This paper tackles online scheduling of electric vehicles (EVs) in an adaptive charging network (ACN) with local and global peak constraints. Given the aggregate charging demand of the EVs and the peak constraints of ...
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This paper tackles online scheduling of electric vehicles (EVs) in an adaptive charging network (ACN) with local and global peak constraints. Given the aggregate charging demand of the EVs and the peak constraints of the ACN, it might be infeasible to fully charge all the EVs according to their charging demand. Two alternatives in such resource-limited scenarios are to maximize the social welfare by partially charging the EVs (fractional model) or selecting a subset of EVs and fully charge them (integral model). The technical challenge is the need for online solution design since in practical scenarios the scheduler has no or limited information of future arrivals in a time-coupled underlying problem. For the fractional model, we devise both offline and online algorithms. We prove that the offline algorithm is optimal. Using competitive ratio as the performance measure, we prove the online algorithm achieves a competitive ratio of 2. The integral model, however, is more challenging since the underlying problem is strongly NP-hard due to 0/1 selection criteria of EVs. Hence, efficient solution design is challenging even in offline setting. For offline setting, we devise a low-complexity primal-dual scheduling algorithm that achieves a bounded approximation ratio. Built upon the offline approximate algorithm, we propose an online algorithm and analyze its competitive ratio in special cases. Extensive trace-driven experimental results show that the performance of the proposed online algorithms is close to the offline optimum, and outperform the existing solutions.
This paper considers the problem of designing scheduling algorithms for multichannel (e.g., OFDM-based) wireless downlink networks, with a large number of users and proportionally large bandwidth. For this system, whi...
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This paper considers the problem of designing scheduling algorithms for multichannel (e.g., OFDM-based) wireless downlink networks, with a large number of users and proportionally large bandwidth. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, it is shown that it has zero rate function in our setting). To address this, a class of algorithms called iterated Heaviest matching with Longest Queues First (iHLQF) is proposed. The algorithms in this class are shown to be throughput-optimal for a general class of arrival/channel processes, and also rate-function-optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes. iHLQF, however, has higher complexity than MaxWeight (n(4) versus n(2), respectively). To overcome this issue, a new algorithm called Server-Side Greedy (SSG) is proposed. It is shown that SSG is throughput-optimal, results in a much better per-user buffer overflow performance than the MaxWeight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n(2)) that is comparable to the MaxWeight algorithm. Thus, it provides a nice tradeoff between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations.
This paper investigates co-scheduling algorithms for processing a set of parallel applications. Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at sched...
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This paper investigates co-scheduling algorithms for processing a set of parallel applications. Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at scheduling several applications concurrently. We partition the original application set into a series of packs, which are executed one by one. A pack comprises several applications, each of them with an assigned number of processors, with the constraint that the total number of processors assigned within a pack does not exceed the maximum number of available processors. The objective is to determine a partition into packs, and an assignment of processors to applications, that minimize the sum of the execution times of the packs. We thoroughly study the complexity of this optimization problem, and propose several heuristics that exhibit very good performance on a variety of workloads, whose application execution times model profiles of parallel scientific codes. We show that co-scheduling leads to faster workload completion time (40 % improvement on average over traditional scheduling) and to faster response times (50 % improvement). Hence, co-scheduling increases system throughput and saves energy, leading to significant benefits from both the user and system perspectives.
It is shown that the performance of the maximal scheduling algorithm in wireless ad hoc networks under the hypergraph interference model can be further away from optimal than previously known. The exact worst-case per...
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It is shown that the performance of the maximal scheduling algorithm in wireless ad hoc networks under the hypergraph interference model can be further away from optimal than previously known. The exact worst-case performance of this distributed, greedy scheduling algorithm is analyzed.
scheduling MAC-layer transmissions in multi-hop wireless networks is an active and stimulating area of research. There are several interesting algorithms proposed in the literature in the problem space of scheduling f...
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scheduling MAC-layer transmissions in multi-hop wireless networks is an active and stimulating area of research. There are several interesting algorithms proposed in the literature in the problem space of scheduling for multi-hop wireless networks, specifically for (a) WiMAX mesh networks, (b) long distance multi-hop WiFi networks, and (c) Vehicular Ad-hoc Networks (VANETs). In general, these algorithms have several dimensions in terms of the assumptions made, the input space considered and the solution space generated. In this context, the goal of this survey is three-fold. Firstly, we classify the scheduling algorithms proposed in the literature based on following parameters: problem setting, problem goal, type of inputs and solution technique. Secondly, we describe different scheduling algorithms based on this classification framework. We specifically cover the state-of-the-art scheduling mechanisms proposed for generic multichannel, multi-radio wireless mesh networks and in particular scheduling algorithms for WiMAX mesh networks, long distance mesh networks and vehicular ad-hoc networks. We describe scheduling algorithms which consider scheduling data, voice as well as video traffic. Finally, we compare these algorithms based on our classification parameters. We also critique individual mechanisms and point out the practicality and the limitations, wherever applicable. We observe that, the literature in the domain of scheduling for wireless mesh network is quite extensive, in terms of depth as well as breadth. Our classification framework helps in understanding the pros and cons of various aspects of scheduling for wireless multi-hop (popularly known as wireless mesh) networks. We also list desirable properties of any scheduling mechanism and use our classification framework to point out the open research issues in the space of scheduling for wireless mesh networks.
