide overall system predictability into two parts: algorithmic and systemic. Algorithmic predictability is concerned with ensuring th...
ISBN:
(纸本)0769516084
Of critical importance to any real-time system is the issue of predictability. We divide overall system predictability into two parts: algorithmic and systemic. Algorithmic predictability is concerned with ensuring that the parallel simulation engine and model from a complexity point of view are able to consistently yield results within a real-time deadline. Systemic predictability is concerned with ensuring that OS scheduling, interrupts and virtual memory overheads are consistent over a real-time period. To provide a framework for investigating systemic predictability, we define a new class of parallel simulation called Extreme Simulation or XSim. An XSim is any analytic parallel simulation that is able to generate a statistically valid result by a real-time deadline. Typically, this deadline is between 10 and 100 milliseconds. XSims are expected to provide decision support to existing complex, realtimesystems. As a new design and implementation methodology for realizing XSims, we embed a state-of-the-art optimistic simulator into the Linux operating system. In this operating environment, OS scheduling and interrupts are disabled. Given a 50 millisecond model completion deadline, we observe that the XSim has a systemic predictability, measure of 98% compared with only 56% for the same time Warp system operating in user-level.
Some problems of a real-timedistributed computer system testing are considered. The authors approach suggests the introduction of redundancy into the system being diagnosed, which in essence is an event model of the ...
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作者：
GOSCINSKI, ADepartment of Computer Science
University College The University of New South Wales Australian Defence Force Academy Canberra Australian Capital Territory Australia
Two algorithms developed utilizing a priority-based event-ordering which manage mutual exclusion in distributedsystems—computer networks—are proposed. In these systems, processes communicate only by messages and do...
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Two algorithms developed utilizing a priority-based event-ordering which manage mutual exclusion in distributedsystems—computer networks—are proposed. In these systems, processes communicate only by messages and do not share memory. The computer network functions either (a) in an environment requiring priorities or (b) in a real-time environment. The algorithms are based on broadcast requests and token passing service approach, but the token need not be passed if no process wishes to enter the critical section. These algorithms are fully distributed and are insensitive to the relative speeds of node computers and communication links. They use only N messages per critical section, where N is the number of nodes (processes). The algorithms are optimal in the sense that a symmetrical, distributed algorithm cannot use fewer messages if requests are processed by each node computer concurrently. Both algorithms ensure freedom from starvation. There are mechanisms to handle node insertion and removal, node failure, the loss of the token, the existence of more than one token, and delivery of messages out of order.
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