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90
Scheduling to Minimize Average Completion Time: Offline and Online Algorithms
, 1996
"... Timeindexed linear programming formulations have recently received a great deal of attention for their practical effectiveness in solving a number of singlemachine scheduling problems. We show that these formulations are also an important tool in the design of approximation algorithms with good wo ..."
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Cited by 197 (27 self)
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Timeindexed linear programming formulations have recently received a great deal of attention for their practical effectiveness in solving a number of singlemachine scheduling problems. We show that these formulations are also an important tool in the design of approximation algorithms with good worstcase performance guarantees. We give simple new rounding techniques to convert an optimal fractional solution into a feasible schedule for which we can prove a constantfactor performance guarantee, thereby giving the first theoretical evidence of the strength of these relaxations. Specifically, we consider the problem of minimizing the total weighted job completion time on a single machine subject to precedence constraints, and give a polynomialtime (4 + ffl)approximation algorithm, for any ffl ? 0; the best previously known guarantee for this problem was superlogarithmic. With somewhat larger constants, we also show how to extend this result to the case with release date constraints, ...
Truthful Mechanisms for OneParameter Agents
"... In this paper, we show how to design truthful (dominant strategy) mechanisms for several combinatorial problems where each agent’s secret data is naturally expressed by a single positive real number. The goal of the mechanisms we consider is to allocate loads placed on the agents, and an agent’s sec ..."
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Cited by 191 (4 self)
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In this paper, we show how to design truthful (dominant strategy) mechanisms for several combinatorial problems where each agent’s secret data is naturally expressed by a single positive real number. The goal of the mechanisms we consider is to allocate loads placed on the agents, and an agent’s secret data is the cost she incurs per unit load. We give an exact characterization for the algorithms that can be used to design truthful mechanisms for such load balancing problems using appropriate side payments. We use our characterization to design polynomial time truthful mechanisms for several problems in combinatorial optimization to which the celebrated VCG mechanism does not apply. For scheduling related parallel machines (QjjCmax), we give a 3approximation mechanism based on randomized rounding of the optimal fractional solution. This problem is NPcomplete, and the standard approximation algorithms (greedy loadbalancing or the PTAS) cannot be used in truthful mechanisms. We show our mechanism to be frugal, in that the total payment needed is only a logarithmic factor more than the actual costs incurred by the machines, unless one machine dominates the total processing power. We also give truthful mechanisms for maximum flow, Qjj P Cj (scheduling related machines to minimize the sum of completion times), optimizing an affine function over a fixed set, and special cases of uncapacitated facility location. In addition, for Qjj P wjCj (minimizing the weighted sum of completion times), we prove a lower bound of 2 p 3 for the best approximation ratio achievable by a truthful mechanism.
Optimal TimeCritical Scheduling Via Resource Augmentation
, 1997
"... We consider two fundamental problems in dynamic scheduling: scheduling to meet deadlines in a preemptive multiprocessor setting, and scheduling to provide good response time in a number of scheduling environments. When viewed from the perspective of traditional worstcase analysis, no good online a ..."
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Cited by 131 (4 self)
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We consider two fundamental problems in dynamic scheduling: scheduling to meet deadlines in a preemptive multiprocessor setting, and scheduling to provide good response time in a number of scheduling environments. When viewed from the perspective of traditional worstcase analysis, no good online algorithms exist for these problems, and for some variants no good offline algorithms exist unless P = NP. We study these problems using a relaxed notion of competitive analysis, introduced by Kalyanasundaram and Pruhs, in which the online algorithm is allowed more resources than the optimal offline algorithm to which it is compared. Using this approach, we establish that several wellknown online algorithms, that have poor performance from an absolute worstcase perspective, are optimal for the problems in question when allowed moderately more resources. For the optimization of average flow time, these are the first results of any sort, for any NPhard version of the problem, that indicate that...
Online Load Balancing
 Theoretical Computer Science
, 1992
"... . We survey online load balancing on various models. 1 Introduction General: The machine load balancing problem is defined as follows: There are n parallel machines and a number of independent tasks (jobs); the tasks arrive at arbitrary times, where each task has an associated load vector and dur ..."
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Cited by 100 (15 self)
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. We survey online load balancing on various models. 1 Introduction General: The machine load balancing problem is defined as follows: There are n parallel machines and a number of independent tasks (jobs); the tasks arrive at arbitrary times, where each task has an associated load vector and duration. A task has to be assigned immediately to exactly one of the machines, thereby increasing the load on this machine by the amount specified by the corresponding coordinate of the load vector for the duration of the task. All tasks must be assigned, i.e., no admission control is allowed. The goal is usually to minimize the maximumload, but we also consider other goal functions. We mainly consider nonpreemptive load balancing, but in some cases we may allow preemption i.e., reassignments of tasks. All the decisions are made by a centralized controller. The online load balancing problem naturally arises in many applications involving allocation of resources. As a simple concrete example,...
The Competitiveness of OnLine Assignments
, 1992
"... Consider the online problem where a number of servers are ready to provide service to a set of customers. Each customer's job can be handled by any of a subset of the servers. Customers arrive onebyone and the problem is to assign each customer to an appropriate server in a manner that will balan ..."
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Cited by 99 (18 self)
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Consider the online problem where a number of servers are ready to provide service to a set of customers. Each customer's job can be handled by any of a subset of the servers. Customers arrive onebyone and the problem is to assign each customer to an appropriate server in a manner that will balance the load on the servers. This problem can be modeled in a natural way by a bipartite graph where the vertices of one side (customers) appear one at a time and the vertices of the other side (servers) are known in advance. We derive tight bounds on the competitive ratio in both deterministic and randomized cases. Let n denote the number of servers. In the deterministic case we provide an online algorithm that achieves a competitive ratio of k = dlog 2 ne (up to an additive 1) and prove that this is the best competitive ratio that can be achieved by any deterministic online algorithm. In a similar way we prove that the competitive ratio for the randomized case is k 0 = ln(n) (up to an a...