In this paper, we consider low complexity user scheduling algorithms for multiuser multiple-input multiple-output systems employing successive zero-forcing precoding. Optimal scheduling involves an exhaustive search (...
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In this paper, we consider low complexity user scheduling algorithms for multiuser multiple-input multiple-output systems employing successive zero-forcing precoding. Optimal scheduling involves an exhaustive search (ES), which is prohibitively complex. Greedy algorithms (GrAs) with heuristic scheduling metrics achieve performance close to that of the ES. Meanwhile, genetic algorithms (GAs) are a rapid suboptimal option of optimising utility (e.g. scheduling) metrics. Herein, we evaluate the performance and complexity of greedy and genetic scheduling algorithms for successive zero-forcing. We also propose and evaluate two hybrid algorithms combining the traits of the GrA and GA. The algorithms' performance is assessed through a series of computer simulations. We demonstrate both the GrA and GA achieve a near-optimal sum rate with low complexity, whereas the hybrid algorithms further enhance the GrA and GA performance without an increase in the order of *** (C) 2012 John Wiley & Sons, Ltd.
The performance of scheduling algorithms for a reservation system is investigated. In this system, a user request is characterised by its start time, resource requirement and holding time. Of interest are scheduling a...
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The performance of scheduling algorithms for a reservation system is investigated. In this system, a user request is characterised by its start time, resource requirement and holding time. Of interest are scheduling algorithms to handle user requests in a loss system where resource requirements may vary. A Markov decision process formulation is used to obtain the optimal scheduling decisions. Two special cases are considered in depth;they correspond to optimal algorithms that minimise the blocking probability and maximise the channel utilisation, respectively. Analytic results are also obtained for the blocking probability and channel utilisation for an arbitrary scheduling algorithm. Using these results, the performance of first come, first served (FCFS) and the two optimal algorithms is compared. We also prove that FCFS is optimal for maximising channel utilisation when the resource requirement follows a uniform distribution.
In this paper, we are interested in using large-deviations theory to characterize the asymptotic decay-rate of the queue-overflow probability for distributed wireless scheduling algorithms, as the overflow threshold a...
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In this paper, we are interested in using large-deviations theory to characterize the asymptotic decay-rate of the queue-overflow probability for distributed wireless scheduling algorithms, as the overflow threshold approaches infinity. We consider ad hoc wireless networks where each link interferes with a given set of other links, and we focus on a distributed scheduling algorithm called Q-SCHED, which is introduced by Gupta et al. First, we derive a lower bound on the asymptotic decay rate of the queue-overflow probability for Q-SCHED. We then present an upper bound on the decay rate for all possible algorithms operating on the same network. Finally, using these bounds, we are able to conclude that, subject to a given constraint on the asymptotic decay rate of the queue-overflow probability, Q-SCHED can support a provable fraction of the offered loads achievable by any algorithms. (C) 2010 Elsevier B.V. All rights reserved.
scheduling algorithms are important components in the provision of guaranteed quality of service parameters such as delay, delay jitter, packet loss rate, or throughout. The design of scheduling algorithms for mobile ...
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scheduling algorithms are important components in the provision of guaranteed quality of service parameters such as delay, delay jitter, packet loss rate, or throughout. The design of scheduling algorithms for mobile communication networks is especially challenging given the highly variable link error rates and capacities, and the changing mobile station connectivity typically encountered in such networks. This article provides a survey of scheduling techniques for several types of wireless networks. Some of the challenges in designing such schedulers are first discussed. Desirable features and classifications of schedulers are then reviewed. This is followed by a discussion of several scheduling algorithms which have been proposed for TDMA, CDMA, and multihop packet networks.
In this paper, we have considered the distributed scheduling problem for channel access in TDMA wireless mesh networks. The problem is to assign time-slot(s) for nodes to access the channels, and it is guaranteed that...
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In this paper, we have considered the distributed scheduling problem for channel access in TDMA wireless mesh networks. The problem is to assign time-slot(s) for nodes to access the channels, and it is guaranteed that nodes can communicate with all their one-hop neighbors in the assigned time-slot(s). And the objective is to minimize the cycle length, i.e., the total number of different time-slots in one scheduling cycle. In single-channel ad hoc networks, the best known result for this problem is proved to be K (2) in arbitrary graphs (IEEE Trans Comput C-36(6):729-737, 1987) and 25K in unit disk graphs (IEEE/ACM Trans Netw pp 166-177, 1993) with K as the maximum node degree. There are multiple channels in wireless mesh networks, and different nodes can use different control channels to reduce congestion on the control channels. In this paper, we have considered two scheduling models for wireless mesh networks. The first model is that each node has two radios, and the scheduling is simultaneously done on the two radios. We have proved that the upper bound of the cycle length in arbitrary graphs can be 2K. The second model is that the time-slots are scheduled for the nodes regardless of the number of radios on them. In this case, we have proved that the upper bound can be (4K-2). We also have proposed greedy algorithms with different criterion. The basic idea of these algorithms is to organize the conflicting nodes by special criterion, such as node identification, node degree, the number of conflicting neighbors, etc. And a node cannot be assigned to a time-slot(s) until all neighbor nodes, which have higher criterion and might conflict with the current node, are assigned time-slot(s) already. All these algorithms are fully distributed and easy to realize. Simulations are also done to verify the performance of these algorithms.
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