NonClairvoyant Scheduling
, 1993
"... Virtually all research in scheduling theory has been concerned with clairvoyant scheduling where it is assumed that the characteristics of a job (in particular, its execution time, release time and dependence on other jobs) are known a priori. This assumption is invalid for scheduling problems t ..."
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Cited by 87 (7 self)
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Virtually all research in scheduling theory has been concerned with clairvoyant scheduling where it is assumed that the characteristics of a job (in particular, its execution time, release time and dependence on other jobs) are known a priori. This assumption is invalid for scheduling problems that arise in timesharing operating systems where the scheduler must provide fast turnaround for processes being generated by the users without any knowledge of the future behavior of these processes. We study preemptive, nonclairvoyant scheduling schemes where the scheduler has no knowledge of the jobs' characteristics. We develop a model for evaluating scheduling strategies for single and multiprocessor systems. This model compares the nonclairvoyant scheduler against the optimal clairvoyant scheduler, and it takes into account various issues such as release times, execution time, preemption cost, and the interdependence between jobs. Within this model we study some standard sc...
Better Bounds For Online Scheduling
 SIAM JOURNAL ON COMPUTING
, 1997
"... We study a classical problem in online scheduling. A sequence of jobs must be scheduled on m identical parallel machines. As each job arrives, its processing time is known. The goal is to minimize the makespan. Bartal, Fiat, Karloff and Vohra [3] gave a deterministic online algorithm that is 1.986c ..."
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Cited by 75 (3 self)
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We study a classical problem in online scheduling. A sequence of jobs must be scheduled on m identical parallel machines. As each job arrives, its processing time is known. The goal is to minimize the makespan. Bartal, Fiat, Karloff and Vohra [3] gave a deterministic online algorithm that is 1.986competitive. Karger, Phillips and Torng [11] generalized the algorithm and proved an upper bound of 1.945. The best lower bound currently known on the competitive ratio that can be achieved by deterministic online algorithms it equal to 1.837. In this paper we present an improved deterministic online scheduling algorithm that is 1.923competitive, for all m 2. The algorithm is based on a new scheduling strategy, i.e., it is not a generalization of the approach by Bartal et al. Also, the algorithm has a simple structure. Furthermore, we develop a better lower bound. We prove that, for general m, no deterministic online scheduling algorithm can be better than 1.852competitive.
OnLine Routing of Virtual Circuits with Applications to Load Balancing and Machine Scheduling
, 1993
"... In this paper we study the problem of online allocation of routes to virtual circuits (both pointtopoint and multicast) where the goal is to minimize the required bandwidth. We concentrate on the case of permanent virtual circuits (i.e., once a circuit is established, it exists forever), and descr ..."
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Cited by 72 (7 self)
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In this paper we study the problem of online allocation of routes to virtual circuits (both pointtopoint and multicast) where the goal is to minimize the required bandwidth. We concentrate on the case of permanent virtual circuits (i.e., once a circuit is established, it exists forever), and describe an algorithm that achieves an O(log n) competitive ratio with respect to maximum congestion, where n is the number of nodes in the network. Informally, our results show that instead of knowing all of the future requests, it is sufficient to increase the bandwidth of the communication links by an O(log n) factor. We also show that this result is tight, i.e. for any online algorithm there exists a scenario in which O(log n) increase in bandwidth is necessary. We view virtual circuit routing as a generalization of an online load balancing problem, defined as follows: jobs arrive on line and each job must be assigned to one of the machines immediately upon arrival. Assigning a job to a machine increases this machine’s load by an amount that depends both on the job and on the machine. The goal is to minimize the maximum load. For the related machines case, we describe the first algorithm that achieves constant competitive ratio. For the unrelated case (with n machines), we describe a new method that yields O(log n)competitive
Online Load Balancing of Temporary Tasks
, 1993
"... This paper considers the nonpreemptive online load balancing problem where tasks have limited duration in time. Upon arrival, each task has to be immediately assigned to one of the machines, increasing the load on this machine for the duration of the task by an amount that depends on both the m ..."
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Cited by 60 (12 self)
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This paper considers the nonpreemptive online load balancing problem where tasks have limited duration in time. Upon arrival, each task has to be immediately assigned to one of the machines, increasing the load on this machine for the duration of the task by an amount that depends on both the machine and the task. The goal is to minimize the maximum load. Azar, Broder and Karlin studied the unknown duration case where the duration of a task is not known upon its arrival [4]. They focused on the special case in which for each task there is a subset of machines capable of executing it, and the increase in load due to assigning the task to one of these machines depends only on the task and not on the machine. For this case, they showed an O(n 2=3 )competitive algorithm, and an \Omega\Gamma p n) lower bound on the competitive ratio, where n is the number of the machines. This paper closes the gap by giving an O( p n)competitive algorithm. In addition, trying to overco...
EnergyEfficient Algorithms for . . .
, 2007
"... We study scheduling problems in batteryoperated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadlinebased settings, in this article we are interested in schedules that guarantee good respons ..."
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Cited by 59 (2 self)
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We study scheduling problems in batteryoperated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadlinebased settings, in this article we are interested in schedules that guarantee good response times. More specifically, our goal is to schedule a sequence of jobs on a variablespeed processor so as to minimize the total cost consisting of the energy consumption and the total flow time of all jobs. We first show that when the amount of work, for any job, may take an arbitrary value, then no online algorithm can achieve a constant competitive ratio. Therefore, most of the article is concerned with unitsize jobs. We devise a deterministic constant competitive online algorithm and show that